WO2013108246A2

WO2013108246A2 - Approximation of remaining travelable distance of a vehicle powered by a battery

Info

Publication number: WO2013108246A2
Application number: PCT/IL2013/050027
Authority: WO
Inventors: Boris Kabisher; Tamir Khason; Yuval Gilboa
Original assignee: Better Place GmbH; Better Place Labs Israel Ltd.
Priority date: 2012-01-17
Filing date: 2013-01-10
Publication date: 2013-07-25
Also published as: WO2013108246A3

Abstract

The invention provides a method and system for calculating a remaining travelable distance of a vehicle powered by a battery. In some embodiments the remaining travelable distance is determined using data indicative of a route of the vehicle, statistical data related to a route and to a user of the vehicle, and data about a measured charge level of the battery of the vehicle indicative of an amount of energy stored in the battery. The statistical data may be utilized to determine a rate of battery energy flow for the battery of the vehicle indicative of a rate of discharge and/or recharge of battery energy along at least a segment of road of the route, such that the remaining travelable distance may be determined based on the determined rate of battery energy flow and the charge level of the battery.

Description

APPROXIMATION OF REMAINING TRAVELABLE DISTANCE OF A VEHICLE POWERED BY A BATTERY

FIELD

The present disclosure relates to a system and method for calculating possible travelable distance of a vehicle powered by a battery.

BACKGROUND

The vehicle industry is encouraged nowadays to shift to hybrid and all-electric vehicles (generally referred to hereinafter as vehicles) employing rechargeable batteries, particularly due to their environmental benefits. The use of rechargeable batteries as a power source provides various advantages, inter alia due to their reusability, cost effective power management, and improved performance.

Since the energy capacity of a rechargeable battery is limited, it is important to present to the user of the vehicle accurate information about the remaining travelable distance that can be driven before the battery goes flat. This type of indication exists today in many of the vehicles sold on the market.

Some developments concerning energy management of batteries of electric vehicles are described in the following patent publications.

U.S. Patent No. 5,487,002, to Robert W. Diller and Jeffery W. Pavlat, describes an energy management system for vehicles having limited energy storage that provides energy consumption prediction for range calculation based on standard or memorized driving data.

International Patent Publication No. WO 2009/067810 to Neil S. Simmonds et al, describes a method for improving performance and charging of hybrid electric vehicles which determines whether the battery of the vehicles will fully discharge during a driving period along a route according to the driving conditions therealong.

U.S. Patent No. 5,627,752 to Michael Buck et al , describes a method for assisting a driver of a vehicle in optimum use of on-board energy supply, which determines a permissible consumption rate taking into account external driving resistances along a driven road. U.S. Patent No. 5,913,917 to Michael D. Murphy describes estimation of fuel consumption of a vehicle over a chosen trip route including a plurality of road segments wherein fuel consumption is estimated for each of the plurality of road segments using certain representative information. GENERAL DESCRIPTION

The electric motors used in electric vehicles convert energy supplied from the battery of the vehicle into rotary movement of the vehicle's wheels. Energy capacities of the batteries of electric vehicles are limited, and it is therefore important to present to the users of such vehicles accurate information about the remaining travelable distance that can be driven before the batteries installed in their vehicles go flat. This type of indication exists today in many of the vehicles sold on the market.

The estimation of the remaining travelable distance of electric vehicles as implemented nowadays typically provides a basic estimation of a reachable distance that the vehicle can drive based on limited information collected by the internal computer of the vehicle from internal units of the vehicle. It appears that such basic estimations tend to be error-prone, and may incur a large percentage of errors. The effect and price of such errors can be significant as drivers may get stuck out of the range of battery charge or exchange stations (generally referred to herein as battery service stations).

Usually, the remaining travelable distance of electric vehicles is approximated mainly based on the amount of energy stored in the vehicle's battery. However, the remaining travelable distance of an electric vehicle depends on a plurality of factors some of which are related to the vehicle and its battery, to the user driving the vehicle, and to weather and road conditions along the route traveled by the user towards a target destination.

In addition, the approximation of remaining travelable distance of an electric vehicle should also consider energy replenishing factors. For example, electric vehicles may convert rotary movement of the wheels (e.g. , through the motor and/or by using alternators), or solar energy (e.g. , using photovoltaic cells panels), into electrical energy which may be used for recharging the vehicles' batteries as the vehicles are being driven. The inventors of the present invention found that the remaining travelable distance of a vehicle powered by a battery may be calculated with improved accuracy based on calculation of a battery energy flow rate reflecting a rate of energy transferred between the battery of the vehicle and other components of the vehicle (e.g. , the vehicle's motor, alternators, and vehicle's electrical appliances) along a road section, or throughout the entire length of a planned route. The battery energy flow rate calculation may require analysis of the conditions of roads along the planned route to determine their slope / gradient, and/or any other resisting or propelling road conditions therealong (e.g. , back or front wind, road curvature, uphill and downhill slopes, etc.), which are used for calculating amounts of battery energy that will be consumed and/or recharged during the ride, along a road section, or throughout the entire length of a planned route.

For example, in possible embodiments the rate of battery energy flow includes rate of battery energy discharge, and/or rate of battery energy recharge, along at least one segment of road, or along the entire length, of the planned route. The battery energy flow rate may be then used to compute the amount of energy that will be consumed (i.e. , discharged from the battery of the vehicle) by the vehicle, or that will be recharged into the battery of the vehicle, over at least one segment of road, or along the entire length, of the planned route, which may be then used to calculate the remaining travelable distance with greater accuracy.

It was also found by the inventors of the present invention that the accuracy of the approximation of the remaining travelable distance may be further improved by introducing adjusting factors into the battery energy flow calculations. In some possible embodiments the adjusting factors reflect driving resisting and/or propelling road conditions. For example, data indicative of driving resisting and/or propelling road conditions may include real-time data comprising traffic and/or weather reports which are received and analyzed to evaluate a traversability factor indicative of the cross- ability of a road section in the planned route. The traffic reports may be indicative of traffic loads or jams in certain road segments of the planned route, and the weather reports may be indicative of resisting or propelling winds along certain road segments.

The inventors of the present invention further found that the accuracy of the approximation of the remaining travelable distance may be also improved by dividing the planned route into discrete road segments, and computing discrete energy flow rate for each of the discrete road segments separately. For example, the planned route may be divided into a plurality of road segments, each characterized by specific driving resisting and/or propelling road conditions. Accordingly, calculation of the remaining travelable distance may be carried out by calculating a residual battery energy content based on the discrete energy flow rate approximations computed for the respective segments.

For instance, the calculation may include successively calculating a residual battery energy content estimate for each road segment of the planned route, starting with the road segment on which the vehicle is at the (present) time, or that the vehicle is about to approach, and proceeding with the upstream road segments towards the target destination. In this successive computation, for each specific road segment of the planned route, a residual battery energy level (indicative of battery residual charge level after the specific road segment is driven) may be computed by reducing from the current energy content of the battery a sum of energy consumption estimations computed for preceding road segments (i.e., the road segments located downstream in the planned route relative to the specific road segment).

In this way, a discrete energy consumption estimate may be calculated for each road segment based on its respective discrete energy flow rate. The residual battery energy content may be computed for each specific road segment of the planned route by summating the discrete energy consumption estimates computed for preceding road segments (i.e. , located downstream relative to the specific road segment for which the residual battery energy content is being computed) and subtracting the summation result from the current energy content of the battery. Thus, the remaining travelable distance may be approximated based on division of a residual battery energy level computed for a specific road segment by the energy flow rate approximated for the specific road segment, or for one or more of the upstream road segments of the route i.e., road segments to be driven from the specific road segment towards the target destination.

The approximation of the remaining travelable distance may include adding to the division result the sum of the lengths of the road segments that are located downstream relative to the specific road segment. For example, the remaining travelable distance may be approximated based on division of a residual battery energy level computed for a specific road segment by some average of the energy flow rates approximated for all of the upstream (or both downstream and upstream) road segments of the route. The approximation of the remaining travelable distance may include adding to the division result the sum of the lengths of the road segments that are downstream relative to the specific road segment.

The calculation may include computing for each discrete road segment a respective remaining travelable distance approximation by dividing the residual battery energy content computed for a previous road segment by the respective discrete battery energy flow rate of the discrete road segment. If the remaining travelable distance approximation computed for a specific road segment is smaller than the length of the specific road segment, then it is determined that the amount of energy stored in the battery of the vehicle is not sufficient for the user driving the vehicle to complete the entire planned route (i.e. , the battery will go flat during the specific road segment).

If it is determined that the battery may go flat during a certain specific discrete road segment then the remaining travelable distance of the vehicle is indicated as the driving distance from the current location of the vehicle to the specific discrete road segment (e.g. , by summating the lengths of all road segments between the current location of the vehicle and the certain specific discrete road segment), or to a specific location therealong in which the battery is expected to go flat. The user may be thus advised to visit a battery service station along the planned route, to change driving style and/or road behavior (e.g. , drive the vehicle at lower speeds and acceleration/deceleration ranges, fully or partially close one or more windows, reduce or stop use of air-conditioning), and/or to change the planned route to include road segments which are less demanding in terms of energy consumption (having less drive- resistant conditions e.g. , having less, or no uphill slopes, having favorable weather conditions, and/or without traffic loads or jams, and suchlike).

In some embodiments the battery energy flow rate for each of the discrete road segments is computed based on external information that may have been recorded by the vehicle itself, or by a control center that manages and stores battery energy flow rates recorded and reported by a plurality of vehicles. Accordingly, the calculation of the remaining travelable distance may be carried out based on battery energy flow rates provided by a control center (or any communicable server system hosting a database of battery energy flow rates), which may utilize energy flow rates recorded for other vehicles and other users, and/or for the same vehicle and/or same user for which the remaining travelable distance is being calculated. In possible embodiments improved approximation of the remaining travelable distance of the electric vehicle is calculated using various data indications and based on the amount of energy stored in the battery of the vehicle (also referred to herein as the battery charge level). The calculation may utilize various data indications accumulated over time and/or determined in real-time during the ride. The data indications may include: electric vehicle data, such as, for example: vehicle weight and efficiency of vehicle's motor; user driving data reflecting driving patterns of the user driving the vehicle, such as, but not limited to, highway and urban road driving speeds, and acceleration/deceleration ranges; road conditions data, such as for example, uphill and downhill slopes and their lengths, traffic loads and/or jams, number of lanes, and roads' curvature (i.e. , relatively straight or tortuous); and/or data about the battery installed in the electric vehicles, such as, battery temperature, battery age and health, battery efficiency, and suchlike.

For example, in some embodiments the approximation of the remaining travelable distance is carried out in accordance with a planned driving route by analyzing the various collected data indications in conjunction with the planned route and calculating, based thereon, an estimation of energy consumption of the vehicle per unit of distance traveled along the planned route. For example, the collected data may include data about amounts of energy consumed by the motor of the vehicle when driven by the user in the past over road segments included in the planned route.

As described hereinabove, the data indicative of the amounts of energy consumed over certain road segments may be based on battery energy flow rates recorded by the vehicle for the same road segments and stored in the internal computer of the vehicle, and/or based on battery energy flow rates collected by the control center for these road segments from a plurality of other users and vehicles. Such data may be used to calculate a battery discharge rate for specific road segments to be driven along the planned route, and/or for its entire length, which may be used to estimate the remaining travelable distance of the vehicle based on the amount of the remaining energy stored in the battery of the vehicle.

In possible embodiments the consumption of energy from the battery of the vehicle over road segments is derived from data indicative of the electric current consumed by the vehicle during the ride along the road segment e.g. , using electric current measurement equipment. Alternatively, or additionally, the battery energy consumed by the vehicle along a specific road segment may be derived from data indicative of changes in the battery electric voltage level, which correlates to the amount of energy being consumed from it. A positioning system may be used to associate the measured electric current and/or voltage indications with specific road segments travelled by the vehicle.

The estimated remaining travelable distance of the vehicle may be modified, by calculating adjusting factors based on the accumulated data indications. For example, such adjusting factors may be calculated according to expected energy losses along the ride, computed based on the efficiency of the vehicle's motor, the efficiency of the vehicle's battery, the battery's age and/or the temperature of the battery. The remaining travelable distance approximation may be continuously or periodically modified by calculating adjusting factors upon receipt of updates received during the drive to the target destination and recalculating the remaining travelable distance approximation based on the newly calculated adjusting factors, the current location of the vehicle, and the current status of the battery (e.g. , charge level, temperature, etc.) of the vehicle.

Further adjusting factors may be calculated based on the user's driving data in general, and specifically based on driving data related to road sections included in the planned route. For example, if the user's driving data reflects that the user usually drives the vehicle at high speed and acceleration/deceleration ranges, then a wasteful user's energy consumption adjusting factor is computed and used to modify the calculated battery discharge rate.

Therefore, according to an aspect of the present application there is provided a method for calculating a remaining travelable distance of a vehicle powered by a battery, the method comprising the steps of: providing data related to a route of the vehicle (e.g. , road segments of the route, road data indicative of road conditions along the at least one segment of road of the route and/or topographic conditions of the at least one segment of road of the route); providing statistical data related to the route, and/or to other routes, and to a user of the vehicle, and/or other users of other vehicles (e.g. , driving patterns of the user, at least one route frequently driven by the user, and/or rate of battery energy flow along at least one segment of road in the at least one route frequently driven by the user); providing data about a measured charge level of the battery indicative of an amount of energy stored in the battery; utilizing the statistical data and determining a rate of battery energy flow for the battery indicative of a rate of discharge or recharge of battery energy along at least one segment of road in the route; and determining a remaining travelable distance based on the rate of battery energy flow and the battery charge level.

The provided data may comprise vehicle data indicative of conditions of the vehicle and/or of its battery (e.g. , vehicle weight, vehicle payload, windows state, amount of energy consumed by electric appliances of the vehicle, motor efficiency, battery efficiency, and/or battery temperature). The road data may include at least one of the following: weather conditions along at least one segment of road of the route; traffic conditions along at least one segment of road of the route; number of lanes in at least one segment of road of the route; road curvature of at least one segment of road of the route; and gradient (slope) of at least one segment of road of the route.

The method may further comprise identifying, based on the provided data, a plurality of discrete road segments in the route, and the calculating of the battery energy flow rate may comprise calculating for each of the plurality of discrete road segments a discrete rate of battery energy flow based at least in part on specific considerations associated therewith.

In possible embodiments the statistical data includes data on a plurality of other users. For example, the statistical data and the data indicative of the route may have at least one common feature selected from the following group: at least one segment of road of a frequently driven route, same time of day in which the route is driven, same day of week in which the route is driven, same day of month in which the route is driven, similar driving style, and similar road behavior.

Optionally, the statistical data is collected from a plurality of users and maintained in data storage (e.g. , data server) accessible by the vehicle. The method may further comprise associating data items in the statistical data to road segments of previously driven routes (driven by the user and/or by other users). Accordingly, provision of the statistical data related to the route may include providing data items based on road segments of the route of the vehicle.

The method may also comprise determining based on the retrieved data at least one adjusting factor indicative of energy losses or gains along at least one segment of road of the route, and the calculating of the rate of battery energy flow may be based at least in part on the at least one adjusting factor. In possible applications the determining of the at least one adjusting factor includes determining resisting or propelling conditions along at least one segment of road of the route based on the retrieved data, and the at least one adjusting factor may be based at least in part on said resisting or propelling conditions. Optionally, the determining of the resisting or propelling conditions includes determining automotive aerodynamic parameters of the vehicle along the at least one segment of road. For example, the at least one adjusting factor may be based at least in part on said automotive aerodynamic parameters.

In some applications the specific considerations are derived from at least one of the following group: the topographic conditions, the road data, the weather conditions, the traffic conditions, the driving patterns of the user, and the automotive aerodynamic parameters of the vehicle. Optionally, the identifying of the plurality of discrete road segments is based at least in part on one of the following: the driving patterns of the user; the rate of battery energy flow along at least one segment of road of route; the road data; the vehicle data; and the topographic conditions along the planned route.

The method may further comprise identifying in the plurality of discrete road segments two or more intersecting discrete road segments and identifying at least one discrete road segment mutual to the two or more discrete road segments according to their intersection. Optionally, the calculating of the battery energy flow rate may comprise calculating for the at least one mutual discrete road segment a discrete rate of battery energy flow based at least in part on specific considerations associated with the two or more intersecting discrete road segments.

In possible applications, the calculating of the remaining travelable distance comprises: calculating for each discrete road segment an amount of expected battery energy discharge along a portion of the route between the first road segment of the route and the specific discrete road segment based on the calculated battery energy flow rates of the specific road segment and of discrete road segments located downstream to the specific discrete road segment, and whenever determining based on the expected battery energy discharge calculated for a specific discrete road segment that the charge level of the battery is not sufficient to complete the route, calculating the remaining travelable distance based on lengths of the discrete road segments located downstream to the specific discrete road segment. Optionally, the remaining travelable distance is calculated based at least in part on calculated residual battery energy indicative of an amount of energy expected to remain in the battery when the specific discrete road segment is reached. Alternatively, if it is determined based on the expected battery energy discharge calculated for all discrete road segment that the charge level of the battery is sufficient to complete the route, the remaining travelable distance is calculated based on a residual battery energy computed for the last discrete road segment of the route. Optionally, the remaining travelable distance is calculated based on a weighted average of energy flow rates computed for two or more of the discrete road segments.

Advantageously, the method may further comprise adding to the route one or more battery service stations whenever it is determined that the charge level of the battery is not sufficient to complete the route.

The method may further comprise determining corrective measures that the user of the vehicle may perform in order to increase the chances of reaching a target destination of the route, whenever the value of calculated residual battery energy content is negative.

In a variant, determining the route may comprise determining a target destination based on data received from the user or based on the at least one frequently driven route, and on at least one of the following indications: current location of the vehicle, time of day the at least one frequently driven route is being driven, and day of the month the at least one frequently driven route is being driven.

In possible embodiments the method may comprise displaying in a display device provided in the vehicle data related to the route, the displayed data may comprise at least one of the following: distance from current location of the vehicle to the target destination; the calculated remaining travelable distance; data indicative of a portion of the battery energy expected to be contained in the battery after reaching the target destination; and the route, and planned stops in battery service stations included in the route, if any.

In another aspect the present application is directed to a system for use in monitoring a traveling vehicle powered by a battery. The system may comprise a processing utility connectable to a memory utility for receiving data comprising statistical data related to a plurality of routes driven by a plurality of users or that is related to the users (e.g. , driving patterns of a user of the vehicle, at least one route frequently driven by the user, and/or rate of battery energy flow along at least one segment of road in the at least one frequently driven routes). In some applications the processing utility comprises a battery energy flow estimator configured and operable to receive and process a planned route and data comprising statistical data of at least one of the plurality of routes or of at least one of the users, and calculate based on the data a rate of battery energy flow for the battery along at least a segment of road of the planned route. The system may comprise a distance approximating unit configured and operable to receive data indicative of an amount of energy stored in the battery and data indicative of the rate of battery energy flow, and calculate a remaining travelable distance for the vehicle based thereon.

In some implementations the battery energy flow estimator is configured and operable to identify, based on the received data, a plurality of discrete road segments in the planned route, and to calculate a respective discrete rate of battery energy flow for each of the plurality of discrete road segments based at least in part on specific considerations associated therewith and derived from the data received.

The received data may also comprise at least one of: road data indicative of road conditions along the at least one road segment (e.g. , weather conditions along at least one segment of road of the planned route; traffic conditions along at least one segment of road of the planned route; number of lanes along at least one segment of road of the planned route; road curvature of at least one segment of road of the planned route; and/or gradient along at least one segment of road of the planned route); vehicle data indicative of conditions of the vehicle or of its battery (e.g. , vehicle weight, vehicle payload, windows state, rate of energy consumed by electric appliances of the vehicle, motor efficiency, battery efficiency, and/or battery temperature); topographic conditions of at least one road segment of the planned route.

In some implementations the battery energy flow estimator may be configured and operable to determine based on the received data at least one adjusting factor indicative of energy losses or gains along at least one road segment of the planned route. The battery energy flow estimator may be configured and operable to calculate the rate of battery energy flow based at least in part on the at least one adjusting factor. Optionally, the battery energy flow estimator is configured and operable to determine resisting or propelling conditions along the at least one road segment of the planned route based on the retrieved data. The at least one adjusting factor may be determined based at least in part on the resisting or propelling conditions. Additionally or alternatively, the battery energy flow estimator may be configured and operable to determine automotive aerodynamic parameters of the vehicle along at least one road segment of the planned route. Optionally, the resisting or propelling conditions are determined based at least in part on the automotive aerodynamic parameters.

In some applications the specific considerations are derived from at least one of the following: the topographic conditions, the road data, the weather conditions, the traffic conditions, the driving patterns of the user, and the automotive aerodynamic parameters of the vehicle.

In possible implementations, the plurality of discrete road segments are identified based at least in part on the driving patterns of the user; the rate of battery energy flow along at least one of the segments of road in the at least one frequently driven routes; the road data; the vehicle data; and/or the topographic conditions.

In a variant, the battery energy flow estimator is configured and operable to identify in the plurality of discrete road segments two or more intersecting discrete road segments and to identify at least one discrete road segment mutual to the two or more discrete road segments according to the intersection. The battery energy flow estimator may calculate a battery energy flow rate for the at least one mutual discrete road segment based at least in part on specific considerations associated with the two or more intersecting discrete road segments.

In possible applications the distance approximating unit is configured and operable to: calculate for each discrete road segment an amount of expected battery energy discharged along a portion of the route between the first road segment of the route and the specific discrete road segment based on calculated battery energy flow rates of the specific road segment and of discrete road segments located downstream to the specific discrete road segment; determine, based on the expected amount of battery energy discharge calculated for a specific discrete road segment, if the charge level of the battery is sufficient to complete the route; and if it is determined that the battery charge level is not sufficient, calculate a remaining travelable distance based on lengths of the discrete road segments located downstream to the specific discrete road segment.

The distance approximating unit may be configured to compute residual battery energy indicative of an amount of energy expected to remain in the battery when the specific discrete road segment is reached, and to calculate the remaining travelable distance based at least in part on said residual battery energy. Whenever it is determined that the charge level of the battery is sufficient to complete the route, the distance approximating unit may compute a remaining travelable distance based on a residual battery energy computed for the last discrete road segment of the route. Additionally or alternatively, the distance approximating unit may be configured to calculate a weighted average of energy flow rates computed for two or more of the discrete road segments, and to calculate the remaining travelable distance based at least in part on the weighted average.

Advantageously, the processing utility may be configured to add to the route one or more battery service stations whenever it is determined that the charge level of the battery is not sufficient to complete the route.

Optionally, the distance approximating unit is configured and operable to determine corrective measures that the user of the vehicle may perform in order to increase the chances of reaching a target destination of the planned route, whenever determining that the energy in battery is not sufficient to complete the route.

The battery energy flow estimator may be configured and operable to determine the planned route by determining a target destination based on data received from the user of the vehicle or based on the statistical data, and on: the current location of the vehicle, the time of day the frequently driven route is being driven, and/or the day of the month the frequently driven route is being driven.

The system may further comprise a charge level measuring unit configured and operable to measure the amount of energy stored in the battery.

In yet another aspect, the present application is directed to a method for presenting data related to a route of a vehicle. The method may include receiving data indicative of battery energy flow along the route or along discrete road segments thereof; computing based on the received data an estimation of an amount of energy to be consumed from a battery of the vehicle during a ride along the route; receiving data indicative of an amount of energy contained in the battery; computing data indicative of a portion of the battery energy expected to be contained in the battery once the ride along the route is completed; and outputting the computed data to a display utility, a memory utility, or a remote computer system.

Optionally, the data indicative of the portion of the battery energy expected to be contained in the battery once the ride along the route is completed is provided in the form of a percentage relative to a battery energy capacity (e.g. , maximal energy content of the battery), or in the form of distance units indicating a remaining travelable distance. BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it may be carried out in practice, embodiments will be now described, by way of non-limiting example only, with reference to the accompanying drawings, in which same reference numerals are used to identify elements or acts with the same or similar functionality, and in which:

Fig. 1 is a block diagram exemplifying a system for approximating a remaining travelable distance of a vehicle according to some possible embodiments;

Fig. 2A and Fig. 2B are flowcharts exemplifying a process for calculating a remaining travelable distance approximation according to some possible embodiments;

Fig. 3 exemplifies a technique for approximating possible travelable distance of a vehicle;

Fig. 4 is a flowchart exemplifying a process for approximating possible travelable distance of a vehicle according to some possible embodiments utilizing a centralized control system;

Fig. 5 is a flowchart exemplifying calculation of a remaining travelable distance approximation for a segmented planned route according to a possible embodiment;

Fig. 6 is a flowchart exemplifying a process of a real-time approximation and update of a remaining travelable distance during a ride of a vehicle according to some possible embodiments;

Fig. 7 demonstrates possible presentation of route data and travelable distance approximations with a road map; and

Figs. 8A and 8B are flowcharts exemplifying a possible method for real time monitoring of vehicle' energy consumption and adding one or more battery service stations to the route whenever needed. DETAILED DESCRIPTION OF EMBODIMENTS

The present disclosure provides a reliable and improved approximation of a remaining travelable distance of a vehicle utilizing a battery as its main power source, based on a plurality of data indications, including profile data, statistical data and real time data obtained from the vehicle and/or from a centralized control system before or during the ride. In exemplary embodiments of the present intention the profile data includes, inter alia: vehicle's profile data, such as, but not limited to, motor efficiency and vehicle's weight; and battery profile data, such as, but not limited to, battery capacity and battery efficiency, road data, such as, but not limited to, gradient of uphill and downhill road segments and their lengths, road curvature, and number of lanes. The statistical data may include battery energy discharge, and/or recharge, rates along driven road sections and data reflecting driving patterns of the user of the vehicle, for instance, road behavior of the user of the vehicle including driving speeds, accelerations, and decelerations along one or more road segments of the planned route. The real-time data may include, but is not limited to, battery charge level and temperature, traffic load, traffic jams, and weather conditions.

Some of the plurality of indications may be collected from a memory of the specific vehicle for which the remaining travelable distance is being calculated (e.g. , using a drive recorder) or based on aggregation of information from numerous vehicles managed by a control center capable of communicating the vehicles and querying them for such driving information. In some embodiments the plurality of data indications are further used to refine the approximation of the remaining travelable distance of the vehicle. The plurality of data indications may be also used to provide additional services to the user of the vehicle, such as, but not limited to, locations of nearby restaurants or shops and locations of pit stops required for recharging or replacing the battery of the vehicle.

For example, in possible embodiments a driving route is planned or determined for a specific vehicle according to the target destination of the user of the vehicle and possibly also according to availability of battery service stations towards the target destination. After determining the driving route (also referred to herein as planned route) the statistical, profile and/or real-time data are retrieved and analyzed, where the statistical data is at least partially based on the planned route. An expected battery discharge rate is then computed based on the retrieved data, which is then used together with the battery energy charge level (i.e. , the amount of energy stored in the battery) to calculate the remaining travelable distance approximation.

A battery energy recharge rate may be calculated if the planned route includes conditions for generating electrical energy by the vehicle therealong. For example, when driving downhill road segments, rotary movement of the wheels can be converted by the motor (or by an alternator) of the vehicle into electric energy usable for recharging the battery of the vehicle. As another example, electrical energy may be also generated using a solar recharging system (e.g. , using photovoltaic cells), which may be installed in the vehicle, if the weather conditions and the time of the day permit recharging the battery pack during the ride. The calculated energy recharge rate may be reduced from the calculated energy discharge rate to refine the remaining travelable distance approximation.

In some embodiments the collected statistical and profile data are further used to calculate various adjusting factors which may be combined in the calculation of the battery discharge rate. For example, if the analysis of the driving data of the user of the vehicle reveals wasteful energy driving behavior (e.g. , high speeds and/or accelerations/decelerations), a respective adjusting factor may be computed for adjusting the calculated battery discharge rate along certain road segments of the planned route, and/or for the entire route. In a similar fashion, adjusting factors may be computed based on an efficiency factor of the vehicle or of the battery. For example, if the data analysis reveals that the motor of the vehicle, or the battery pack used in the vehicle experience substantial energy loses, corresponding adjusting factors are computed and then combined in the calculation of the battery energy discharge rate.

In possible embodiments the remaining travelable distance is periodically or continuously adjusted during the ride based on real-time data updates retrieved from the vehicle and/or from a control system (e.g. , control center such as a service provider, traffic control agency, or battery service station). For example, the retrieved real-time data updates may indicate presence of resistive, or propelling, road conditions (e.g. , fog, traffic loads and/or jams, windy/stormy weather), substantial changes in the temperature of the battery or of the motor of the vehicle requiring respective adjusting factors to be introduced due to reduction of battery and/or motor efficiency, substantial changes in the vehicle payload (e.g. , due to the upload or discharge of passengers or luggage) or in the automotive aerodynamics of the vehicle (e.g. , due to open/closed windows, substantial changes in rolling resistance due to ambient temperature or humidity) and/or in the electrical consumption of the vehicle (e.g. , due to use of air-conditioning, use of high beam headlights, and suchlike), each of which may require calculation of a respective adjusting factor to be used in the calculation of the battery discharge rate approximation.

Fig. 1 is a block diagram demonstrating a possible system 10 for approximating remaining travelable distance of a vehicle powered by a battery according to some possible embodiments. In this example the system 10 comprises a computer system 15, one or more vehicles 13a, 13b, 13c,... (collectively referred to herein as vehicles 13), a profile and statistical data storage device 11 for storing and reporting profile data 12 related to at least the vehicles 13 and/or the users' of said vehicles, and a road data storage device 18 (designated as traffic control in Fig. 1) for storing and reporting road data 19 related to at least the driving conditions (e.g. , road conditions, traffic loads/jams, and suchlike) in the driven roads. The computer system 15 is communicatively coupled to the storage devices 11 and 18 via a data network 14 (e.g. , the Internet), or over a direct wired (e.g. , landline telephony, cables, and suchlike), optical (e.g. , optic fibers) or wireless (e.g. , IR, or RF, such as, satellite communication, WiFi, Bluetooth, cellular communication, and suchlike) communication link (designated by dashed arrowed lines).

The computer system 15 is also communicatively linked to the vehicles 13, preferably over a wireless communication link, such as exemplified hereinabove. For example, vehicles 13 may be configured to establish wireless communication with the data network 14 and therethrough to communicate data with the computer system 15, using any suitable conventional technique known in the art (e.g. , using cellular communication).

The profile and statistical data storage device 11 is configured to store and maintain a plurality of data records 12a, 12b, 12c, ... each comprising data related to at least the respective users of the vehicles 13. For example, a data record 12a may comprise data indicative of driving patterns (12al, e.g. , driving style, road behavior, frequently driven routes and their day times, and such like) of a user of a respective vehicle 13a. The data profile 12a may also include information about the vehicle 13a (12a2, e.g. , vehicle weight, motor power and motor efficiency) and/or about the battery pack used in the vehicle 13a (12a3, e.g. , maximal energy capacity of the battery, battery health and age, battery efficiency).

In some possible embodiments the profile and statistical data storage device 11 is maintained and managed by a service provider (36 in Fig. 3) that provides battery exchange and recharge services to the vehicles 13 by a plurality of battery service stations (BSS) 17. Alternatively or additionally, the profile and statistical data storage device 11, or portions thereof, may be stored and maintained in a memory (35m in Fig. 3) of the vehicles 13. As demonstrated in Fig. 1, the BSS 17 is communicatively coupled to the computer system 15 over the data network 14, or directly (indicated by a dashed arrowed line), for example, via land line telephony, cables infrastructures or fiber optics communication.

The data records relating to the user and to the vehicle 13a may be collected periodically or continuously by the internal computer of each of the vehicles 13, for example, by utilizing an in-vehicle data recorder (IVDR). Accordingly, in some embodiments the internal computer (35 in Fig. 3) of the vehicle 13a is configured to collect in real time data pertaining to the user (13al), to the battery pack (13a2), and/or the vehicle (13a3), and send from time to time such real-time data updates to the profile data storage device 11 and/or to the computer system 15. Accordingly, the internal computer of each vehicle 13 may be configured to collect and store such profile and statistical data, 13al 13a2 13a3..., in a memory (35m) of the vehicle's computer, and to transfer some, or all, of the collected data to the storage device 11 or to the computer system 15 (designated by dashed-broken arrowed lines 3a).

The road data storage device 18 is configured to collect and store real-time temporal data and data considered as unchanging (that usually remains constant) related to the roads used by the users of the vehicles 13, which may be used by the system 10 to derive various inclusions about the energy consumption of vehicles traveling along these roads. For example, road data storage device 18 may include unchanging data about the conditions of the roads (19a, e.g., number of uphill and downhill road segments and their lengths and gradient (slope), number of traffic lanes, road curvature), and contemporary road data about the weather conditions in the roads areas (19b, e.g., dry, rainy, foggy or stormy weather conditions, winds directions and strengths, road is dry or wet, ambient temperature, and suchlike), and any possible obstacles therealong (19c, e.g., car collisions, bumpers, traffic lights, traffic loads or jams).

The road data storage device 18 may be part of a traffic control agency utilizing sensing devices (not shown e.g. , video cameras, car counters, weather sensors, and such like), satellite images weather reports, and/or topographic maps, and suchlike, to collect information about the conditions of the roads. In possible embodiments the data required for calculating the travelable distance approximation is collected from the road data storage device 18 for each vehicle by the control center. The collected data is then transmitted by the control center to each vehicle. The control center may process the collected data and assist in calculating the travelable distance approximation for each vehicle. Alternatively, the control center may process the collected data, calculate the travelable distance approximation for each vehicle, and transfer the calculated result to the vehicles.

The profile and statistical data storage and the road data storage devices, 11 and 18, may be implemented employing any suitable memory devices (e.g. , RAM, FLASH, magnetic disks, optic disks, and such like). Each of the data storage devices 11 and 18 may be part of a data server (e.g. , RAID server) connected to the data network 14, for example, as known to those versed in the art.

The computer system 15 is configured to retrieve, or plan, a driving route (also referred to herein as planned route) for at least one vehicle 13a, and to collect the profile and statistical data 12 relevant to the vehicle 13a and/or to the user of the vehicle, and/or the road data 19 based on the planned route. The computer system 15 analyzes the collected data and calculates, based thereon, the remaining travelable distance approximation for the vehicle 13a. The computer system 15 utilizes a processor utility 16 and a memory utility 15m configured to collect and analyze the profile and statistical data 12 and the road data 19, and to calculate various estimations about the energy recharge and discharge rates along road segments to be traveled by the vehicle, and/or about the traversability of these road segments. The various computed estimations are then used by the computer system 15 to calculate the remaining travelable distance approximation for the vehicle 13a.

Computer system 15 may be implemented using any suitable combination of processors (CPUs) or controllers (MCUs), and memory devices (e.g., RAM, ROM, FLASH, magnetic/optic disks). In some possible embodiments the computer system 15 is part of a service provider system (e.g. , 36 in Fig. 3) configured to provide various services to the vehicles 13 and/or to their users. Alternatively or additionally, computer system 15 may be implemented in form, or as part, of an internal computer (e.g. , 35 in Fig. 3) of the vehicle 13a.

Fig. 2A is a flowchart demonstrating a process 30 for approximating a remaining travelable distance of a vehicle 13a according to some embodiments, as may be performed by the computer system 15. The process 30 may be initiated in determining a target destination (20) and/or route (21) to be driven by the user of the vehicle 13a. The determination of target destination and driving route may be based on direct input from the user via the user interface of the control unit of the vehicle (35 in Fig. 3). For example, the user may indicate the target destination in order to receive driving directions from a positioning system (e.g. , 35g in Fig. 3) and/or in order to approximate a remaining travelable distance and, based thereon, receive recommendations for BSS 17 stops along the planned route). In cases where a destination is not provided by the user, the target destination and the route data may be derived based on historical data of the user indicted by the previously driven routes data. The historical data may be locally stored in memory (35m) of the vehicle's control unit (35), but it may, additionally or alternatively, be also stored and retrieved from a control center (e.g. , of service provider 36), and/or from storage devices (11) communicatively linked thereto.

For example, the target destination and route data may be determined by querying the user for the target destination and/or route via the internal computer 35 of the vehicle 13a, and/or by analyzing the profile data of the user (12al) extracted by the system (in step 22). More particularly, the computer system 15 may use data relating to the user's frequently driven routes and their times as provided in the user profile data (12al), and determine the user's target destination if the current time and location of the vehicle match with the frequently driven routes and their times data. For instance, if the user of the vehicle 13a drives during morning hours of regular working days between home and work locations and the time and location of the vehicle comply with this home-work route and its usual day time range data, the system may determine with high level of certainty that the user is driving the regular route between the home and work locations. The target destination determined by the system may be presented to the user of the vehicle, who may be requested to confirm or decline the determined destination.

Possible target destination selection criteria may include selection of the most common destination that the user is targeting when located at the specific location as reported by the positioning system (35g). In case the user profile data records do not include route information relating to the road(s) currently driven by the user, profile data records of other users may be used to determine the most common destination driven by other users from the current location of the vehicle, for example, based on time of day and/or day of week data. The system may be further configured to track the actual progress of the vehicle 13a along the planned route based on position data received from a positioning system (35g) installed in the vehicle, and update in realtime the vehicle location data and the remaining travelable distance approximation, accordingly. The profile and statistical data 12, and possibly also the road data 19, relevant to the planned route are then extracted from their respective storage devices and analyzed (22) by the computer system 15. Additional real-time data (e.g. , 13al, 13a2, 13a3,...) may be collected directly from the vehicle 13a. Based on the collected data a battery energy flow rate is then calculated (23). For example, based on the collected data the computer system 15 may calculate a rate of energy discharge from the battery of the vehicle 13a along the planned route, or along discrete segments thereof. For example, the profile and statistical data (22) may include statistical road data comprising various battery discharge rates recorded by the system 10 along road segments in the planned route, for different users and vehicles, or for the same user and/or vehicle 13a for which the remaining travelable distance approximation is currently being computed.

The computer system 15 may be configured to use in the calculation (23) the battery energy discharge rates recorded for the user and/or for the vehicle 13a of the user, along the planned route or along discrete road segments thereof. Preferably battery energy discharge rates recorded for the same specific user and the vehicle 13a of the user along the planned route (21) or along discrete road segments thereof are used. However, if the statistical road data does not include battery discharge rates related to the user and/or its vehicle 13a, then the system 10 may use battery discharge rates recorded for other users driving a vehicle having similar characteristics (e.g. , of the same type, model, and/or make) along relevant road segments. Alternatively, the system 10 may calculate an averaged battery energy discharge rate based on various battery energy discharge rates recorded for a plurality of users using vehicles 13 having characteristics that are similar to (or different than) those of the vehicle 13a for which the remaining travelable distance approximation is being computed.

If there is no profile or statistical data related to the user in the statistical data storage device 11, then profile or statistical data recorded for a number of, or all, other users for the specific planned route or for road segments thereof, or for a route or road segments having similar characteristics (e.g. , length and driving resisting and/or propelling road conditions), is used. On the other hand, if the system does not find suitable data, in the statistical data storage device 11 or in the road data storage device 18, relevant to the planned route, and/or to one or more discrete road segments thereof, data relating to similar routes, and/or to the respective discrete road segments thereof (e.g., having similar topographic or weather conditions), may be used instead in the remaining travelable distance approximation process.

After computing the battery energy flow rate (23) the charge level of the battery (13a2 i.e., the amount of energy currently stored in the battery) of vehicle 13a may be fetched (26) for computation of the remaining travelable distance approximation (27) for the vehicle 13a, which may be then outputted (28), for example, to a display device, to a storage or memory device (e.g. , 11/18 or 15m), to service provider (e.g. , 36) and/or to BSS 17. In certain embodiments the remaining travelable distance approximation may end in the outputting of the remaining travelable distance approximation (28).

In possible embodiments the calculation of the remaining travelable distance approximation may include various adjustments, and in such possible embodiments after the battery energy flow rate is calculated (23) the process proceeds (designated by a dashed arrowed lines) to a step of calculating various adjusting factors (24) based on the retrieved profile, statistical, and/or road data. The various adjusting factors (24) are then used for modifying the computed battery energy flow rate (25). Thereafter, the battery charge level (13a2) is obtained (26) and used together with the modified battery energy flow rate (25) for calculating the remaining travelable distance approximation (27). In such possible embodiments the remaining travelable distance approximation may end in this stage as the calculated remaining travelable distance approximation is being outputted (28).

For example, the adjusting factors (24) may include calculation of a traversability factor providing a measure of cross-ability of road segments of the planned route in view of possible obstacles and/or indications of various driving resisting and/or propelling road conditions provided in the road data 19.

In other possible embodiments the remaining travelable distance approximation may be updated periodically or continuously during the ride along the planned route. In such possible embodiments after each output of a remaining travelable distance approximation (28) the process proceeds (designated by dotted arrowed lines) upon retrieval of updates of real-time data (29). The real-time data updates (29) may be obtained from profile and statistical data storage device 11, from road data storage device 18, from the internal status reporting modules (35d, in Fig. 3) of the vehicle 13a, and/or from BSS 17 or an external server (not shown) to which the computer system 15 (or vehicle internal computer) may be communicatively linked. For example, the real- time data updates may comprise reports about traffic loads/jams and/or weather reports, along road segments in the planned route, changes in automotive aerodynamics (e.g., one or more windows been opened, changes in the vehicle drag coefficient) and/or battery temperature of the vehicle 13a.

These real-time data updates (29) entail computation of various adjusting factors

(24) which are used for calculating a modified energy discharge rate (25) for the vehicle 13a. In this case, however, the calculation of the modified battery energy flow rate is carried out according to the current location of the vehicle 13a along the residual road segments of the planned route i.e. , using data pertaining only to not yet driven road segments of the planned route. The modified battery energy flow rate (25) is then used for calculating and outputting the remaining travelable distance approximation (steps 26-28), as described hereinabove. This loop (steps 23-29) may be performed periodically or continuously along the entire ride in order to update the user and/or the system 10 in real-time about any changes in the previously computed remaining travelable distance approximations.

The computer system 15 may further calculate estimates of battery recharging rates during the ride of the vehicle along the planned route. These estimates are particularly useful if there are downhill roads along the route of the vehicle 13, during which the battery of the vehicle may be recharged with energy, or if the vehicle 13a includes a solar recharging system, for example. With reference to Fig. 2B, as seen, the energy flow rate calculation (step 23) may include calculation of a battery discharge rate (23d) and battery recharge rate (23r) along the entire planned route and/or along discrete road segments thereof. The energy flow rate (23) may be calculated by summating (23s) the battery discharge (23d) and recharge (23r) rates computed for each discrete road segment, and/or for the entire planned route.

The computed energy flow rate (23) combining battery discharging and recharging rates may be then used to calculate the remaining travelable distance approximation as described hereinabove (e.g., by performing steps 23 and 26 to 28 in Fig. 2A), and may be similarly used in embodiments employing adjusting factors in the remaining travelable distance approximation (e.g., by performing steps 23 to 28 in Fig. 2A), and/or in embodiments in which the remaining travelable distance is continuously or periodically updated along the ride based on real-time data updates (e.g., by performing steps 23 to 29 in Fig. 2A in repetitions). The remaining travelable distance approximation may be further refined by considering possible fluctuations in the battery energy flow rate approximation associated with the time of day, day of week and weather conditions. For example, if the statistical data is collected for the specific route at different times of day, and there is significant variability in the energy flow rate data across the different time of day events recorded in the system, then the battery energy flow rate estimation will use data that has been collected for a time of day that is similar to current time of day.

An alternative approach that may be used in possible embodiments, instead, or in cases where no relevant historical data for the specific route is available, is to predict the battery energy flow rate based on classification of the road type and the historical driving style per road type for the specific driver (i.e. , to evaluate the discharge rate based on the road conditions data and the driving patterns of the user). For example, if the user usually drives at 90 km/h on 10% uphill and aggressively presses the acceleration, then it is most probable that the user will maintain this driving behavior with similar characteristics on other roads. Thus, previously recorded driving behavior and style of a user related to other road segments may be used to evaluate the energy discharge rate for a road segment about which there is no historical data, based on similarities of the road segment to previously driven road segments.

Fig. 3 exemplifies various components of vehicle 13a according to possible embodiments. In this example vehicle 13a comprises a control unit 35 including a processor utility 35p, a memory utility 35m (e.g. , ROM, RAM, FLASH, and/or magnetic/optic disks), a user interface 35u operable to display information to the user (e.g. , on a LCD or video display device) and receive user inputs (e.g. , via keyboard/keypad or touch screen), and a communication module 35c (e.g. , wireless LAN, Cellular, Bluetooth, or suchlike) operable to communicate data with the computer system 15 and/or the data network 14.

The vehicle 13a may also include various status reporting modules 35d operable to measure various parameters and conditions of the vehicle and provide corresponding indicative data based thereon to the control unit 35, for example, over a data bus (not shown) using a bus interface 35b. For instance, the status reporting modules 35d may include a battery status module 35dl operable to measure and report the current charge level (E_c) of the vehicle's battery 35t (the amount of energy E_c stored in the battery e.g. , based on battery voltage measurements) and the current temperature of the battery 35t. The status reporting modules 35d may include a payload sensing module 35d2 configured and operable to determine the number of passengers in the vehicle e.g. , by using sensors installed in the vehicle's seats, and/or sensors used to measure the vehicle's weight e.g. , using pressure or tension sensors installed in the suspension system of the vehicle. Additionally, a window state reporting module 35d3 may be also included for sensing and reporting the state of the vehicle's windows, and/or an energy recharge/discharge rate measuring module 35d4 configured and operable to measure energy consumption of vehicle's motor and possibly of other systems of the vehicle other than its motor {e.g., light system, air-conditioning, etc.).

The vehicle 13a may further include a positioning system 35g (global positioning system such as GPS, or any suitable wireless triangulation positioning system e.g., satellite, cellular network, WiFi AP tracking, or suchlike), applicable for determining the current position of the vehicle 13a and reporting the same to the control unit 35. Positioning system 35g may be implemented as an integral part of the control unit 35 as demonstrated in Fig. 3, as part of the status reporting modules 35d, or as a separate unit. Data from the status reporting modules 35d may be continuously or periodically communicated to the control unit 35 over the internal bus interface 35b of the vehicle for updating it about the amount of energy stored in the battery pack 35t of the vehicle 13a (13a2), about the temperature of the battery 35t of the vehicle, about the rate of energy recharge and discharge, and also for determining whether the vehicle is in a regenerative mode {i.e. , mode of slowing the vehicle while converting kinetic energy into electrical energy).

In possible embodiments the control unit 35 is utilized in the vehicle 13a to collect and record information about driving routes and the driving patterns of the user of vehicle 13a. For example, the control unit 35 may be configured to record in memory 35m driving speeds, accelerations/decelerations, driven routes and time of day during which these routes are driven by the user, and battery energy discharge/recharge rates for the recorded driven routes.

Fig. 4 is a flowchart schematically illustrating possible embodiments wherein a centralized control center {e.g. , of service provider 36) is utilized in the calculation of the remaining travelable distance approximation. In this example the target destination (step 42) and/or the planned route (43) are determined by the control unit 35 of the vehicle 13a, for example, by querying the user via the user interface 35u. The planned route is sent through the communication module 35c to the service provider 36 (step 48), which analyzes the planned route and retrieves relevant statistical and/or profile data (step 49), for example from a storage device 11 and/or 18, and transfers the retrieved data to the control unit 35 of the vehicle 13a.

The control unit 35 then analyzes the retrieved data and calculates (step 44) the battery energy flow rate, which is then used by the control unit 35 to calculate the remaining travelable distance approximation (step 45) that may be outputted to a user display provided in the user interface 35u, to the memory 35m, and/or to service provider through the communication module 35c. The control unit may collect during the ride driving and status data (step 40) which may be further used in the calculation of the battery energy flow rate (in step 44) and/or in the calculation of the remaining travelable distance approximation (in step 45). The collected driving and status data may be transferred to the service provider 36 (steps 41 and 47) for recordal therein, and/or in the profile data records stored in storage device 11. It is noted that the approximation of travelable distance (step 45) may be carried out using any of the methods described hereinabove and hereinbelow.

The status reporting modules 35d may further comprise a driving speed reporting module (not shown) operable for measuring and reporting driving speeds of the vehicle (13al) to the control unit 35. The driving speed reporting may be further configured to compute and report acceleration and deceleration ranges, which may be alternatively or additionally computed by the control unit 35. The control unit 35 and/or the status reporting modules 35d may further include an energy recharge/discharge rate measuring module (35d4) operable for measuring and reporting to the control unit 35 the energy recharge and discharge rates (13a2).

For example, the energy recharge/discharge rate measuring module 35d4 may be configured to continuously or periodically measure the electric current supplied by the battery 35t of the vehicle, and thereby measure a total amount of electric current consumed by the electric devices operating in the vehicle. Alternatively or additionally, the energy recharge/discharge rate measuring module 35d4 may be configured to continuously, or periodically, measure the electrical current consumed by the motor of the vehicle. In possible embodiments the voltage of the battery is also continuously, or periodically, measured by the energy recharge/discharge rate measuring module 35d4, and used to calculate rate of battery energy flow. In possible embodiments the estimation of the remaining travelable distance of the vehicle 13a employ information about allowed driving speeds on roads included in the route of the vehicle, as may be obtained from road data storage device 18 or from a topographic information systems and mapping services.

The control unit 35 and/or the status reporting modules 35d may be configured to collect information about the driving habits and road behavior (e.g. , expressed in acceleration/deceleration patterns and driving speeds in relation to road conditions), and data indicative of routes driven by the user of the vehicle over time. The data indicative of the routes may include target destination data, and may further include data indicative of the time of day and the date (day of week, month, holidays) on which the recorded routes have been driven. The user driving data may further comprise recorded rates of battery energy discharge, and/or rates of battery energy recharge, associated with each type of driving style, driving speeds, and/or accelerations/deceleration recorded for the user. The user driving data preferably also includes battery discharge rates for each of the driving routes, or of discrete road segments thereof, recorded for the user.

In possible embodiments the system may provide an option for the user to request approximation of remaining travelable distance for a plurality of possible target destinations simultaneously. The destination determining (step 20 in Fig. 2A) may therefore include determining multiple target destinations, which will be followed by determination of a corresponding plurality of driving routes (in step 21 in Fig. 2A) and calculation of corresponding remaining travelable distance approximations for each.

With reference to Fig. 3, in possible embodiments the entire length (S) of the planned route 33 is segmented into a plurality of road segments ( _/, , S3, .. .,S„; e.g. , S=Si+S₂+S3+.. .+S„) based on, for example, resistive or propelling road conditions indicated in the retrieved road data 19. For example, the planned route may be segmented according to road conditions indications, such as, but not limited to, multilane road segments (e.g. , fast highways), heavily traffic loaded road segments, jammed road segments, tortuous and/or uphill or downhill road segments. Based on the road data 19 obtained, the computer system 15 may calculate for each of the road segments 5,· (where in an integer, \<=i<=n) a respective rate of battery energy flow (23) and adjusting factors (24). The system may classify road segments of the planned route based on topographic information included in the road data and/or based on driving patterns of the user e.g. , driving speeds or segmented per time of day, as indicated in the retrieved road data and the statistical and profile data. The system may then use its recorded battery energy flow rates {e.g. , battery discharge rate) typical for these conditions for the specific user, and then calculate the overall expected remaining travelable distance approximation. With reference to Fig. 1, in possible embodiments computer system 15 comprises an energy discharge rate estimator module 15d configured to calculate energy discharge rates estimates for the battery of the vehicle 13a along the planned route, and/or along discrete road segments thereof (dR,^ e.g. , expressed as a negative value). An energy recharge estimator 15c is used in these embodiments in computer system 15 to calculate an estimation of energy recharge rate (dRi ⁺⁾) along the planned route, and/or along discrete road segments thereof. A summation module 15u may be used in the computer system 15 to calculate an energy flow rate (dRi) based on the calculated energy discharge rate estimate and energy recharge rate estimate (dR^dR^+dR^).

The computer system 15 may also include adjusting factors calculation unit 15t configured and operable to estimate various adjusting factors (W,) for the planned route, and/or for discrete road sections thereof. The computer system 15 may further include a multiplier 15e operable for adjusting the energy flow rate evaluation (dRi) by introducing the adjusting factors (W,) into the computation (e.g. , W,xi/R,)-

A distance approximator unit 15s provided in computer system 15 is used to calculate a remaining travelable distance approximation ( ) 16p based on the calculated energy flow rate (dRi) and the current charge level 13a2 of the battery (35t in Fig. 3). For example, if the energy flow rate approximation (dRi) is provided in units of energy per unit of distance, and planned route includes a single road segment (i.e. , i=l), then the remaining travelable distance approximation may be calculated in the distance approximator unit 15s by dividing the current charge level E_c of the battery by the adjusted energy flow rate approximation (dRi) e.g. , D = E_C /(d^ - W_t ).

On the other hand if the planned route is segmented into two or more discrete road segments S_j (j=l ,2,3, .. .,n, where n is an integer, n>\), then the approximation unit 15s may calculate the remaining travelable distance approximation iteratively based on computation of residual battery energy state ( E ^es) ) for each road segment S,- e.g. , g = E_c - (E_t ) , where E_c is the amount of energy currently contained in the battery and E_i = dR_{ ^■ S_{ designates an amount of battery energy expected to be discharged over road segment S,- (j and are positive integers, j<n and i<n). If the value of the residual battery energy computed for a certain road segment S,- is negative ( E ^es) < 0 ) then it is assumed that the amount of energy contained in the battery E_c is not sufficient and that the battery is expected to go flat during the previous road segment S/j. In this case, the remaining travelable distance may be approximated by summating the lengths of the road segments downstream to said previous road segment

S_j.i, e.g. , D = ^ 5_; . Alternatively, the energy flow rate dR _l and the residual battery energy computed for the said previous road segment may be used to adjust the calculation e.g. , D = (∑ S, ) + E _ I dR^ .

If the value of the residual battery energy computed for all road segments S_j is positive ( E^{( s)} > 0 , for j= 1 ,2,3, .. . , n) then it is assumed that the amount of energy contained in the battery E_c is sufficient for the planned route 5, and the remaining travelable distance may be computed in this case by dividing the current battery energy level (E_c) by an average of the energy flow rate values e.g. , D = ^'^_j dS_i + E^{"^s) I dR_w where

E_n ^(res) denotes the amount of energy expected to remain in the battery after driving the route 5 e.g. , E^^es) = E_c - ^ {dR_t ^■ S_t) , and dR_w is a weighted average of some, or all, of the calculated energy discharge rates dR_t, e.g. , dR_w = ~ = {E_C - E^[- ^es))l S■ Fig. 5 exemplifies a possible process for computation of a remaining travelable distance performed for a plurality of discrete road segments S,- of a planned route S. In this process after the current battery charge state E_c is retrieved (first step 62) an iterative process is commenced (63) in which the amount of battery energy expected to be discharged £\ (64) is computed for each discrete road segment S_j (e.g. , E_j = dR_j ^■ S_j , where j is a positive integer and j<n). In each iteration j of this iterative process (steps 63 to 66) it is checked (65) if the total amount of battery energy expected to be discharged between the first road segment / and the 7^th road segment /,

is within a predetermined bound.

For example, in some possible embodiments the predetermined bound may be defined to be some portion Kl (e.g., 90%) of the current charge state of the battery E_c i

e.g. , (E_t ) < K\ - E_C . In other possible embodiments the predetermined bound may be i=l

defined to reserve a specific portion (e.g., 10%) of the battery energy. For example, the predetermined bound may be set to reserve a certain portion K2 of the maximal energy capacity £„ of the battery e.g. , ^ (E_t ) < (K\^■ E_c - K2^■ E_max ) , thereby defining safety i=l

margins within the calculation of the remaining travelable distance. While the energy portions factors Kl and K2 may generally be set in the range of 0 to 1 , it may be preferable to set energy portion factor Kl in the range of 0.8 to 1 (inclusive) and energy portion factor K2 in the range of 0 to 0.2 (inclusive). For example, in possible embodiments it may be desired that the predetermined bound define only a safety margin defined by a portion K2 of the battery maximal capacity (e.g. , by setting Kl=\), while in other possible embodiments it may be desired that the predetermined bound be defined as a portion of the current battery energy only (e.g. , by setting K2=0).

If the computation of the total energy expected to be discharged is within the predetermined bound for all of the road segments (e.g. , (E_t) < (K\ - E_c - K2^■ E^ ) i=l

for =1 ,2,3, .. .,«), it is than assumed that the battery will not go flat during the ride along the planned route, and in this case the process steps 63 to 66 will be carried out for all road segments of the planned route. As the loop of steps 63 to 66 is completed, the remaining travelable distance may be calculated (68) based on the residual battery energy computed for the last road segments S„ of the route e.g. , by subtracting from the current battery energy state E_c the sum of total battery energy expected to be discharged along the planned route E_n ^{res) = E_c - ^ E_t · A weighted average energy flow rate dR_w computed for the planned route 5 may be used in this computation and a sum ( ^ 5, ) of i=l the lengths of the road segments of the planned route, as exemplified hereinabove. If it is determined (65) that the total energy expected to be discharged computed in a certain iteration j is not within the predetermined bound i.e. ,

(E_t) > (K\^■ E_c - K2^■ E_max) , then it is assumed that the battery may go flat during the i=l

specific road segment . . In such an event, the process terminates in computation of the remaining travelable distance based on the road segments for which the computed total battery energy expected to be discharged is within the predetermined bound (67, i.e. , for l< < -2). For example, by summating the lengths of all of the road segments for which the computed total battery energy expected to be discharged was within the

j-2

predetermined bound, except for the last one (e.g. , ^ ¹^; ) and adding to the summation

i=l

result a remaining travelable distance computed for the last discrete road segment for which the battery is expected to go flat, e.g. , D = S_t) + E _l I dR _l■

The process may proceed to determine in step 69 possible corrective measures that may be adopted by the user of the vehicle in order to increase the chances of reaching the target destination. For example, the user may be advised to divert from the planned route towards a reachable battery service station (BSS 17). Alternatively, the user may be advised to change driving style and/or perform any other possible energy saving actions e.g. , close one or more windows, reduce or eliminate use of air- conditioning, discharge heavy payload, and suchlike.

Step 69 may include presenting to the user via the user interface 35u reachable battery service stations, and allowing the user to select the most suitable battery service station 17 that satisfies the user's needs. Alternatively, the service provider 36 or the control unit of the vehicle 35 may select a suitable battery service station 17 and instruct the user to approach it to replenish the vehicle power source. In certain situations the suitable battery service station 17 may be selected to be the nearest station within the remaining travelable distance of the vehicle, and/or any reachable battery service station offering the best price and/or having compatible battery charging equipment and/or compatible charged batteries (e.g. , compatible to the vehicle of the user).

In possible embodiments the process illustrated in Fig. 5 is continuously, periodically or intermittently, performed during the ride along the planned route. It may happen that planned routes initially having a reachable target destination according to the computation of the remaining travelable distance approximation, appear along the ride to be unreachable e.g., due to unexpected excess battery consumption along certain road segments. It is important that such situations are identified quickly to provide the user with possible corrective measures (step 69) as soon as possible.

In case the user chooses to access a battery service station to replenish the vehicle power source, then a new planned route to the target destination may be generated using the selected battery service station as the current location of the vehicle, and the processes illustrated in Fig. 5 may be carried out for the newly generated planned route by estimating the amount of replenished energy the vehicle will have after being serviced in the battery service station. If it is determined that the target destination is still unreachable after replenishing the vehicle's power source, another one or more suitable battery service stations may be selected towards the target destination until it is determined that the target destination is reachable.

The remaining travelable distance approximation may be adapted in real time during the ride based on data indications collected during the ride in order to adjust the approximated remaining travelable distance to varying conditions that cannot be accurately foreseen. Fig. 6 demonstrates one possible process wherein the travelable distance approximation is continuously or periodically updated in real-time during the ride. First, current location (70) and the target destination of the user (71) are determined (72). Typically, the current location is obtained from the positioning system 35g, and the target destination may be determined by querying the user through the user interface 35u of the control unit 35. However, if the user did not indicate a target destination, then the system derives a possible destination (72) based on statistical data collected in the system. For example, the collected route data may be analyzed by the computer system 15 or by the control unit 35 of the vehicle 13a to derive a target destination based on the current location of the vehicle 13a and the current time, as exemplified hereinabove.

After the target destination is determined, a driving route is planned (73). Based on the planned route, the relevant statistical, profile and/or roads data are collected (74) and analyzed. The analyzed data is then used to identify discrete road segments (75) of the planned route for which the energy flow calculation requires specific considerations. Next, a battery energy flow rate is computed (76), and adjusting factors are calculated (77), for each of the identified discrete road segments, or for the entire length of the planned route. At this stage the remaining travelable distance may be approximated by measuring the battery charge level (78) and, based thereon, computing a travelable distance for the identified discrete road segments (79). The remaining travelable distance approximation may be then displayed via the user interface 35u and/or sent to the service provider for monitoring. It is noted that the data analysis and computations (steps 74 to 79) may be carried out by the service provider (e.g. , employing the computer system 15) or by the control unit 35 of the vehicle 13a.

The remaining travelable distance is continuously or periodically updated by obtaining new readings of the current location (80) of the vehicle 13a, of the battery charge state and temperature, and retrieving real-time updates on road conditions and/or driving patterns of the user. For example, it may be determined (81) that the remaining travelable distance approximation should be updated if the user has opened one or more windows and/or switched on an air-conditioning system, and/or started to aggressively accelerate the vehicle and drive at high speeds. Or, as another example, if received traffic updates indicate that there are traffic loads on road segments of the planned route.

As yet another example, the vehicle's payload may change along the ride as passengers and/or luggage are loaded onto, or discharged from, the vehicle, which may require applying corresponding adjustments in the remaining travelable distance approximation.

Receipt of such updates may require identification of new sub-segments in the planned route or carrying out the segmentation step (75) for the residual planned route according to the current location of the vehicle (80), that is carried by passing the control back to the segmentation step (75). Based on the new segmentation, or sub- segmentation, the remaining travelable distance is approximated again by repeating the prescribed steps i.e., calculation of energy flow rate (76) and adjusting factors (77) for the newly identified road segments, measuring the battery charge level (78) and travelable distance computation (79).

On the other hand, if there are no updates (81) , control is passed back to the battery charge level measurement step (78), and a new remaining travelable distance approximation is carried out (79) based on the previously determined segmentation (75), battery energy flow rate (76) and adjusting factors (77) (i.e., without repeating steps 75, 76 and 77). It is noted that though the reporting of the battery charge state from the vehicle's internal information system may be based on its current voltage state or other electrical features, the relation between the battery voltage and remaining battery energy may change due to aging of the battery, and it also depends on the temperature of the battery and the number of recharge cycles. Accordingly, in certain embodiments, the battery status module 35dl, and/or the control unit 35, may be configured to evaluate the charge level of the battery 35t based on the battery age, battery temperature and/or its charging history.

For example, the vehicle's control unit 35 may be configured to translate a measured electrical property (e.g. , voltage) of the battery 35t, reported by the battery status module 35dl, to an actual battery charge level based on historical data of the battery 35t maintained by the control unit 35, based on information retrieved for the battery 35t from a control center or service provider, and/or based on the current temperature of the battery 35t. In possible embodiments the charge level of the battery 35t is determined using fixed monotonic curves that characterize a relation between the voltage level of the battery and the actual energy stored in it. For example, the control center, or any other communicable server, may be used to store lookup tables (e.g. , in the memory 15m of the computer system 15) representing monotonic curve relations of various types of batteries, which are used to return an actual amount of energy stored in a battery upon receipt of the battery temperature and/or battery age. Additionally or alternatively, such monotonic curve lookup tables may be stored and used in the internal computer of the vehicle 13a (e.g. , in the memory 35m of control unit 35), or in the status reporting modules 35d, to allow instant extraction of the battery charge level by the internal computer of the vehicle.

The computed remaining travelable distance approximation may be presented to the user on a display device of the user interface 35u, or alternatively, or additionally, on a dedicated user interface provided in the vehicle 13a, and it may be also sent for display to other devices such as a mobile handset or tablet of the user (e.g. , over a Bluetooth link). In case of a single target destination, the remaining travelable distance approximation may be displayed in a numerical or other textual representation form, and/or graphically on a map showing the planned route and the expected driving distance thereon. In cases where multiple target destinations are analyzed, the computed remaining travelable distance approximations may be presented in the form of a range of corresponding approximation values, and/or graphically presented on a map showing all analyzed routes and the different distances that can be traveled on each of the routes.

A contour line may be drawn to connect between the maximal distances on each of the routes to present an expected reachable area. Fig. 7 exemplifies approximation of travelable distances, D_a, D_b, D_c,..., D_e, for a vehicle 13a to a plurality of respective possible target destinations 37a, 37b, 37c,...,37e, and possible display of relevant data in a display device 88 (e.g., may be part of the user interface 35u or of the positioning system 35g) provided in vehicle 13a. In this example, different travelable distances are computed for each of the target destinations, such that the reachable range designated by the closed line 86 presented in the user display on the road map 85 is typically of a curved closed asymmetric shape.

The display 88 may further present a planned route 83 to a selected target destination 37d, and textual display indications 87 of data associated with the planned route 83. For example, the textual display 87 may provide indication 87a of the distance to the target destination 37d (D2T, i.e. , ¾) from the current location of the vehicle 13a according to the planned route 83, the approximation of the remaining travelable distance (RTD) 87b computed for the planned route 83, and a ratio 87c of a the remaining residual battery energy (RE%) that will be left in the battery 35t after reaching the target destination 37d relative to the maximal energy capacity E_MAX of the battery 35t. In this example, assuming the planned route includes a single road segment Si for which a battery energy flow rate dRi was calculated, then the ratio of remaining residual battery energy RE% may be computed by dividing the amount of battery energy E^^ES) expected to remain in the battery after reaching the target destination 37d by the maximal energy capacity E_MAX of the battery e.g., RE% = 100 · E E_max = 100 · {E_c - dR, - Sj/ E^ .

The planned route 83 may include stops in one or more battery service stations, 17a 17b, presented to the user in the display 88, for replenishing (charging or exchanging) the battery of the vehicle 13a along the ride of the planned route 83. In possible embodiments the remaining travelable distance is continuously, intermittently or periodically, monitored (e.g. , based on measured battery energy and/or temperature level, and/or updated road or vehicle data) in real time during the ride along the planned route 83 to verify that the target destination is reachable. If it appears during the ride that the target destination is not reachable (e.g., if the battery energy consumption is greater than expected), then a new route to the target destination may be generated to include one or more battery service stations for charging or exchanging the battery of the vehicle. For example, generation of the new route may be part of generation of an energy plan computed for the vehicle by the internal computer of the vehicle or by the control center, as described in International Patent Application No. PCT/US2009/057029, of the same applicant hereof, the content of which is incorporated herein by reference.

Fig. 8A exemplifies process steps that may be embedded in the process exemplified in Fig. 6 for updating a planned route to include one or more battery service stations 17. In this example, after the remaining travelable distance is determined in step 79 of Fig. 6 it is determined based on the calculated remaining travelable distance if the target destination is reachable (90). If it is determined that the target destination is reachable then the control is passed to the next process step (80) in Fig. 6 which thus proceeds without, or with minimal, interruption. If it is however realized that the target destination is not reachable, then one or more suitable battery service stations 17 are determined (91) for replenishing the battery of the vehicle. The one or more suitable battery service stations 17 may include all battery service stations that are reachable (i.e., within the calculated remaining travelable distance), and/or stations having compatible charging equipment or suitable replenished batteries.

Optionally, the one or more suitable battery service stations may be presented to the user for selection (92, designated by dotted lines) of a preferable service station for being serviced at. Alternatively, a suitable battery service station is selected without user intervention according to battery stations status report received from the service provider (or from a communicable server), to guarantee timely receipt of the desired service with minimal deviations from the originally planned route to the target destination. Once a suitable battery service station is selected, the original target destination is stored in memory and the selected battery service station is set as the destination (93). The control is then passed to step 73 in Fig. 6 for determining a route to the selected battery service station and proceeding with the real-time approximation and update of the remaining travelable distance approximation during a ride towards the selected battery service station.

Fig. 8B exemplifies further possible adjustments to the real-time remaining travelable distance approximation of Fig. 6, wherein after each step of determining the current location of the vehicle (80) it is checked if the target destination was reached (94). If it is determined that target destination is not yet reached, then the process of Fig. 6 proceeds without, or with minimal, interruptions, as the control is passed to step 81 in Fig. 6. Otherwise, if it determined that target destination was reached, then it is checked if the target destination is a selected battery station (95). If it is determined that the vehicle reached a selected battery service station then the process is halted until receipt of the required service (96). Otherwise, if it is determined that the vehicle reached its original target destination, then the process is terminated (98). After the vehicle receives the required service in step 96, the original target destination is fetched from the memory and a new route to the target destination from the current location (i.e., from the battery service station) is planned as the control is passed to step 73 in Fig. 6.

The above examples and description have of course been provided only for the purpose of illustration, and are not intended to limit the invention in any way. As will be appreciated by the skilled person, the invention can be carried out in a great variety of ways, employing more than one technique from those described above, all without exceeding the scope of the invention.

Claims

CLAIMS:

1. A method for calculating a remaining travelable distance of a vehicle powered by a battery, the method comprising:

providing data indicative of a route of said vehicle;

providing statistical data related to a route and to a user of said vehicle;

providing data about a measured charge level of said battery indicative of an amount of energy stored in the battery;

utilizing the statistical data and determining a rate of battery energy flow for said battery indicative of a rate of discharge or recharge of battery energy along at least a segment of road in said route; and

determining a remaining travelable distance based on said rate of battery energy flow and said battery charge level.

2. The method according to claim 1, further comprising identifying based on the retrieved data a plurality of discrete road segments in the route, wherein the calculating of the battery energy flow rate comprises calculating for each of said plurality of discrete road segments a discrete rate of battery energy flow based at least in part on specific considerations associated therewith.

3. The method according to claim 1 or 2, wherein the statistical data includes at least one of: driving patterns of the user, at least one route frequently driven by the user, and rate of battery energy flow along at least one segment of road in the at least one route frequently driven by the user.

4. The method according to any one of claims 1 to 3, wherein the statistical data includes data about a plurality of other users, wherein said statistical data and the data indicative of the route have at least one common feature selected from the following group: at least one segment of road of a frequently driven route, same time of day in which the route is driven, same day of week in which the route is driven, same day of month in which the route is driven, similar driving style, similar road behavior.

5. The method according to any one of claims 2 to 4 wherein the statistical data is collected from a plurality of users and maintained in a storage accessible by the vehicle, the method further comprising associating data items of said statistical data to road segments of previously driven routes, and wherein providing statistical data related to the route includes providing data items based on road segments of the route of the vehicle.

6. The method according to claim 5, wherein the storage is hosted by a data server accessible over a data network.

7. The method according to any one of claims 1 to 6, wherein the retrieved data comprises at least one of: road data indicative of road conditions along the at least one segment of road of the route; vehicle data indicative of conditions of the vehicle or of its battery; and topographic conditions of the at least one segment of road of the route.

8. The method according to claim 7, wherein the road data includes at least one of the following: weather conditions along at least one segment of road of the route; traffic conditions along at least one segment of road of the route; number of lanes in at least one segment of road of the route; road curvature of at least one segment of road of the route; and gradient of at least one segment of road of the route.

9. The method according to claim 7 or 8, wherein the vehicle data includes at least one of the following: vehicle weight, vehicle payload, windows state, amount of energy consumed by electric appliances of the vehicle, motor efficiency, battery efficiency, battery temperature.

10. The method according to any one of claims 1 to 9, further comprising determining based on the retrieved data at least one adjusting factor indicative of energy losses or gains along at least one segment of road of the route, wherein the calculating of the rate of battery energy flow is based at least in part on said at least one adjusting factor.

11. The method according to claim 10, wherein determining the at least one adjusting factor includes determining resisting or propelling conditions along at least one segment of road of the route based on the retrieved data, wherein the at least one adjusting factor is based at least in part on said resisting or propelling conditions.

12. The method according to claim 11, wherein determining resisting or propelling conditions includes determining automotive aerodynamic parameters of the vehicle along the at least one segment of road, wherein the at least one adjusting factor is based at least in part on said automotive aerodynamic parameters.

13. The method according to any one of claims 3 to 12, wherein the specific considerations are derived from at least one of the following group: the topographic conditions, the road data, the weather conditions, the traffic conditions, the driving patterns of the user, and the automotive aerodynamic parameters of the vehicle.

14. The method according to any one of claims 7 to 13, wherein identifying the plurality of discrete road segments is based at least in part on one of the following: the driving patterns of the user; the rate of battery energy flow along at least one segment of road of the route; the road data; the vehicle data; and the topographic conditions.

15. The method according to any one of claims 7 to 13, wherein identifying the plurality of discrete road segments is based on data collected from a plurality of users.

16. The method according to any one of claims 2 to 15, further comprising identifying in the plurality of discrete road segments two or more intersecting discrete road segments and identifying at least one discrete road segment mutual to said two or more discrete road segments according to said intersection, wherein the calculating of the battery energy flow rate comprises calculating for said at least one mutual discrete road segment a discrete rate of battery energy flow based at least in part on specific considerations associated with said two or more intersecting discrete road segments.

17. The method according to any one of claims 2 to 16, wherein the calculating of the remaining travelable distance comprises:

calculating for each discrete road segment an amount of expected battery energy discharge along a portion of the route between the first road segment of the route and the specific discrete road segment based on the calculated battery energy flow rates of the specific road segment and of discrete road segments located downstream to the specific discrete road segment, and whenever determining based on the expected amount of battery energy discharge calculated for a specific discrete road segment that the charge level of the battery is not sufficient to complete the route calculating the remaining travelable distance based on lengths of the discrete road segments located downstream to the specific discrete road segment.

18. The method according to claim 17, further comprising calculating residual battery energy indicative of an amount of energy expected to remain in the battery when said specific discrete road segment is reached, wherein the remaining travelable distance is calculated based at least in part on said residual battery energy.

19. The method according to claim 17, comprising, whenever determining based on the expected battery energy discharge calculated for all discrete road segment that the charge level of the battery is sufficient to complete the route, calculating remaining travelable distance based on a residual battery energy computed for the last discrete road segment of the route.

20. The method according to any one of claims 17 to 19, wherein calculating the remaining travelable distance is based on a weighted average of energy flow rates computed for two or more of the discrete road segments.

21. The method according to any one of claims 17 to 20, comprising adding to the route one or more battery service stations whenever it is determined that the charge level of the battery is not sufficient to complete the route.

22. The method according to any one of the preceding claims, further comprising determining corrective measures that the user of the vehicle may perform in order to increase the chances of reaching a target destination of the route, whenever the value of the calculated battery residual energy content is negative.

23. The method according to any one of the preceding claims, wherein determining the route comprises determining a target destination based on data received from the user or on the at least one frequently driven route, and on at least one of the following indications: current location of the vehicle, time of day the at least one frequently driven route is being driven, and day of the month the at least one frequently driven route is being driven.

24. The method according to any one of the preceding claims, comprising displaying in a display device provided in the vehicle data related to the route, said data comprising at least one of the following: distance from current location of the vehicle to the target destination; the calculated remaining travelable distance; data indicative of a portion of the battery energy expected to be contained in the battery after reaching the target destination; and the route and any planned stops in battery service stations included in the route.

25. A system for use in monitoring a traveling vehicle powered by a battery, comprising:

a processing utility connectable to a memory utility for receiving data comprising statistical data related to a plurality of routes driven by a plurality of users or related to said users, the processing utility comprising:

a battery energy flow estimator configured and operable to receive and process a planned route and data comprising statistical data of at least one of said plurality of routes or of at least one of said users, and calculate, based on said data, a rate of battery energy flow for said battery along at least a segment of road of said planned route; and

a distance approximating unit configured and operable to receive data indicative of an amount of energy stored in said battery and data indicative of said rate of battery energy flow, and calculate a remaining travelable distance for said vehicle based thereon.

26. A system according to claim 25, wherein the battery energy flow estimator is configured and operable to identify, based on the received data, a plurality of discrete road segments in the planned route, and to calculate a respective discrete rate of battery energy flow for each of said plurality of discrete road segments based at least in part on specific considerations associated therewith and derived from said data.

27. A system according to claim 25 or 26, wherein the statistical data includes at least one of: driving patterns of a user of the vehicle, at least one route frequently driven by the users, rate of battery energy flow along at least one segment of road in the at least one frequently driven routes.

28. A system according to any one of claims 25 to 27, wherein the statistical data includes data about a plurality of other users, wherein said statistical data and the data indicative of the route have at least one common feature selected from the following group: at least one segment of road of a frequently driven route, same time of day in which the route is driven, same day of week in which the route is driven, same day of month in which the route is driven, similar driving style, similar road behavior.

29. A system according to any one of claims 25 to 28, wherein the retrieved data comprises at least one of: road data indicative of road conditions along the at least one road segment; vehicle data indicative of conditions of the vehicle or of its battery; topographic conditions of at least one road segment of the planned route.

30. A system according to any one of claims 25 to 29, wherein the road data includes at least one of the following: weather conditions along at least one segment of road of the planned route; traffic conditions along at least one segment of road of the planned route; number of lanes along at least one segment of road of the planned route; road curvature of at least one segment of road of the planned route; and gradient along at least one segment of road of the planned route.

31. A system according to claim 29 or 30, wherein the vehicle data includes at least one of the following: vehicle weight, vehicle payload, windows state, rate of energy consumed by electric appliances of the vehicle, motor efficiency, battery efficiency, battery temperature.

32. A system according to any one of claims 25 to 31, wherein the battery energy flow estimator is configured and operable to determine, based on the received data, at least one adjusting factor indicative of energy losses or gains along at least one road segment of the planned route, and to calculate the rate of battery energy flow based at least in part on said at least one adjusting factor.

33. A system according to claim 32, wherein the battery energy flow estimator is configured and operable to determine resisting or propelling conditions along the at least one road segment of the planned route based on the retrieved data, wherein the at least one adjusting factor is determined based at least in part on said resisting or propelling conditions.

34. A system according to claim 33, wherein the battery energy flow estimator is configured and operable to determine automotive aerodynamic parameters of the vehicle along at least one road segment of the planned route, wherein the resisting or propelling conditions are determined based at least in part on said automotive aerodynamic parameters.

35. A system according to any one of claims 26 to 34, wherein the specific considerations are derived from at least one of the following: the topographic conditions, the road data, the weather conditions, the traffic conditions, the driving patterns of the user, and the automotive aerodynamic parameters of the vehicle.

36. A system according to any one of claims 26 to 35, wherein the plurality of discrete road segments are identified based at least in part on one of the following: the driving patterns of the user; the rate of battery energy flow along at least one of the segments of road in the at least one frequently driven routes; the road data; the vehicle data; and the topographic conditions.

37. A system according to any one of claims 26 to 36, wherein the battery energy flow estimator is configured and operable to identify in the plurality of discrete road segments two or more intersecting discrete road segments and to identify at least one discrete road segment mutual to said two or more discrete road segments according to said intersection, and to calculate a battery energy flow rate for said at least one mutual discrete road segment based at least in part on specific considerations associated with said two or more intersecting discrete road segments.

38. A system according to any one of claims 26 to 37, wherein the distance approximating unit is configured and operable to: calculate for each discrete road segment an amount of expected battery energy discharge along a portion of the route between the first road segment of the route and the specific discrete road segment based on calculated battery energy flow rates of the specific road segment and of discrete road segments located downstream to the specific discrete road segment; determine based on the expected battery energy discharge calculated for a specific discrete road segment if the charge level of the battery is sufficient to complete the route; and if it is determined that the buttery charge level is not sufficient, calculate a remaining travelable distance based on lengths of the discrete road segments located downstream to the specific discrete road segment.

39. A system according to claim 38, wherein the distance approximating unit is configured and operable to compute a residual battery energy indicative of an amount of energy expected to remain in the battery when the specific discrete road segment is reached, and to calculate the remaining travelable distance based at least in part on said residual battery energy.

40. A system according to claim 38, wherein the distance approximating unit is configured and operable to compute a remaining travelable distance based on a residual battery energy computed for the last discrete road segment of the route, whenever it is determined that the charge level of the battery is sufficient to complete the route.

41. A system according to any one of claims 38 to 40, wherein the distance approximating unit is configured and operable to calculate a weighted average of energy flow rates computed for two or more of the discrete road segments, and calculate the remaining travelable distance based at least in part on said weighted average.

42. A system according to any one of claims 38 to 41, wherein the processing utility is configured and operable to add to the route one or more battery service stations whenever it is determined that the charge level of the battery is not sufficient to complete the route.

43. A system according to any one of claims 25 to 42, wherein the distance approximating unit is configured and operable to determine corrective measures that the user of the vehicle may perform in order to increase the chances of reaching a target destination of the planned route, whenever the value of the calculated battery residual energy content is negative.

44. A system according to any one of claims 30 to 43, wherein the battery energy flow estimator is configured and operable to determine the planned route by determining a target destination based on data received from the user of the vehicle or based on the statistical data, and on at least one of the following indications: current location of the vehicle, time of day the frequently driven route is being driven, and day of the month the frequently driven route is being driven.

45. A system according to any one of claims 25 to 44, further comprising a charge level measuring unit configured to measure the amount of energy stored in said battery.

46. A method for presenting data related to a route of a vehicle, comprising: receiving data indicative of battery energy flow along said route or along discrete road segments thereof;

computing based on said data an estimation of an amount of energy to be consumed from a battery of the vehicle during a ride along said route;

receiving data indicative of an amount of energy contained in the battery;

computing data indicative of a portion of the battery energy expected to be contained in the battery once the ride along said route is completed; and

outputting the computed data to a display utility, a memory utility, or a remote computer system.

47. A method according to claim 46, wherein the data indicative of the portion of the battery energy expected to be contained in the battery once the ride along the route is completed is provided in the form of a percentage relative to the maximal energy content of the battery, or in the form of distance units indicating a remaining travelable distance.