Range estimation for battery electric vehicles

1 . A method of generating estimates of end of range for an electric vehicle, the vehicle comprising an electric motor providing drive power to the vehicle, a battery that provides current to the electric motor to use in providing drive power, a user screen for displaying a map to a user, and a controller configured to obtain map information and generate a map on the user screen, comprising:

determining each of a current location of the electric vehicle using the map information, and a state of charge (SOC) of the battery;

using the determined current location and SOC of the battery:

a) identifying a plurality of potential destinations around the current location;

b) determining route information for each of the plurality of potential destinations;

c) simulating a prediction model for each of the plurality of potential destinations which predicts SOC of the battery along potential routes to each of the plurality of potential destinations using the route information;

d) calculating and displaying to the user via the user screen a battery SOC consumption map based on the predicted SOC of the battery along the potential routes, the battery SOC consumption map including, for each of the plurality of potential destinations, a graphical indication of at least one of (i) a portion of a corresponding potential route at which the SOC is predicted to cross a reserve threshold and (ii) a portion of the potential route at which the SOC is predicted to be insufficient to reach the potential destination;

by the controller, automatically controlling a navigation guidance function based on the battery SOC consumption map by:

(i) suppressing from presentation on the user screen potential destinations having no corresponding potential route on which the SOC is predicted to remain above the reserve threshold, and

(ii) prioritizing guidance to remaining potential destinations according to predicted SOC at arrival; and

wherein identifying the plurality of potential destinations is performed automatically by the controller without obtaining a destination input from the user.

2 . The method of claim 1 , further comprising displaying on the battery SOC consumption map at least one range indicator each indicating a location at which the battery SOC is predicted to cross a first boundary.

3 . The method of claim 2 , wherein the at least one range indicator includes:

a first range indicator on a first potential route to a first potential destination, the first range indicator showing where on the first potential route the battery SOC is predicted to cross a first boundary; and

a second range indicator on a second potential route to a second potential destination, the second range indicator showing where on the second potential route the battery SOC is predicted to cross a first boundary.

4 . The method of claim 1 , wherein calculating the map comprises interpolation using route information for at least two of the plurality of potential destinations to predict battery SOC at a location not simulated with the prediction model.

5 . The method of claim 1 , wherein simulating a prediction model for each of the plurality of potential destinations uses the route information by accounting for at least one of traffic, grade, and curvature of the potential route.

6 . The method of claim 1 , wherein each of steps a), b), c) and d) are performed as a first iteration of the method, and the method further comprises, after completing the first iteration, determining a new location and a new state of the battery and performing a second iteration of the method, wherein step a) in the second iteration is performed by:

determining an estimated maximum distance the vehicle can travel with the new state of the battery;

defining a plurality of segments within a region having a radius determined from the estimated maximum distance;

categorizing the plurality of segments into filled and unfilled segments by identifying segments as filled if routes from the vehicle to the potential destinations from the first iteration are contained in the segments, and otherwise as unfilled; and

identifying a plurality of potential destinations in the second iteration by targeting the unfilled segments.

7 . The method of claim 1 , wherein step a) is performed by first determining unreachable locations around the vehicle, and omitting the unreachable locations from consideration when identifying the plurality of potential destinations.

8 . The method of claim 1 , wherein step a) is performed by applying one or more rules to space the potential destinations from one another.

9 . The method of claim 1 , wherein step a) is performed without obtaining a destination from the user.

10 . The method of claim 1 , wherein the method is performed iteratively such that a memory associated with the controller stores a set of previously analyzed potential destinations, and step a) is performed by:

defining segments in a map region surrounding the vehicle;

identifying first segments which do not contain a previously analyzed potential destination; and

identifying the potential destinations in the first segments.

11 . The method of claim 10 , wherein the memory updates the set of previously analyzed potential destinations on a first-in, first-out basis.

12 . The method of claim 1 , further comprising:

determining from the predicted SOC along each potential route a minimum range based on the battery SOC;

determining from the predicted SOC along each potential route a maximum range based on the battery SOC; and

presenting the minimum range and maximum range to the user of the vehicle.

13 . The method of claim 1 , further comprising determining from the predicted SOC along each potential route a non-directional range of the vehicle as a function of the vehicle range on each potential route, and presenting the non-directional range to the user.

14 . The method of claim 1 , wherein the method is performed iteratively such that a memory associated with the controller stores a set of previously analyzed potential destinations and associated simulated routes, and the method further comprises:

using a current direction of vehicle motion to assign, for each stored route, a probability that the vehicle will travel along that stored simulated route in a next driving interval, the probability being a function of at least heading alignment between the stored simulated route and the current direction of vehicle motion;

calculating a directional range of the vehicle using a probability-weighted average of all simulated routes; and

presenting the directional range of the vehicle to the user.

15 . A controller for an electric vehicle, the electric vehicle having an electric motor providing drive power, a battery that provides current to the electric motor to use in providing drive power, a user screen for displaying a map to a user, the controller configured to obtain map information and generate a map on the user screen, the controller comprising one or more processors and a memory stored instructions that, when executed, executed cause the controller to perform the method of claim 1 , including automatically controlling a navigation guidance function based on the battery SOC consumption map by suppressing unreachable potential destinations and prioritizing reachable potential destinations according to predicted SOC at arrival.

16 . An electric vehicle comprising an electric motor providing drive power, a battery that provides current to the electric motor to use in providing drive power, a user screen for displaying a map to a user and the controller of claim 15 .

17 . A method of generating estimates of end of range for a vehicle, the vehicle having an engine consuming a fuel, a fuel tank having a capacity and containing a quantity of fuel, a user screen for displaying a map to a user, and a controller configured to obtain map information and generate a map on the user screen, the method comprising:

determining each of a current location of the electric vehicle using the map information, and a quantity of fuel in the fuel tank;

using the determined current location and the determined quantity of fuel:

a) identifying a plurality of potential destinations around the current location;

b) determining route information for each of the plurality of potential destinations;

c) simulating a prediction model for each of the plurality of potential destinations which predicts remaining quantity of fuel in the fuel tank along a potential route to each of the plurality of potential destinations using the route information; and

d) calculating and reporting to the user via the user screen a fuel consumption map based on the predicted fuel consumption along the potential routes.

18 . The method of claim 17 , wherein the method is performed iteratively such that a memory associated with the controller stores a set of previously analyzed potential destinations and associated simulated routes, and the method further comprises:

using a direction of vehicle motion to assign a set of probabilities to simulated routes for each of the stored set of previously analyzed potential destinations;

calculating a directional range of the vehicle using a probability-weighted average of all simulated routes; and

presenting the directional range of the vehicle to the user.

19 . The method of claim 17 , wherein step a) is performed without obtaining a destination from the user.

20 . The method of claim 17 , wherein the method is performed iteratively such that a memory associated with the controller stores a set of previously analyzed potential destinations, and step a) is performed by:

defining segments in a map region surrounding the vehicle;

identifying first segments which do not contain a previously analyzed potential destination; and

identifying the potential destinations in the first segments.