METHOD FOR DETERMINING PREDICTED ACCELERATION INFORMATION IN AN ELECTRIC VEHICLE AND SUCH AN ELECTRIC VEHICLE

Abstract

Method for determining predicted acceleration information which describes a future acceleration potential of an electric vehicle having an electric motor as the drive device, which is supplied with electric power from a battery in the electric vehicle, this method including the following steps: Supplying power predictive information of the electric motor, which describes the predicted available acceleration power of the electric motor for at least one future period of time, Determining the acceleration information from the power predictive information by using a vehicle model which supplies the prevailing operating state of the electric vehicle, at least one vehicle parameter describing the acceleration possible on the basis of the acceleration power and/or using predictive path data supplied in particular by a navigation system for the period of time.

Claims

1. A method for determining a predicted acceleration information which describes a future acceleration potential of an electric vehicle having an electric motor as the drive device, which is supplied with electric power from a battery in the electric vehicle, comprising the following steps: Providing power predictive information of the electric motor which describes the predicted available acceleration power of the electric motor for at least one future period of time, Determining the acceleration information from the power prediction information by using a vehicle model which supplies the prevailing operating state of the electric vehicle, at least one vehicle parameter describing the acceleration possible on the basis of the acceleration power and/or using predictive path data supplied in particular by a navigation system for the period of time.

2. The method according to claim 1, wherein the acceleration information is used to control at least one driver assistance system in particular a longitudinal guidance system of the electric vehicle, in particular a predictive operating strategy of the driver assistance system.

3. The method according to claim 1, wherein, to determine the power predictive information, at least one item of energy information describing a prevailing state of the battery and/or a prevailing state of an electronic power system associated with the battery and/or the electric motor, and/or information about the environment describing the operating conditions of the electric motor and/or the battery and/or the electronic power system is/are used.

4. The method according to claim 3, wherein the energy information includes a state of charge of the battery and/or an aging state of the battery and/or the information about the environment includes at least one temperature, in particular an outside temperature and/or a battery temperature, and/or an efficiency model is used that is parameterized by the energy information and/or the information about the environment and describes the conversion of electric power stored in the battery into acceleration power that can be utilized by the electric motor.

5. The method according to claim 1, wherein a vehicle model supplying at least one dynamic vehicle parameter and at least one static vehicle parameter is used.

6. The method according to claim 5, wherein a prevailing vehicle weight and/or a prevailing weight distribution and/or a prevailing and/or predicted speed of the electric vehicle is/are used as a vehicle parameter.

7. The method according to claim 1, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

8. The method according to claim 1, wherein the predictive path data includes a predictive speed profile of the electric vehicle and/or a predictive speed profile of the electric vehicle is determined from the predictive path data, wherein the predicted speed of the electric vehicle at a point in time within the period of time is used for determining the acceleration potential for this point in time.

9. The method according to claim 1, wherein an acceleration profile describing the maximum possible acceleration over the period of time is determined as the acceleration information and/or at least one item of information about the cause of a deviation from a nominal acceleration potential is associated with the acceleration information.

10. The method according to claim 2, wherein, to determine the power predictive information, at least one item of energy information describing a prevailing state of the battery and/or a prevailing state of an electronic power system associated with the battery and/or the electric motor, and/or information about the environment describing the operating conditions of the electric motor and/or the battery and/or the electronic power system is/are used.

11. The method according to claim 2, wherein a vehicle model supplying at least one dynamic vehicle parameter and at least one static vehicle parameter is used.

12. The method according to claim 3, wherein a vehicle model supplying at least one dynamic vehicle parameter and at least one static vehicle parameter is used.

13. The method according to claim 4, wherein a vehicle model supplying at least one dynamic vehicle parameter and at least one static vehicle parameter is used.

14. The method according to claim 2, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

15. The method according to claim 3, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

16. The method according to claim 4, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

17. The method according to claim 5, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

18. The method according to claim 6, wherein predictive path data describing curve information and/or slope information for a segment of road in front of the vehicle is used, wherein a potential longitudinal component of the acceleration, which increases the longitudinal speed of the electric vehicle, is determined and/or a wheel slip is taken into account, based in particular on road condition information and/or coefficient of friction information of the predictive path data.

19. The method according to claim 2, wherein the predictive path data includes a predictive speed profile of the electric vehicle and/or a predictive speed profile of the electric vehicle is determined from the predictive path data, wherein the predicted speed of the electric vehicle at a point in time within the period of time is used for determining the acceleration potential for this point in time.

20. The method according to claim 3, wherein the predictive path data includes a predictive speed profile of the electric vehicle and/or a predictive speed profile of the electric vehicle is determined from the predictive path data, wherein the predicted speed of the electric vehicle at a point in time within the period of time is used for determining the acceleration potential for this point in time.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0022] Additional advantages and details of the present invention are derived from the exemplary embodiments described below and also on the basis of the drawings, in which:

[0023] FIG. 1 shows a schematic diagram of an electric vehicle according to the invention and

[0024] FIG. 2 shows a diagram to illustrate the method according to the invention.

DETAILED DESCRIPTION

[0025] FIG. 1 shows a schematic diagram of an electric vehicle 1 according to the invention, having an electric motor 2 as the drive device, whose drive power and thus optionally also acceleration power can be transmitted over the remaining drivetrain 3, which is merely indicated here, to the wheels of the vehicle 1 which are not shown in greater detail here. By using the corresponding electronic power system 4, the electric motor 2 is supplied with power from a high voltage battery 5.

[0026] Motor vehicle 1 also has a control device 6 which is designed for carrying out the method according to the invention and may comprise at least one control unit in particular an energy management control unit and/or a motor control unit and/or a control unit of a central drive assistance system. The control device 6 communicates with other vehicle systems, of which only a navigation system 7 and a driver assistance system 8 are shown here, merely as examples, the driver assistance system being designed as a longitudinal guidance system, in particular an ACC system or a cruise control system.

[0027] FIG. 2 shows a schematic diagram for carrying out the method according to the invention, which serves to determine predictive acceleration information 9 which can be supplied to the driver assistance system 8 and optionally other vehicle systems 10, in particular other driver assistance systems. This starts from power predictive information 11, which describes the predicted available acceleration power of the electric motor 2 for a future period of time, for example, for several seconds into the future. To determine the power predictive information, a check is ultimately performed to ascertain whether the maximum conceivable acceleration power that can be supplied by the electric motor 2 might be restricted by conditions of the energy system 12 (FIG. 1) itself or by the environment. To do so, the prevailing condition of the battery 5, in particular its state of charge, is described exactly like the outside temperature, the cooling conditions or the like, and may enter into a temperature model which describes the heating of the components of the energy system 12 and of the electric motor 2, which tracks the corresponding temperatures on the basis of the operation of the individual components. The temperature model is part of a general efficiency model, which describes the conversion of electric power from the battery 5 into drive power and thus also acceleration power by the electric motor 2.

[0028] This power predictive information 11 which can describe which maximum acceleration power can be made available for which period of time for various points in time of the period of time can basically be converted first into a wheel power on the wheels of the electric vehicle 1, if the instantaneous properties of the drivetrain 3 are known, which can be mapped according to another efficiency model. This wheel power is implemented by taking into account the wheel slip and/or friction losses in relation to the substrate on which the vehicle is driving.

[0029] The acceleration power of the electric motor 2 results in a change in the speed of the electric vehicle 1, which is the result based on physical principles. To do so, first the vehicle model 13 is used; this includes the vehicle speed as a dynamic vehicle parameter and the weight of the vehicle as a static vehicle parameter, wherein other vehicle properties can also be taken into account in a more detailed implementation and modeling. Furthermore, in order to be able to ascertain the acceleration information 9, this uses predictive path data 14, which is obtained in particular at least from the navigation system 7 and also contains slope information and curve information for the segment of road ahead of one's vehicle. The slope and the curve are essential for possible acceleration of the electric vehicle 1 because components which serve to provide compensation for acceleration due to earth's gravity and centrifugal force can be removed by calculation, given a knowledge of same.

[0030] In the present embodiment, the acceleration information 9 is determined as possible accelerations starting from a predictive speed profile at various points in time during the period of time. This means that for each point in time to be investigated within the period of time for which the acceleration information is to be predicted, a predictive speed of motor vehicle 1 is known, and it is possible to use the information shown, in particular the power predictive information 11, the vehicle model 13 and the predictive path data 14, to determine a maximum possible acceleration at this point in time, in exactly the same way as the maximum duration of same, which can be determined until reaching the maximum achievable speed of the electric vehicle 1, which may also be provided as part of the acceleration information 9 but can also be determined in the driver assistance system 8, for example, for blocking certain set speeds. Other or additional information is also conceivable as predictive acceleration information 9 and/or a portion thereof which describes the maximum possible acceleration of electric vehicle 1, for example, as an acceleration profile over the period of time to be predicted.

[0031] Corresponding acceleration information 9 can also be analyzed in the driver assistance system 8 and/or additional vehicle systems 10 for selecting suitable operating strategies, in particular also with regard to minimizing energy consumption and/or a predictable comfortable utilization of the driver assistance system.