CN113844457A

CN113844457A - Method and apparatus for vehicle energy management

Info

Publication number: CN113844457A
Application number: CN202111191992.7A
Authority: CN
Inventors: 禹尧; 张超
Original assignee: Daimler AG
Current assignee: Mercedes Benz Group AG
Priority date: 2021-10-13
Filing date: 2021-10-13
Publication date: 2021-12-28
Also published as: DE102022003673A1

Abstract

The present invention relates to the field of energy management of vehicles. The present invention provides a method for vehicle energy management, the method comprising the steps of: s1: obtaining events potentially affecting an automatic driving function and/or a driving assistance function of a vehicle; s2: correlating the event with at least one vehicle component for an automatic driving function and/or a driving assistance function; and, S3: determining an operating mode of a vehicle component and at least one characteristic parameter of the operating mode on the basis of the correlation, operating the vehicle component in the operating mode having the characteristic parameter. The invention also provides an apparatus for vehicle energy management and a computer program product. In the present invention, by establishing the association of specific events with vehicle components, it is possible to ensure that as far as possible only the necessary internal and external components are activated to achieve the overall optimum power consumption without compromising any system functionality.

Description

Method and apparatus for vehicle energy management

Technical Field

The invention relates to a method for vehicle energy management, an apparatus for vehicle energy management and a computer program product.

Background

In order to provide sufficient computing power and ensure safety, vehicle-equipped autopilot/driver assistance systems contain numerous actuator and sensor modules, however the introduction of these modules also entails high energy consumption, high temperatures, and noise. The development of vehicle motorization and intellectualization puts higher demands on vehicle energy management, and therefore, it is very important to reasonably distribute and control the starting, triggering and response time of each module.

Currently, a method for operating a vehicle sensor system is proposed in the prior art, in which the sensor system is operated in a normal operating mode or in an energy-saving operating mode in response to detected vehicle parameters, so that energy savings are achieved to a certain extent. Furthermore, a method is known for increasing the safety and comfort of autonomous driving, in which a vehicle system determines the probability that at least one sensor is about to become unavailable and triggers a corresponding countermeasure in advance on the basis of this probability.

However, the above solutions still have many disadvantages, and particularly, currently, only the mode switching of the sensors can be automatically triggered according to the detected preset conditions, but the correlation between the events in the vehicle operation and each sensor is not substantially established, and when there is a complex scene with multiple overlapped events, the identification only through the vehicle parameters is still insufficient to ensure the optimal power consumption of the vehicle as a whole. In addition, the existing solutions also lack specific planning of the characteristic parameters (e.g. response time, trigger timing, duration, etc.) of the respective sensor operation modes.

In this context, it is desirable to provide an improved vehicle energy management strategy to achieve optimal energy deployment for the various components of the vehicle.

Disclosure of Invention

It is an object of the present invention to provide a method for vehicle energy management, an apparatus for vehicle energy management and a computer program product to solve at least some of the problems of the prior art.

According to a first aspect of the invention, a method for energy management of a vehicle is proposed, the method comprising the steps of:

s1: obtaining events potentially affecting an automatic driving function and/or a driving assistance function of a vehicle;

s2: correlating the event with at least one vehicle component for an automatic driving function and/or a driving assistance function; and

s3: determining an operating mode of a vehicle component and at least one characteristic parameter of the operating mode on the basis of the correlation, operating the vehicle component in the operating mode having the characteristic parameter.

The invention comprises in particular the following technical concepts: the operation of vehicle components is not tied to a particular level of functionality or functional strategy, but is directly affected by individual events encountered in driving. In this way, it is ensured that, during operation of the vehicle, only the necessary internal and external components are activated as far as possible for optimum power consumption without impairing any system function. With this vehicle energy management strategy, energy savings can be realized while also significantly reducing noise and increasing the useful life of vehicle components.

Optionally, determining at least one characteristic parameter of the operating mode of the vehicle component from the correlation comprises: the duration of the operating mode of the vehicle component, the activation time of the operating mode, the deactivation time of the operating mode, the waiting time and/or the waiting distance before the operating mode is activated are determined as a function of the extent of influence of the event on the vehicle component.

Thereby, the following technical advantages are achieved: characteristic parameters of the operating mode of the relevant vehicle component are also defined on the basis of different events, whereby system exit or degradation can be controlled more precisely.

Optionally, determining the operating mode of the vehicle component according to the correlation comprises:

determining the operational necessity of the vehicle component in the event of the event; and

a first operating mode or a second operating mode of the vehicle component is selected as a function of the operating requirement, the vehicle component having a lower energy consumption in the second operating mode than in the first operating mode.

Thereby, the following technical advantages are achieved: when the automatic driving function is used, all relevant modules do not need to be started uniformly, and the starting is finished step by step according to the necessity, so that the endurance mileage of the vehicle is improved, and the energy consumption is reduced.

Alternatively, in the case of switching a vehicle component from the first operating mode to the second operating mode, the replacement vehicle component is placed in the first operating mode depending on the availability of the automatic driving function and/or the driving assistance function supported by the vehicle component.

Thereby, the following technical advantages are achieved: after waiting/sleeping a part of the vehicle components, the relevant automatic driving function/driving assistance function may be limited, in which case it may be considered appropriate to replace the original vehicle components with other vehicle components, which here also include vehicle components based on other principles, in order to improve driving safety while ensuring optimal energy consumption.

Optionally, the method further comprises the steps of:

acquiring the state change of the event along with the time;

obtaining a correlation between an event and a change in demand for a vehicle component based on the change in state; and

updating the operating mode of the vehicle component in accordance with the changed association, wherein the vehicle component is restored from the second operating mode to the first operating mode, in particular in response to the release of the event.

Thereby, the following technical advantages are achieved: as the vehicle travels, the demands placed on the vehicle components by system functions may gradually move out of the range of influence of a particular event, and the correlation between them may change in the process. By taking such variations into account, a more flexible energy management strategy can be achieved.

Optionally, the second operating mode of the vehicle component is selected when the event is indicative of at least any one of:

the vehicle environment does not satisfy the starting conditions of the automatic driving function and/or the driving assistance function supported by the vehicle component;

the vehicle state does not satisfy the starting condition of the automatic driving function and/or the driving assistance function supported by the vehicle component;

a failure of a vehicle component and/or an automatic driving function and/or a driving assistance function supported by the vehicle component; and

the automatic driving function and/or the driving assistance function supported by the vehicle components are switched off manually by the driver.

Thereby, the following technical advantages are achieved: in certain scenarios, if the driving assistance/automatic driving function enabling condition is not fulfilled, it is not necessary to have the system-related modules sense in real time in preparation for entering the functional readiness state, but rather to select an operating mode with lower energy consumption, thereby advantageously avoiding a continuous energy consuming process.

Optionally, at least one vehicle component is assigned an association with different events in an initialization phase, the operating modes of the vehicle component are stored in a bound manner for a predetermined association, and the corresponding operating mode is called up in step S3 as a function of the determined association.

Thereby, the following technical advantages are achieved: due to the complexity of the dynamic scene, the judgment model can be established and trained in advance based on big data and machine learning, so that the online calculation process can be simplified, and the system processing delay is reduced.

Optionally, the method comprises the steps of: establishing a multidimensional matrix of the event, the at least one vehicle component, the operating mode of the at least one vehicle component and/or at least one characteristic parameter of the operating mode, displaying in the multidimensional matrix an association of the event with the at least one vehicle component.

Thereby, the following technical advantages are achieved: by establishing the matrix, associations can be established and visualized between a plurality of restriction factors influencing the operation of the vehicle component, so that the adjustment rule of the operation mode of the vehicle component can be systematically observed or analyzed.

According to a second aspect of the invention, there is provided an apparatus for vehicle energy management for performing a method according to the first aspect of the invention, the apparatus comprising:

an acquisition module configured to be able to acquire events potentially affecting the automatic driving functions and/or driving assistance functions of the vehicle;

an evaluation module configured to evaluate the event in relation to at least one vehicle component for an automatic driving function and/or a driving assistance function; and

a determination module configured to be able to determine an operating mode of a vehicle component and at least one characteristic parameter of the operating mode depending on the correlation, to operate the vehicle component in the operating mode with the characteristic parameter.

According to a third aspect of the present invention, there is provided a computer program product, wherein the computer program product comprises a computer program for implementing the method according to the first aspect of the present invention when executed by a computer.

Drawings

The principles, features and advantages of the present invention may be better understood by describing the invention in more detail below with reference to the accompanying drawings. The drawings comprise:

FIG. 1 shows a block diagram of an apparatus for vehicle energy management according to an exemplary embodiment of the present invention;

FIG. 2 shows a flow diagram of a method for vehicle energy management according to an exemplary embodiment of the present invention;

FIG. 3 shows a flow chart for using the method according to the invention in an exemplary application scenario;

FIG. 4 shows a flow chart for using the method according to the invention in another exemplary application scenario; and

fig. 5 shows a flow chart for using the method according to the invention in another exemplary application scenario.

Detailed Description

In order to make the technical problems, technical solutions and advantageous effects of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings and exemplary embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of the invention.

Fig. 1 shows a block diagram of an arrangement for vehicle energy management according to an exemplary embodiment of the present invention.

As shown in fig. 1, the apparatus 1 is arranged, for example, in a vehicle 2 having an automatic driving function/driving assistance function. Furthermore, the following vehicle components are also shown in the vehicle 1: vehicle-mounted camera 110, vehicle-mounted antenna 120, vehicle battery unit 130, radar sensor 140, ultrasonic sensor 150, and high-precision positioning module 160.

In order to implement intelligent vehicle energy management, the device 1 comprises an acquisition module 10, an evaluation module 20 and a determination module 30. The acquisition module 10 is designed, for example, as a communication interface and is connected to the vehicle camera 110 in order to acquire traffic events detected in real time by means of the vehicle camera 110. The acquisition module 10 is also connected to a vehicle-mounted antenna 120 in order to acquire, for example, position information. The obtaining module 10 is further connected to the cloud platform 200, so that event information can be obtained from other vehicles, road side units, data platforms and the like by means of the real-time communication capability of the intelligent networked vehicle. Furthermore, the acquisition module 10 is also connected to the vehicle battery unit 130, so that a state event (e.g., battery remaining amount) of the vehicle itself can be acquired.

After the corresponding event information is acquired, the acquisition module 10 transmits the information to the calculation module 20. The determination module 20 is used, for example, to determine an association of the respective event with at least one vehicle component for the automatic driving function and/or the driving assistance function. The obtaining module 20 stores, for example, the relevance between the vehicle component and the event under different events, and the obtaining module 20 is further connected to the cloud platform 200, so that after the event is received, the obtaining module 20 can retrieve the relevance bound and stored with the corresponding event from the cloud platform 200, and meanwhile, the relevance and the corresponding operation mode stored in the obtaining module 20 can be updated from the cloud platform 200.

The evaluation module 20 provides the evaluated relevance to the determination module 30. In the determination module 30, the operating mode of the vehicle component and at least one characteristic variable of the operating mode of the vehicle component are determined as a function of the ascertained correlation. The determination module 30 is also connected to a plurality of

vehicle components

110, 140, 150, 160 in order to be able to send control signals to these

vehicle components

110, 140, 150, 160, so that these

vehicle components

110, 140, 150, 160 can be operated in an operating mode with characteristic parameters. For example, whether to start the high-precision positioning module 160 and thus enable the system to enter a ready state is determined by acquiring the vehicle surrounding event, for example, the high-precision positioning module 160 is started to enable a map real-time verification function. For another example, whether to turn on the in-vehicle camera 110 may be decided by the acquisition of weather conditions and thus the dynamic object type recognition function is enhanced.

It will be appreciated that fig. 1 is only an exemplary block diagram according to the present invention and that further sensors, actuators, modules related to the driving assistance function/automatic driving function are not shown, such as lidar, domain controllers, etc.

FIG. 2 shows a flow diagram of a method for vehicle energy management according to an exemplary embodiment of the present invention.

An initialization procedure is performed in optional step S0. Here, for example, the associations with different events can be assigned to all vehicle components in advance, while the operating mode of each vehicle component is prestored in a defined association. This can be achieved, for example, by means of manual labeling, but it is also possible to create and train a machine learning model in advance from the big data, with the aid of which the relevance of the vehicle components at the respective event can be estimated.

In step S1, an event that potentially affects the automatic driving function/driving assistance function of the vehicle is acquired.

In the sense of the present invention, an event is understood to be information which is obtained via different channels and has different timeliness and which influences the vehicle function class and/or the vehicle function strategy. Different types of events and their description and/or acquisition channels and examples of the events are illustrated in table 1.

TABLE 1

In step S2, the event is correlated with at least one vehicle component for the automatic driving function and/or the driving assistance function.

Relevance in the sense of the present invention is understood, for example, as: the functional effectiveness of the support of the vehicle component is influenced by the magnitude of the specific event or the magnitude of the operational necessity of the vehicle component in the event of the specific event. By way of example, "strongly associated" means that the vehicle component is necessarily in an on state in the event of a particular event, or that the particular event has a minor effect on the effectiveness of the functionality supported by the vehicle component. "weakly associated" means that the vehicle component does not have to remain on in the event of a particular event, or that the particular event has a greater effect on the functional effectiveness of the vehicle component.

In step S3, the operation mode of the vehicle component and the characteristic parameter of the operation mode are determined according to the correlation, and the vehicle component is operated in the operation mode having the characteristic parameter.

Here, the vehicle component may be selectively placed in a normal operation mode, a standby mode, a sleep mode, or a power-down mode depending on the magnitude of the operational necessity for the vehicle component upon occurrence of a specific event. It is conceivable that such an operating requirement can be quantitatively expressed by a numerical value, for example, such that the energy consumption of the selected operating mode decreases as the operating requirement of the vehicle component and/or the wake-up speed requirement decreases. Upon determining that the vehicle component has no operational necessity at all or only an extremely low operational necessity at a particular event, the vehicle component is placed in a power-down mode.

In this case, for example, the duration of the operating mode of the vehicle component, the activation time of the operating mode, the deactivation time of the operating mode, the waiting time and/or the waiting distance before activation of the operating mode are also determined as a function of the extent of influence of the event on the vehicle component. By way of example, knowing these characteristic parameters can cause vehicle components to enter sleep mode in advance before becoming completely unusable due to exposure to events, and make adjustments to vehicle functionality strategies in advance. As another example, the vehicle arrives at a design operation domain for a specific driving function, however, from the view point of historical driving data, the driver does not like to turn on the driving function on the road section, and thus does not turn on all sensors, or puts the sensors into a standby mode instead of an on mode for the road section range; or for some vehicles with the domain controller electronic and electric appliance architecture powered on, namely with the loss of the service life of the domain controller, the sensors, the actuators and the domain controllers related to the functions are put into a power-down mode for the range of the road section when the driver starts the road section with the extremely low probability of the functions.

Fig. 3 shows a flow chart of the use of the method according to the invention in an exemplary application scenario. In this exemplary application scenario, it is introduced how to intelligently adjust the overall energy deployment of the vehicle for an intra-plan event. An intra-plan event, in the sense of the present invention, represents a conditional limit defined by a supplier or a government-related functional group to turn on a specific automatic driving function/driving assistance function. For example, in the unstable positioning signal areas such as road structures, bridge openings, viaducts, tunnels, overpasses, underground parking lots and the like, the unstable positioning signal may cause the initial absolute positioning information of the vehicle to be inaccurate, thereby affecting the relative positioning result of the vehicle with respect to the map carried, and therefore, the starting condition of the specific automatic driving function is not satisfied in these areas.

In step 301, it is known, for example, by means of vehicle-mounted sensors or based on V2X technology: the vehicle is about to drive into the tunnel.

In step 302, the relevance of each sensor/actuator onboard the vehicle to this expected event is determined. Here, the respective association of the respective vehicle component can be retrieved from the predefined information, for example by accessing a local or cloud database.

In step 303, the operating mode of each sensor/actuator may be determined based on the correlation.

In step 304, the "standby range" of the weakly associated sensor/actuator is determined. The association of the various expected events with the sensors/actuators and the extent/duration of the influence are shown in table 2 by way of example.

TABLE 2

Here, the symbol √ denotes "weakly associated" sensors/actuators, which should be placed in a standby mode. The symbol x indicates "strong association" and therefore does not change the operating mode, which the sensors/actuators should remain in.

In step 305, the weakly associated sensor/actuator is placed in a standby mode according to a "standby range". As can be seen, for example, from table 2, in the event of the expected event "tunnel", the association of the first camera of the vehicle with the event is weakly associated, and therefore the first camera should switch from the on mode into the standby mode. Here, the standby range (d ═ 200m) indicates: and under the condition that the distance from the vehicle to the tunnel is 200m, the first camera enters a standby mode. (d, d _ lat) refers to a rectangular geofenced area with sides of d and d _ lat, respectively; (r) refers to a circular geofenced area of radius r meters.

In step 306, it is determined whether the expected event is resolved. Here, for example, it is determined whether the onboard GNSS continuously receives a stable positioning signal. Based on a further system strategy, it is also possible, for example, to recognize in a fused manner by means of a camera and a lidar whether the vehicle has already exited the tunnel.

If this is the case, it is an indication that the expected event has resolved, i.e., that the respective vehicle component has left the area of influence of the tunnel. The weakly associated sensor/actuator may then be turned back on in step 308.

If this is not the case, it indicates that the expected event has not resolved. The weakly associated sensor/actuator may therefore continue to remain in the standby mode in step 307.

Fig. 4 shows a flow chart of the use of the method according to the invention in another exemplary application scenario. In this exemplary application scenario, it is presented how to intelligently adjust the overall energy deployment of a vehicle based on vehicle state events.

In step 401, the remaining battery level of the vehicle battery unit is monitored to be 12% during the running of the vehicle.

In step 402, the predicted range of the vehicle with different numbers/classes of sensors/actuators on is determined. The results of the determination are shown in table 3, for example.

TABLE 3

Here, the function a represents, for example, an automatic driving function requiring a large part of sensor/actuator cooperation. Function B represents, for example, a driving assistance function requiring a small number of sensor/actuator combinations. The full manual driving mode indicates that the driving task is performed entirely by the driver.

In step 403, the operating mode of each sensor/actuator is selected based on the predicted range. Here, based on the existing route planning information, for example, it is determined that the battery remaining capacity is insufficient to travel to the destination in function a and function B is selected.

In step 404, the operating mode switching timing for each sensor/actuator is further selected in conjunction with the predicted range. For example, the turn-off sequence of the sensors is determined according to the expected variation trend of the electric quantity.

In step 405, after the driver is given sufficient reaction time and the driver corresponding action is detected, the partial sensor/actuator is gradually and stepwise waited/dormant in accordance with the determined switching timing.

In step 406, it is determined whether the availability of the particular drive assist function after the standby/sleep portion sensor/actuator is below a threshold.

If the threshold is lower, it means that the remaining sensors/actuators are insufficient to support the normal execution of the driving assistance function. The system may then be degraded or alternate low energy vehicle components activated in step 408 to ensure that the vehicle travels to the destination with as little safety and user experience as possible.

If so, the driving assistance function may continue to be performed with the remaining vehicle components in the normal operating mode in step 407.

Fig. 5 shows a flow chart for using the method according to the invention in another exemplary application scenario. In this exemplary application scenario, it is presented how to intelligently adjust the overall energy deployment of a vehicle based on vehicle state events.

In step 501, when it is monitored that a function is activated during the running of the vehicle, the signal of the sensor a is unstable.

In step 502, it is determined that the a sensor may be malfunctioning and thus its operation in the current situation is less necessary.

In step 503, the functional link M that is dominated by the sensor A signal is switched to the functional link N that is not dominated by the sensor A. From the perspective of an energy strategy, the sensor/actuator of the functional chain M is uniquely dormant, and the vehicle is electrified for self-checking after the vehicle is static.

In step 504, the sensor a on-going time is determined based on the signal quality (signal instability level) of sensor a.

In step 505, instead of immediately standing by or sleeping sensor a, sensor a is kept on for a period of time so that a corresponding fault code can be recorded.

Although specific embodiments of the invention have been described herein in detail, they have been presented for purposes of illustration only and are not to be construed as limiting the scope of the invention. Various substitutions, alterations, and modifications may be devised without departing from the spirit and scope of the present invention.

Claims

1. A method for vehicle energy management, the method comprising the steps of:

2. The method of claim 1, wherein determining at least one characteristic parameter of an operating mode of a vehicle component from the correlation comprises:

determining the duration of the operating mode of the vehicle component, the activation time of the operating mode, the deactivation time of the operating mode, the waiting time and/or the waiting distance before the operating mode is activated according to the influence range of the event on the vehicle component.

3. The method of claim 1 or 2, wherein determining the operating mode of the vehicle component from the correlation comprises:

4. A method according to claim 3, wherein in the event of switching a vehicle component from a first operating mode to a second operating mode, a replacement vehicle component is placed in the first operating mode depending on the availability of the autonomous driving function and/or the driving assistance function supported by the vehicle component.

5. The method according to claim 3 or 4, wherein the method further comprises the steps of:

acquiring the state change of the event along with the time;

6. A method according to any of claims 3 to 5, wherein a second operating mode of a vehicle component is selected when the event is indicative of at least any of:

7. Method according to one of claims 1 to 6, wherein at least one vehicle component is assigned an association with different events in an initialization phase, the operating mode of the vehicle component is stored in a bound manner for a predetermined association, and the corresponding operating mode is called up in step S3 as a function of the ascertained association.

8. The method according to any one of claims 1 to 7, wherein the method comprises the steps of:

establishing a multidimensional matrix of the event, the at least one vehicle component, the operating mode of the at least one vehicle component and/or at least one characteristic parameter of the operating mode, displaying in the multidimensional matrix an association of the event with the at least one vehicle component.

9. A device (1) for energy management of a vehicle, the device (1) being configured to perform the method according to any one of claims 1 to 8, the device (1) comprising:

an acquisition module (10) configured to enable acquisition of events potentially affecting the automatic driving functions and/or driving assistance functions of the vehicle;

an evaluation module (20) which is configured to evaluate the association of the event with at least one vehicle component for an automatic driving function and/or a driving assistance function; and

a determination module (30) configured to determine an operating mode of a vehicle component and at least one characteristic parameter of the operating mode depending on the correlation, to operate the vehicle component in the operating mode with the characteristic parameter.

10. A computer program product, wherein the computer program product comprises a computer program for implementing the method according to any one of claims 1 to 8 when executed by a computer.