Energy recovery method, device and vehicle

Abstract

The present application is applicable to the field of automotive technologies, and provides an energy recovery method, apparatus and vehicle. The method includes: obtaining a first recovery torque, where the first recovery torque is the maximum energy recovery torque for enabling a specified vehicle to operate stably under the constraint of environmental prediction information; modifying the first recovery torque under the constraint of environmental acquisition information to obtain a second recovery torque; and controlling the specified vehicle to perform energy recovery according to the second recovery torque. The energy recovery control based on the second recovery torque in the present application can overcome the reliability problem and efficiency problem existing in the prior art, that is, the control of energy recovery can be achieved without touching the ESC, and the efficiency and safety of energy recovery can be ensured without disabling the energy recovery system.

Description

Technical Field

[0001] This application belongs to the technical field of automobiles, and particularly relates to an energy recovery method, device, and automobile. Background Art

[0002] There are two ways for a vehicle to decelerate, namely reducing power input (such as releasing or lightening the accelerator / throttle pedal) to decelerate through environmental resistance and introducing an external force opposite to the forward direction (such as stepping on or increasing the brake pedal) to decelerate.

[0003] Generally speaking, vehicle deceleration is in response to the driver's actions. For some vehicles with energy recovery functions, there may be an acceleration generated by the intervention of the energy recovery system that cannot be precisely controlled by the driver. This acceleration may cause the vehicle to lose stability and even cause an accident in a specific environment.

[0004] To avoid the situation where energy recovery causes the vehicle to lose stability, an optional solution is to combine energy recovery with ESC (Electronic Stability Controller). That is, when energy recovery causes the vehicle to lose stability and ESC is triggered, the energy recovery system is prohibited from working to ensure safety.

[0005] However, a similar method still objectively causes the vehicle to lose stability (that is, after ESC intervenes and the vehicle has already lost stability, energy recovery stops). Subsequently, during the period when the energy recovery system is disabled, the vehicle may have left the dangerous section where it is prone to instability and entered a safe section (that is, a section where the energy recovery system can operate safely), but the prior art still prohibits energy recovery, which will result in the loss of some recoverable energy and insufficient energy recovery efficiency.

[0006] Therefore, how to provide a more reliable and efficient energy recovery method, device, and automobile has become a technical problem that needs to be solved urgently in the industry. Summary of the Invention

[0007] The embodiments of this application provide an energy recovery method, device, and automobile, which can solve the problems of insufficient reliability and efficiency of the existing energy recovery solutions.

[0008] In a first aspect, the embodiments of this application provide an energy recovery method, including:

[0009] Obtaining a first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque that specifies the stable operation of the vehicle under the constraint of environmental prediction information;

[0010] Modifying the first recovery torque under the constraint of environmental acquisition information to obtain a second recovery torque;

[0011] Control the specified vehicle to perform energy recovery according to the second recovery torque.

[0012] The above method predicts in advance the first recovery torque as the torque reference value for energy recovery based on the environmental prediction information. As the first recovery torque is based on prediction information, the real-time requirement is relatively low, and it can be predicted within a more ample time period, so that a more accurate first recovery torque can be obtained at the cost of consuming more computing resources and time. Further, based on this relatively accurate predicted value of the first recovery torque, the deviation of the first recovery torque caused by the deviation of the environmental prediction information is corrected through the environmental acquisition information. By using the first recovery torque as the reference value, the calculation can be completed with less consumption of computing resources and less time, and a more accurate second recovery torque corrected by the environmental acquisition information can be obtained to control the energy recovery of the vehicle. The energy recovery control based on the second recovery torque can overcome the efficiency problems existing in the prior art, that is, the control of energy recovery can be realized without touching the ESC, and the efficiency and safety of energy recovery can be ensured without disabling the energy recovery system.

[0013] In a possible implementation manner of the first aspect, the step of controlling the specified vehicle to perform energy recovery according to the second recovery torque includes:

[0014] Obtain the historical recovery torque under the environmental acquisition information;

[0015] Use the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque, and control the specified vehicle to perform energy recovery.

[0016] The above method further restricts the second recovery torque through the vehicle historical data. On the one hand, it provides a redundant space for vehicle operation safety, and on the other hand, it also realizes the "one-size-fits-one" energy recovery control based on the vehicle historical control data, improving the driving consistency of the driver and enhancing the vehicle user experience.

[0017] In a possible implementation manner of the first aspect, the step of obtaining the first recovery torque includes:

[0018] Construct a prediction scenario and a prediction path according to the environmental prediction information; the prediction scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter; the prediction path is the path within the prediction scenario;

[0019] Calculate the slip ratio and the tire side slip angle when the specified vehicle running on the prediction path performs energy recovery with a prediction torque;

[0020] Update the predicted torque, and return the step of calculating the slip ratio and the tire sideslip angle when the specified vehicle running on the predicted path performs energy recovery with the predicted torque, until the maximum predicted torque that satisfies the preset slip ratio condition and the tire sideslip angle condition is obtained as the first recovery torque.

[0021] The above method constructs a prediction scenario and a prediction path through environmental prediction information, and judges whether there is a preset vehicle instability risk for the specified vehicle running on the prediction path, that is, the judgment process based on the slip ratio condition and the tire sideslip angle condition, combined with the update and iteration of the predicted torque, to obtain the first recovery torque. This method can obtain a more realistic simulation result under the environmental prediction conditions through multiple verifications in the predicted environment, so as to obtain a more accurate first recovery torque, providing a good basis for subsequent energy recovery control.

[0022] In a possible implementation manner of the first aspect, the step of updating the predicted torque includes:

[0023] If it is determined that under the predicted torque, the slip ratio satisfies the preset slip ratio condition and the tire sideslip angle satisfies the preset tire sideslip angle condition, then update the predicted torque to a torque value with a larger absolute value;

[0024] If it is determined that under the predicted torque, the slip ratio does not satisfy the preset slip ratio condition, or the tire sideslip angle does not satisfy the preset tire sideslip angle condition, then update the predicted torque to a torque value with a smaller absolute value.

[0025] The above method introduces an iterative optimization scheme. For the predicted torque that satisfies the slip ratio condition and the tire sideslip angle condition, increase its absolute value for iteration to obtain a more extreme (under the premise of vehicle stability) upper limit of the energy recovery torque; for the predicted torque that does not satisfy the slip ratio condition and the tire sideslip angle condition, reduce its absolute value for iteration to obtain the energy recovery torque that can make the vehicle run stably, so as to more efficiently approach the actual value of the first recovery torque.

[0026] In a possible implementation manner of the first aspect, the step of correcting the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque includes:

[0027] Construct an operation scenario and an operation path according to the environmental acquisition information; the operation scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter; the operation path is the path within the operation scenario;

[0028] Calculate the slip ratio and the tire sideslip angle when the specified vehicle running on the operation path performs energy recovery with the first recovery torque;

[0029] If the slip ratio satisfies a preset slip ratio condition and the tire sideslip angle satisfies a preset tire sideslip angle condition, output the second recovery torque; the value of the second recovery torque is the same as that of the first recovery torque.

[0030] If the slip ratio does not satisfy the preset slip ratio condition or the tire sideslip angle does not satisfy the preset tire sideslip angle condition, output the second recovery torque; the absolute value of the second recovery torque is less than that of the first recovery torque.

[0031] The above method constructs an operating scenario and an operating path through environmental acquisition information, and obtains the second recovery torque through the process of judging whether there is a preset vehicle instability risk for a specified vehicle running on the operating path, that is, the judgment process based on the slip ratio condition and the tire sideslip angle condition, in cooperation with the correction and update of the first recovery torque. This method can correct the first recovery torque through the acquired environmental information to obtain a more real result and a more accurate second recovery torque, and thus more effectively realize the energy recovery control of the vehicle.

[0032] In a possible implementation manner of the first aspect, the step of correcting the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque includes:

[0033] Construct an operating scenario and an operating path according to the environmental acquisition information; the operating scenario includes at least one of temperature distribution parameters, humidity distribution parameters, rainfall distribution parameters, and road condition parameters.

[0034] Obtain historical environmental parameters matching the environmental acquisition information, and construct a motion speed function according to the historical operating parameters of the specified vehicle under the historical environmental parameters.

[0035] Taking the operating scenario, the operating path, and the motion speed function as constraints, correct the first recovery torque to obtain the second recovery torque.

[0036] The above method introduces a motion speed function on the basis of historical data, corrects the first recovery torque on the basis of considering the variable of the vehicle's motion speed to obtain the vehicle control habits of the driver at a specific speed, and adjusts the control of energy recovery accordingly, so as to make the driver experience more consistent and achieve the effect of "one size fits one person".

[0037] In a possible implementation manner of the first aspect, the step of obtaining the historical recovery torque under the environmental acquisition information includes:

[0038] Calculate the road adhesion coefficient according to the environmental acquisition information.

[0039] Obtain the historical adhesion coefficient consistent with the road surface adhesion coefficient in the historical operation data of the specified vehicle, and the historical recovery torque corresponding to the historical adhesion coefficient.

[0040] The above method matches the historical operation data of the specified vehicle based on the road surface adhesion coefficient, providing a good basis for the recovery torque calibration when the historical database is insufficient.

[0041] In a possible implementation manner of the first aspect, the step of obtaining the first recovery torque includes:

[0042] Using the environmental prediction information as input, run the first model to obtain the first recovery torque; wherein, the first model is a model that calculates the maximum energy recovery torque for the stable operation of the specified vehicle under the constraint of the environmental prediction information.

[0043] The above method makes the calculation process of the first recovery torque black-box by introducing the first model. At the same time, the programmed operation of the first recovery torque through the first model is beneficial to improving the efficiency and stability of the energy recovery calculation process.

[0044] In a possible implementation manner of the first aspect, the first model includes a first virtual vehicle; the first virtual vehicle is simulated based on the power parameters, steering parameters, and braking parameters of the specified vehicle.

[0045] The above method uses the first virtual vehicle as the basis of the first model, providing a reliable basis for the calculation of the first recovery torque based on the environmental prediction information, making the first recovery torque more in line with the actual situation as a prediction result, and reducing the computing resources required by the second model.

[0046] In a possible implementation manner of the first aspect, the step of correcting the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque includes:

[0047] Using the first recovery torque and the environmental acquisition information as input, run the second model to obtain the second recovery torque; wherein, the second model is used to correct the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque.

[0048] The above method makes the calculation process of the second recovery torque black-box by introducing the second model. At the same time, the programmed operation of the second recovery torque through the second model is beneficial to improving the efficiency and stability of the energy recovery calculation process.

[0049] In a possible implementation manner of the first aspect, the second model includes a second virtual vehicle; the second virtual vehicle is simulated based on the power parameters, steering parameters, and braking parameters of the specified vehicle.

[0050] The above method uses the second virtual vehicle as the basis of the second model, providing a reliable basis for calculating the second recovery torque based on the environment acquisition information, that is, correcting the first recovery torque, making the second recovery torque more in line with the actual situation, and thus more effectively realizing the energy recovery control of the vehicle.

[0051] In a possible implementation manner of the first aspect, the step of controlling the specified vehicle to perform energy recovery according to the second recovery torque includes:

[0052] Invoking a third model according to the environment acquisition information to obtain the historical recovery torque under the environment acquisition information;

[0053] Taking the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque, and controlling the specified vehicle to perform energy recovery;

[0054] Wherein, the third model includes the historical environment parameters and historical operation parameters of the specified vehicle.

[0055] The above method records the vehicle historical data through the third model, and makes the acquisition process of the historical recovery torque programmed by the way of invoking the model, which is beneficial to improving the efficiency and stability of the energy recovery calculation process.

[0056] In a second aspect, an embodiment of the present application provides an energy recovery device, including:

[0057] A first recovery torque module, configured to obtain a first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque for the specified vehicle to operate stably under the constraint of environment prediction information;

[0058] A second recovery torque module, configured to correct the first recovery torque under the constraint of environment acquisition information to obtain a second recovery torque;

[0059] A recovery module, configured to control the specified vehicle to perform energy recovery according to the second recovery torque.

[0060] In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where when the processor executes the computer program, the energy recovery method described in any item of the first aspect above is implemented.

[0061] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the energy recovery method described in any item of the first aspect above is implemented.

[0062] Fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product runs on a terminal device, the terminal device is caused to execute the energy recovery method described in any one of the above first aspects.

[0063] Sixth aspect, an embodiment of the present application provides a vehicle, including the above energy recovery device or the above terminal device.

[0064] It can be understood that the beneficial effects of the above second to sixth aspects can be referred to the relevant descriptions in the above first aspect, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0066] Figure 1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0067] Figure 2 is a schematic flowchart of the energy recovery method provided by an embodiment of the present application;

[0068] Figure 3 is an application diagram of the energy recovery method based on digital twin provided by an embodiment of the present application;

[0069] Figure 4 is a logical diagram of the energy recovery method based on digital twin provided by an embodiment of the present application;

[0070] Figure 5 is a schematic structural diagram of the energy recovery device provided by an embodiment of the present application;

[0071] Figure 6 is a schematic structural diagram of the terminal device provided by an embodiment of the present application;

[0072] Reference Signs:

[0073] Vehicle 100;

[0074] Vehicle machine processor 101;

[0075] Vehicle machine storage unit 1011;

[0076] First virtual vehicle 1012;

[0077] Second virtual vehicle 1013;

[0078] Environment prediction module 102;

[0079] Sensor 103;

[0080] First recovery torque module 501;

[0081] Second recovery torque module 502;

[0082] Recovery module 503;

[0083] Terminal device 60;

[0084] Processor 601;

[0085] Memory 602;

[0086] Computer program 603. Detailed implementation manners

[0087] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system architectures, technologies, etc. are presented in order to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0088] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0089] It should also be understood that the term "and / or" as used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0090] As used in the specification of the present application and the appended claims, the term "if" can be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" according to the context. Similarly, the phrase "if determined" or "if detecting [the described condition or event]" can be interpreted as meaning "once determined" or "in response to determining" or "once detecting [the described condition or event]" or "in response to detecting [the described condition or event]" according to the context.

[0091] In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0092] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that specific features, structures, or characteristics described in connection with that embodiment are included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but rather mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0093] If the kinetic energy reduced during the vehicle deceleration process can be recycled through certain means, at least a part of the vehicle's energy will be recycled, thereby improving the energy consumption problem of the vehicle, especially new energy vehicles (here new energy vehicles include pure electric vehicles and hybrid energy vehicles such as plug-in hybrid vehicles).

[0094] Different from the vehicle braking force brought about by the driver adjusting the brake pedal, when the energy recovery system intervenes and works, the braking force generated by the vehicle cannot be accurately adjusted in real time by the driver.

[0095] During the actual operation of the vehicle, there is a certain physical limit to the friction force between the vehicle and the ground. And the friction force, as an important parameter for the control of the vehicle 100, affects all aspects of vehicle control. For example, when the vehicle has a large positive or negative acceleration (for example, when the accelerator / throttle / brake pedal is depressed), if the vehicle is simultaneously controlled to turn at a certain speed (that is, in addition to the acceleration in the forward direction / tangential direction of the vehicle, a radial acceleration for turning is simultaneously generated), the sum of the friction force required for the tangential acceleration and the friction force required for the radial acceleration may exceed the upper limit of the friction force between the vehicle and the ground, thereby causing the vehicle to lose control (push head / fishtail / slip, etc.), and even causing an accident.

[0096] As described above regarding the friction force, the essential reason for the instability of some vehicles lies in insufficient friction force. And the driver can at least control the radial acceleration of the vehicle (that is, the turning amplitude controlled by the steering wheel) and the tangential acceleration brought about by the accelerator / throttle / brake pedal, so as to avoid the vehicle from losing control. That is to say, when the energy recovery system is not considered, the relevant control authorities of the vehicle acceleration and friction force are all completed by the driver in cooperation with the assisted driving system.

[0097] However, after the introduction of the energy recovery system, there may be some additional braking forces generated by energy recovery that are not controlled by the driver, thereby reducing the driver's error tolerance space and increasing the probability of accidents.

[0098] Therefore, although the energy recovery system can recycle some of the vehicle's energy to reduce the overall energy consumption of the vehicle 100, there is still a risk of increasing the accident probability.

[0099] The inventors found that the above problems can be summarized as the same reason, that is, the control of the energy recovery torque is not accurate enough. It can be understood that it is precisely because the prior art ignores this reason that the above problems are caused.

[0100] Furthermore, the inventors considered that if the energy recovery torque can be used as a controllable variable, so that the intensity of energy recovery changes with the environment and road conditions, a higher energy recovery intensity is adopted when the vehicle handling margin (in some cases, it can be understood as the available margin of the friction between the vehicle and the ground) is relatively sufficient to achieve more efficient energy recovery, and when the vehicle handling margin is insufficient, a lower energy recovery intensity (or temporarily prohibit energy recovery until the vehicle handling margin is sufficient) is adopted to ensure the safety of vehicle driving.

[0101] Through such a solution, the problems mentioned in the above prior art can be avoided, and the efficiency of the vehicle energy recovery process can be improved.

[0102] To implement the above control solution, it is necessary to monitor the state during the vehicle operation, calculate the maximum allowable energy recovery torque of the vehicle based on the state monitoring parameters, and further control the intensity of energy recovery.

[0103] However, when simply controlling the energy recovery intensity through the above solution, there are still problems of insufficient computing resources and / or long computing time, which in turn lead to tight computing resources of the vehicle (especially intelligent vehicles), or a relatively high delay in the control of the energy recovery intensity.

[0104] To further solve these problems, Figure 1 A feasible application solution is shown, that is, the environment prediction module 102 (such as the weather forecast APP in the cloud, the map / navigation APP, etc.) is communicatively connected to the in-vehicle processor 101 inside the vehicle 100, the environment prediction information is obtained through the environment prediction module 102, and a predictive energy recovery intensity operation (the first recovery torque) is further performed based on the environment prediction information. Since this part of the prediction is of a predictive nature, it can take a relatively long time (referring to a longer time compared to the subsequent operation time based on the environment acquisition information, rather than the absolute length of time being long) to obtain a more accurate result. Subsequently, based on the predictive energy recovery intensity operation, the environment acquisition information collected by the sensor 103 is used as a constraint to adjust and calculate the energy recovery intensity for actual control (the second recovery torque), thereby reducing the operation time from the environment acquisition information to the second recovery torque.

[0105] That is to say, the embodiment of the present application provides an energy recovery method, as Figure 2 shown, including:

[0106] Step 202, obtain the first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque for ensuring the stable operation of a specified vehicle under the constraint of environmental prediction information;

[0107] Step 204, correct the first recovery torque under the constraint of environmental acquisition information to obtain the second recovery torque;

[0108] Step 206, control the specified vehicle to perform energy recovery according to the second recovery torque.

[0109] An optional execution entity of this embodiment is the in-vehicle processor 101 of the vehicle.

[0110] The environmental prediction information can be obtained either through the weather forecast APP, map / navigation APP, etc. installed in the in-vehicle unit, or through the environmental prediction module 102 shown as Figure 1 installed in the cloud and communicating with the in-vehicle unit.

[0111] The environmental acquisition information can be obtained through the sensor 103 installed on the vehicle.

[0112] In this embodiment, the types of environmental prediction information and environmental acquisition information can be the same. For example, both include temperature, humidity, rainfall, road vehicle density, etc.; or they can be different. For example, the environmental prediction information includes weather forecast information and map information, and the environmental acquisition information includes temperature, humidity, rainfall, road vehicle density, information collected by the visual sensor 103 (such as a camera), information collected by lidar / millimeter wave radar, etc.

[0113] In an optional implementation manner, the calculation process of the first recovery torque and the process of correcting to obtain the second recovery torque can be implemented in the following manner:

[0114] Calculate the vehicle's handling margin according to the environmental prediction information or environmental acquisition information (for example, using the friction between the vehicle and the ground as a key parameter, and taking the difference between the upper limit of friction and the used friction as a quantitative index of the handling margin);

[0115] Adjust the verification value of the first recovery torque or the second recovery torque, and pay attention to the change of the handling margin until the actual value of the first recovery torque or the second recovery torque is determined, and this actual value can ensure that there is enough handling margin reserved.

[0116] The beneficial effects of this embodiment are as follows:

[0117] Based on the environmental prediction information, the first recovery torque is predicted in advance as the torque reference value for energy recovery. As the first recovery torque is based on the prediction information, the real-time requirement is low and it can be predicted in a more ample time period, so that a more accurate first recovery torque can be obtained at the premise of consuming more computing resources and time. Furthermore, based on the relatively accurate prediction value of the first recovery torque, the deviation of the first recovery torque caused by the deviation of the environmental prediction information is corrected by the environmental collection information. By using the first recovery torque as a reference value, the calculation can be completed with less computing resource consumption and less time, and a more accurate second recovery torque can be obtained under the correction of the environmental collection information to control the energy recovery of the vehicle. The energy recovery control based on the second recovery torque can overcome the efficiency problem existing in the prior art, that is, the energy recovery control can be realized without touching the ESC, and the efficiency and safety of energy recovery can be guaranteed without disabling the energy recovery system.

[0118] Based on the above embodiments, the prior art still has the following problems.

[0119] Due to the unavoidable problem brought about by the energy recovery mechanism, the braking force generated by energy recovery is not under the driver's control, which will have a significant impact on the driver's driving experience. Therefore, from the perspective of vehicle driving experience, the above solution still has room for optimization.

[0120] Therefore, in yet another embodiment:

[0121] The step of designating the vehicle to perform energy recovery according to the second recovery torque control includes:

[0122] Get historical recovery torque under environmental collection information;

[0123] The smaller absolute value of the historical recovery torque and the second recovery torque is used as the upper limit of the absolute value of the energy recovery torque to control the designated vehicle to perform energy recovery.

[0124] In this embodiment, the historical recovery torque is obtained by matching based on the environmental collection information. That is to say, the historical time nodes with similar environment and road conditions to the collection time can be obtained through the environmental collection information, and the third model is called to query the historical operating parameters of the historical time nodes to obtain the historical recovery torque, so as to further regulate the energy recovery intensity.

[0125] It should be noted that the concept of historical recovery torque is not limited to the energy recovery torque at this historical time node. In some cases, it also includes the torque corresponding to the acceleration generated by the driver through the brake / throttle / throttle pedal to better adapt to the driver's driving habits (for example, in a rainy environment, some drivers tend to maintain a relatively low speed, then the historical recovery torque can record the braking torque generated by the driver due to environmental factors to cooperate with the second recovery torque to regulate energy recovery).

[0126] In an optional implementation manner, the specific implementation of the step of obtaining a historical time node similar to the environment and road conditions at the acquisition moment through environmental acquisition information can be based on the adhesion coefficient.

[0127] The purpose of this implementation manner is to provide a solution when the driver's historical driving data is insufficient, that is, when the amount of the driver's historical driving data is small, although the environmental acquisition information can be collected, the historical data that strictly corresponds to the environmental acquisition information (the deviation of information such as temperature, humidity, and rainfall is less than a preset threshold) may not exist.

[0128] At this time, the adhesion coefficient can be used as a correlation quantity. First, determine the adhesion coefficient of the road under the environmental acquisition information, and then call the third model to query the historical time node with a similar adhesion coefficient (the deviation of the adhesion coefficient is less than a preset threshold, but the information such as temperature, humidity, and rainfall may have a certain deviation), and consider the historical recovery torque of this historical time node to control the energy recovery intensity.

[0129] That is to say, in this implementation manner:

[0130] The steps of obtaining the historical recovery torque under the environmental acquisition information include:

[0131] Calculate the road surface adhesion coefficient according to the environmental acquisition information;

[0132] Obtain the historical adhesion coefficient consistent with the road surface adhesion coefficient in the historical operation data of the specified vehicle, and the historical recovery torque corresponding to the historical adhesion coefficient.

[0133] This implementation manner matches the historical operation data of the specified vehicle based on the road surface adhesion coefficient, providing a good basis for the calibration of the recovery torque when the historical database is insufficient.

[0134] Further, in some alternative embodiments, the second recovery torque is the maximum allowable energy recovery torque to ensure the stable operation of a specified vehicle. If the environmental parameters at the historical time node are exactly the same as the environmental acquisition information, excluding the case of driver's manual control, the historical recovery torque should be less than the second recovery torque. That is, in this case, the historical recovery torque is preferentially considered as the habit data of the vehicle driver. In some other cases, the environmental parameters at the historical time node do not exactly match the environmental acquisition information. Considering the differences between environmental parameters, there is a possibility that the historical recovery torque is greater than the second recovery torque. In this case, since the second recovery torque is already the maximum torque under the preset conditions, the second recovery torque should be preferentially considered as the torque upper limit for vehicle energy recovery.

[0135] The beneficial effects of this embodiment are as follows:

[0136] By further constraining the second recovery torque through vehicle historical data, on the one hand, it provides a redundant space for vehicle operation safety, and on the other hand, it realizes the "one-size-fits-one" energy recovery control based on vehicle historical control data, improves the driver's control consistency, and enhances the vehicle user experience.

[0137] According to any of the above embodiments, in another embodiment:

[0138] The steps of obtaining the first recovery torque include:

[0139] Construct a prediction scenario and a prediction path according to the environmental prediction information; the prediction scenario includes at least one of temperature distribution parameters, humidity distribution parameters, rainfall distribution parameters, and road condition parameters; the prediction path is a path within the prediction scenario;

[0140] Calculate the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with the prediction torque;

[0141] Update the prediction torque, and return to the step of calculating the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with the prediction torque until the maximum prediction torque with the slip ratio meeting the preset slip ratio condition and the tire sideslip angle meeting the preset tire sideslip angle condition is obtained as the first recovery torque.

[0142] Among them, the slip ratio meeting the preset slip ratio condition means that the slip ratios of all tires of the vehicle meet the slip ratio condition, and the tire sideslip angle meeting the preset tire sideslip angle condition means that the tire sideslip angles of all tires of the vehicle meet the slip ratio condition.

[0143] In an alternative embodiment, the steps of obtaining the first recovery torque include:

[0144] Taking the environmental prediction information as the input, run the first model to obtain the first recovery torque; wherein, the first model is a model for calculating the maximum energy recovery torque for the stable operation of a specified vehicle under the constraint of the environmental prediction information.

[0145] The first model includes a first virtual vehicle 1012; the first virtual vehicle 1012 is simulated based on the power parameters, steering parameters, and braking parameters of the specified vehicle.

[0146] The first virtual vehicle 1012 is a digital twin model constructed based on the actual parameters of the specified vehicle. In an optional embodiment, in addition to the power parameters, steering parameters, and braking parameters, the construction of the first virtual vehicle 1012 also considers the structural parameters of the specified vehicle. Specifically, the first virtual vehicle 1012, that is, the digital twin vehicle 100 model, is constructed based on the following table of parameters.

[0147]

[0148] This embodiment uses the first virtual vehicle 1012 as the basis of the first model, providing a reliable basis for calculating the first recovery torque based on the environmental prediction information, making the first recovery torque as a prediction result more in line with the actual situation, and reducing the computing resources required by the second model.

[0149] It is worth noting that, matching the specific algorithm, the environmental prediction information may include different specific information types. For example, in this embodiment, the environmental prediction information includes weather information and road information. Among them, the weather information may include temperature, humidity, rainfall (snowfall), etc.; the road information may include the predicted path, road type, congestion level, etc. The acquisition of the weather information can be achieved based on the weather forecast, and the acquisition of the road information can be achieved based on the in-vehicle navigation.

[0150] By combining the weather information with the road type information (such as asphalt roads like urban roads and closed elevated roads, gravel roads like rural roads, etc.), various parameters of the prediction scenario can be constructed, such as the road adhesion coefficient in the prediction scenario, etc., as the simulation operation environment of the first virtual vehicle 1012.

[0151] The predicted path can be obtained through the road information as the simulation operation path of the first virtual vehicle 1012.

[0152] Based on the prediction environment and prediction path, a predicted torque (which can be understood as the verification value of the first recovery torque) is applied to the first virtual vehicle 1012 in the running state, and the running state of the first virtual vehicle 1012 to which the predicted torque has been applied is monitored. Different from the example in the above embodiment regarding the road friction force as the quantization value of the handling margin, in this embodiment, the tire slip angle and slip ratio when the first virtual vehicle 1012 is running are concerned, and the tire slip angle condition and slip ratio condition are preset (for example, setting the tire slip angle threshold and slip ratio threshold). When calculating the tire slip angle and slip ratio parameters of the first virtual vehicle 1012 under this predicted torque, the predicted torque is then updated, and the above steps of calculating the tire slip angle and slip ratio parameters are repeatedly iterated, so as to obtain a series of predicted torque values and their corresponding tire slip angle and slip ratio parameters, and further obtain the maximum predicted torque value that simultaneously satisfies the tire slip angle condition and slip ratio condition as the first recovery torque.

[0153] It should be noted that the stop condition of the above iteration process is that the maximum predicted torque value that simultaneously satisfies the tire slip angle condition and slip ratio condition has been obtained as the first recovery torque. The iteration process can be understood as a process of approaching the finally obtained first recovery torque. In actual calculation, the update of the predicted torque can be set with a predetermined discrete interval, that is, the minimum interval between predicted torque values. Due to the existence of this discrete interval, assuming that there is a torque value that simultaneously satisfies the tire slip angle condition and slip ratio condition, and after increasing or decreasing a discrete interval based on this torque value, it does not simultaneously satisfy the tire slip angle condition and slip ratio condition, then this torque value can be considered as the maximum predicted torque value that simultaneously satisfies the tire slip angle condition and slip ratio condition.

[0154] The beneficial effect of this embodiment is as follows:

[0155] By constructing a prediction scenario and prediction path through environmental prediction information, through the judgment process of whether there is a preset vehicle instability risk for a specified vehicle running on the prediction path, that is, the judgment process based on the slip ratio condition and tire slip angle condition, and in cooperation with the update iteration of the predicted torque, the first recovery torque is obtained. This method can obtain a more realistic simulation result under the environmental prediction condition through multiple verifications in the prediction environment, so as to obtain a more accurate first recovery torque, providing a good basis for subsequent energy recovery control.

[0156] According to any of the above embodiments, in another embodiment:

[0157] The step of updating the predicted torque includes:

[0158] When the slip ratio meets the preset slip ratio condition and the tire sideslip angle meets the preset tire sideslip angle condition at the determined predicted torque, update the predicted torque to a torque value with a larger absolute value;

[0159] When the slip ratio does not meet the preset slip ratio condition or the tire sideslip angle does not meet the preset tire sideslip angle condition at the determined predicted torque, update the predicted torque to a torque value with a smaller absolute value.

[0160] According to the above description of friction, it can be seen that whether it is the acceleration in the forward direction of the vehicle 100 or the acceleration in the reverse direction of the forward direction of the vehicle 100, it may affect the vehicle's stability control. It can be understood that for energy recovery, the torque applied by it also has a similar effect. Therefore, in the step of updating the predicted torque, the difference in the absolute values of the torque values before and after the update is a relatively critical parameter.

[0161] The beneficial effect of this embodiment lies in:

[0162] By introducing an iterative optimization scheme, for the predicted torque that meets the slip ratio condition and the tire sideslip angle condition, increase its absolute value for iteration to obtain a more extreme upper limit of the energy recovery torque (on the premise that the vehicle remains stable); for the predicted torque that does not meet the slip ratio condition and the tire sideslip angle condition, reduce its absolute value for iteration to obtain the energy recovery torque that can make the vehicle run stably, so as to more efficiently approach the actual value of the first recovery torque.

[0163] According to any of the above embodiments, in another embodiment:

[0164] The steps of correcting the first recovery torque under the constraint of the environment acquisition information to obtain the second recovery torque include:

[0165] Construct an operating scenario and an operating path according to the environment acquisition information; the operating scenario includes at least one of temperature distribution parameters, humidity distribution parameters, rainfall distribution parameters, and road condition parameters; the operating path is the path within the operating scenario;

[0166] Calculate the slip ratio and the tire sideslip angle when a specified vehicle running on the operating path performs energy recovery with the first recovery torque;

[0167] If the slip ratio meets the preset slip ratio condition and the tire sideslip angle meets the preset tire sideslip angle condition, output the second recovery torque; the value of the second recovery torque is the same as that of the first recovery torque;

[0168] If the slip ratio does not meet the preset slip ratio condition or the tire sideslip angle does not meet the preset tire sideslip angle condition, output the second recovery torque; the absolute value of the second recovery torque is less than that of the first recovery torque.

[0169] Similar to the embodiment of obtaining the first recovery torque, in this embodiment, the process of correcting the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque can still construct the environment and the path. Different from the first recovery torque, since one of the input quantities of the second recovery torque is the environmental acquisition information rather than the environmental prediction information, the operating environment and the operating path are constructed in this embodiment.

[0170] In an alternative embodiment, the step of correcting the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque includes:

[0171] Taking the first recovery torque and the environmental acquisition information as inputs, running the second model to obtain the second recovery torque; wherein, the second model is used to correct the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque.

[0172] The second model includes a second virtual vehicle 1013; the second virtual vehicle 1013 is simulated according to the power parameters, steering parameters, and braking parameters of a specified vehicle.

[0173] Similarly, in this embodiment, the second virtual vehicle 1013 is a digital twin model constructed based on the actual parameters of a specified vehicle, and the foregoing embodiments regarding the first virtual vehicle 1012 are equally applicable to the second virtual vehicle 1013.

[0174] In addition, the second virtual vehicle 1013 and the first virtual vehicle 1012 can be either two completely identical digital twin models or the same digital twin model.

[0175] This embodiment uses the second virtual vehicle 1013 as the basis of the second model, providing a reliable basis for the calculation of the second recovery torque based on the environmental acquisition information, that is, the correction of the first recovery torque, making the second recovery torque more in line with the actual situation, and thus more reliably and effectively realizing the energy recovery control of the vehicle 100.

[0176] In this embodiment, the construction of the operating environment is similar to the construction of the predicted environment, and is constructed based on the temperature, humidity, rainfall (snowfall) information in the environmental acquisition information in cooperation with the road type information in the road information; the construction of the operating path is similar to the construction of the predicted path, and is constructed based on the navigation information and congestion information in the road information.

[0177] Compared with the operation basic environment prediction information of the first model, the operation basic environment acquisition information of the second model has better accuracy. Since the prediction information has a certain reliability, the first recovered torque calculated based on the environment prediction information is still relatively close to the actual value of the second recovered torque. Therefore, the process of running the second model based on the first recovered torque as a reference value will take less time and consume fewer computing resources. On this basis, it becomes possible to perform real-time control of the torque of energy recovery at a higher frequency.

[0178] It should be noted that the process of correcting the first recovered torque to obtain the second recovered torque can also be realized based on an iterative process, that is, calculating the slip ratio and tire sideslip angle of the second virtual vehicle 1013 based on the first recovered torque. If the preset slip ratio condition and tire sideslip angle condition are both satisfied, the value of the first recovered torque is directly determined as the second recovered torque (in some optional embodiments, an iterative verification of the absolute value of the first recovered torque can also be added to get closer to the limit of vehicle performance. This method can ensure the efficiency of energy recovery to the greatest extent, but consumes more computing resources); if the preset slip ratio condition and tire sideslip angle condition are not both satisfied, the absolute value of the first recovered torque is reduced, and the slip ratio and tire sideslip angle of the second virtual vehicle 1013 are verified again until the maximum value of the second recovered torque that satisfies the preset slip ratio condition and tire sideslip angle condition is determined.

[0179] In addition, the naming of the first model and the second model is distinguished based on different tasks. That is to say, in some optional embodiments, the first model and the second model can be the same model entity. When performing the step of obtaining the first recovered torque based on the environment prediction information, this model is called the first model, and when performing the step of obtaining the second recovered torque based on the environment acquisition information, this model is called the second model.

[0180] Different from the first model and / or the second model of the virtual vehicle based on digital twin above, in some other optional embodiments, the first model and the second model are two models constructed based on different model entities.

[0181] For the specific structures of the first model and / or the second model, there are some optional solutions. For example, at least one of the first model and the second model is a deep learning model based on a neural network; another example is that at least one of the first model and the second model is a mathematical model based on mechanical physics operation simulation.

[0182] That is to say, the entity structures of the first model and the second model do not constitute a limitation on the protection scope of this embodiment. The purposes of the first model and the second model are respectively:

[0183] Calculate the maximum energy recovery torque for the stable operation of a specified vehicle under the constraint of environmental prediction information;

[0184] Modify the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque.

[0185] The beneficial effects of this embodiment are as follows:

[0186] Construct an operation scenario and an operation path through the environmental acquisition information. Through the judgment process of whether there is a preset vehicle instability risk for the specified vehicle running on the operation path, that is, the judgment process based on the slip ratio condition and the tire side slip angle condition, and in cooperation with the correction and update of the first recovery torque, the second recovery torque is obtained. This method can correct the first recovery torque through the acquired environmental information, obtain a more real result, obtain a more accurate second recovery torque, and thus more effectively realize the energy recovery control of the vehicle.

[0187] According to any of the above embodiments, the following will provide an embodiment that can achieve more energy recovery control in line with the driver's driving habits. In this embodiment:

[0188] Construct an operation scenario and an operation path according to the environmental acquisition information; the operation scenario includes at least one of the temperature distribution parameter, the humidity distribution parameter, the rainfall distribution parameter, and the road condition parameter;

[0189] Obtain the historical environmental parameters matching the environmental acquisition information, and construct a motion speed function according to the historical operation parameters of the specified vehicle under the historical environmental parameters;

[0190] Modify the first recovery torque with the operation scenario, the operation path, and the motion speed function as constraints to obtain the second recovery torque.

[0191] In an optional implementation manner, the steps of controlling the specified vehicle to perform energy recovery according to the second recovery torque include:

[0192] Call the third model according to the environmental acquisition information to obtain the historical recovery torque under the environmental acquisition information;

[0193] Use the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque to control the specified vehicle to perform energy recovery;

[0194] Among them, the third model includes the historical environmental parameters and historical operation parameters of the specified vehicle.

[0195] In this embodiment, the third model is different from the first model and the second model. Its purpose is to store the historical data (historical environmental parameters and historical operating parameters) of the vehicle, understand the driving habits of the vehicle driver through the historical data, and form an energy recovery intensity control adapted to the driver's habits on this basis. Therefore, it can be understood that the third model can be a model in the form of a database.

[0196] Based on this embodiment, in cooperation with this example, the functions of the third model can be further expanded, that is:

[0197] Considering that there are still other parameters in the third model that can help the energy recovery control conform to the driver's driving habits in addition to the historical recovery torque, a scheme based on the motion speed function is introduced.

[0198] Among them, the motion speed function refers to the function of the vehicle operating speed corresponding to the historical recovery torque changing with time.

[0199] On the one hand, the constraint of the motion speed function can further select historical time nodes with similar speeds as the basis for determining the historical recovery torque in the case of multiple optional historical time nodes, realizing a more fitting energy recovery control according to the driver's driving habits. On the other hand, it can also provide a basis for the introduction of a quantitative parameter of the severity of the vehicle instability consequence when the speeds are different. For example, the vehicle control margin threshold can be set higher at higher speeds to ensure safety.

[0200] In addition, in addition to the speed distribution function, other operating parameters of the vehicle can also be introduced into this example or any of the above examples to achieve personalized energy recovery control.

[0201] The beneficial effect of this example is as follows:

[0202] Based on the historical data, the motion speed function is introduced, and the first recovery torque is corrected considering the variable of the vehicle's motion speed to obtain the vehicle control habits of the driver at a specific speed, and the energy recovery control is adjusted accordingly, so as to make the driver experience more consistent and achieve the effect of "one size fits one person".

[0203] According to any of the above embodiments, a complete embodiment will be provided from an overall perspective below to better illustrate the solution of this application.

[0204] This embodiment can solve the problem that in the scheme of making vehicle steady-state control judgment according to ESC, when the energy recovery torque triggers and causes the whole vehicle to be unstable, the energy recovery is prohibited. The problem is that it is not controlled by prediction, but when the energy recovery torque causes the vehicle to be unstable, the energy recovery is prohibited in a one-size-fits-all way. The optimal energy recovery control torque is found through the digital twin virtual vehicle.

[0205] The purpose of this embodiment is as follows:

[0206] 1. Find the optimal energy recovery control torque through the digital twin virtual vehicle to achieve the purpose of energy saving.

[0207] 2. Classify and store historical data, and use targeted historical working condition data to output torque limit in actual working conditions.

[0208] Figure 3 The application schematic diagram of the energy recovery method of this embodiment is shown.

[0209] The vehicle-mounted processor 101 includes a first model (the first virtual vehicle 1012), a second model (the second virtual vehicle 1013), and a vehicle-mounted storage unit 1011.

[0210] After the environment prediction module 102 sends the environment prediction information to the vehicle-mounted processor 101, the first model runs the first virtual vehicle 1012 to obtain the first recovery torque, and sends the first recovery torque to the vehicle-mounted memory; after the sensor 103 sends the environment acquisition information to the vehicle-mounted processor 101, the second model runs the second virtual vehicle 1013. In addition, the operation input data of the second virtual vehicle 1013 also includes the first recovery torque stored in the memory. After the second model runs the second virtual vehicle 1013, it obtains the second recovery torque and sends it to the vehicle-mounted memory for subsequent energy recovery control.

[0211] Figure 4 The flow schematic diagram of this embodiment is shown. Specifically, the solution of this embodiment includes:

[0212] 1. Build the future path model Model1 (the first model):

[0213] a. Obtain future temperature, humidity, and rainfall information through weather forecasts;

[0214] b. Obtain future road condition information through map tools;

[0215] Build the future path model Model1 in the virtual vehicle through the above information.

[0216] Calculate the energy recovery control torque Tq1 of the future path:

[0217] Obtain the adhesion coefficient μ1 through the future path model Model1. Under the path of μ1 of the virtual vehicle, apply the energy recovery torque Tq1 (the first recovery torque), deduce the vehicle slip ratio and tire sideslip angle. If the vehicle becomes unstable, reduce Tq1 (absolute value) until the vehicle is stable, and output it.

[0218] 2. Build the real-time path model Model2 (the second model):

[0219] a. Obtain real-time temperature information through a temperature sensor;

[0220] b. Obtain real-time humidity information through a humidity sensor;

[0221] c. Obtain real-time rainfall information through a rainfall sensor;

[0222] d. Obtain real-time road condition information through a camera and a radar;

[0223] Construct a real-time road condition model Model2 in the virtual vehicle based on the above information.

[0224] Calculate the energy recovery control torque Tq2 of the real-time path:

[0225] Obtain the adhesion coefficient μ2 through the real-time path model Model2. Apply the future energy recovery torque Tq1 to the virtual vehicle under the μ2 path, and deduce the vehicle slip ratio and tire sideslip angle. If the vehicle becomes unstable, it means that the absolute value of Tq1 is still too large and needs to be reduced until the vehicle is stable, and then output the real-time energy recovery torque Tq2 (the second recovery torque).

[0226] 3. Construct a historical data storage model Model3 (the third model):

[0227] The data and torque of each real-time path are stored as historical data in the virtual vehicle to form a historical path model Model3, obtaining the historical adhesion coefficient μ3 and the corresponding historical energy recovery control torque Tq3 (historical recovery torque).

[0228] 4. Construct the "personalized" energy recovery control torque Tq4:

[0229] Before the real-time energy recovery torque Tq2 is output, compare it with the energy recovery torque Tq3 under the same historical adhesion coefficient, and output the minimum value of their absolute values for further safety redundancy control.

[0230] Since the driving paths of different vehicles are inconsistent and the energy recovery level settings of different drivers are also inconsistent, through the deduction of the digital twin system, the "personalized" energy recovery control torque can be obtained, rather than uniformly prohibiting energy recovery after the current vehicle becomes unstable.

[0231] The beneficial effects of this embodiment are as follows:

[0232] 1. Solve the problem that the current excessive energy recovery torque triggers the ESP function, resulting in the prohibition of the energy recovery torque and the inability to achieve the energy-saving effect.

[0233] 2. More efficiently control the output of the energy recovery torque, avoiding repeated calculations for the same working conditions and wasting computing power.

[0234] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0235] Corresponding to the energy recovery method in the above embodiment, Figure 1 The structural block diagram of the energy recovery device provided by the embodiment of the present application is shown. For the convenience of description, only the parts related to the embodiment of the present application are shown.

[0236] Referring to Figure 5 , the device includes:

[0237] The first recovery torque module 501 is used to obtain the first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque for the specified vehicle to operate stably under the constraint of the environmental prediction information;

[0238] The second recovery torque module 502 is used to correct the first recovery torque under the constraint of the environmental acquisition information to obtain the second recovery torque;

[0239] The recovery module 503 is used to control the specified vehicle to perform energy recovery according to the second recovery torque.

[0240] In an alternative embodiment, the recovery module 503 includes:

[0241] The history unit is used to obtain the historical recovery torque under the environmental acquisition information;

[0242] The redundancy control unit is used to use the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque to control the specified vehicle to perform energy recovery.

[0243] In an alternative embodiment, the first recovery torque module 501 includes:

[0244] The prediction unit is used to construct a prediction scenario and a prediction path according to the environmental prediction information; the prediction scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter; the prediction path is a path within the prediction scenario;

[0245] The iteration unit is used to calculate the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with the prediction torque;

[0246] An update unit is used to update the predicted torque and return the steps of calculating the slip ratio and tire sideslip angle when a specified vehicle running on a predicted path recovers energy with the predicted torque until the maximum predicted torque that satisfies the preset slip ratio condition and the preset tire sideslip angle condition is obtained as the first recovery torque.

[0247] In an optional implementation manner, the update unit includes:

[0248] An increase sub-unit is used to determine that when the slip ratio satisfies the preset slip ratio condition and the tire sideslip angle satisfies the preset tire sideslip angle condition under the predicted torque, update the predicted torque to a torque value with a larger absolute value;

[0249] A decrease sub-unit is used to determine that when the slip ratio does not satisfy the preset slip ratio condition or the tire sideslip angle does not satisfy the preset tire sideslip angle condition under the predicted torque, update the predicted torque to a torque value with a smaller absolute value.

[0250] In an optional implementation manner, the second recovery torque module 502 includes:

[0251] An operation unit is used to construct an operation scenario and an operation path according to the environment acquisition information; the operation scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter; the operation path is a path within the operation scenario;

[0252] A parameter calculation unit is used to:

[0253] Calculate the slip ratio and tire sideslip angle when a specified vehicle running on the operation path recovers energy with the first recovery torque;

[0254] If the slip ratio satisfies the preset slip ratio condition and the tire sideslip angle satisfies the preset tire sideslip angle condition, output the second recovery torque; the value of the second recovery torque is the same as that of the first recovery torque;

[0255] If the slip ratio does not satisfy the preset slip ratio condition or the tire sideslip angle does not satisfy the preset tire sideslip angle condition, output the second recovery torque; the absolute value of the second recovery torque is less than that of the first recovery torque.

[0256] In an optional implementation manner, the second recovery torque module 502 includes:

[0257] An operation unit is used to construct an operation scenario and an operation path according to the environment acquisition information; the operation scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter;

[0258] A speed function unit, configured to obtain historical environmental parameters matching the environmental acquisition information, and construct a motion speed function based on the historical operation parameters of a specified vehicle under the historical environmental parameters;

[0259] A correction unit, configured to correct the first recuperation torque with the operation scenario, operation path, and motion speed function as constraints to obtain a second recuperation torque.

[0260] In an optional embodiment, the historical unit includes:

[0261] An adhesion coefficient subunit, configured to calculate the road surface adhesion coefficient according to the environmental acquisition information;

[0262] An adhesion consistency subunit, configured to obtain the historical adhesion coefficient consistent with the road surface adhesion coefficient and the historical recuperation torque corresponding to the historical adhesion coefficient in the historical operation data of the specified vehicle.

[0263] In an optional embodiment, the first recuperation torque module 501 includes:

[0264] A first model unit, configured to take the environmental prediction information as input, run a first model to obtain a first recuperation torque; wherein, the first model is a model for calculating the maximum energy recuperation torque for the stable operation of the specified vehicle under the constraint of the environmental prediction information.

[0265] In an optional embodiment, the first model includes a first virtual vehicle 1012; the first virtual vehicle 1012 is simulated according to the power parameters, steering parameters, and braking parameters of the specified vehicle.

[0266] In an optional embodiment, the second recuperation torque module 502 includes:

[0267] A second model unit, configured to take the first recuperation torque and the environmental acquisition information as input, run a second model to obtain a second recuperation torque; wherein, the second model is used to correct the first recuperation torque under the constraint of the environmental acquisition information to obtain the second recuperation torque.

[0268] In an optional embodiment, the second model includes a second virtual vehicle 1013; the second virtual vehicle 1013 is simulated according to the power parameters, steering parameters, and braking parameters of the specified vehicle.

[0269] In an optional embodiment, the recuperation module 503 includes:

[0270] A third model unit, configured to call a third model according to the environmental acquisition information to obtain the historical recuperation torque under the environmental acquisition information;

[0271] A redundant control unit is used to take the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque, and control a specified vehicle to perform energy recovery;

[0272] Wherein, the third model includes the historical environmental parameters and historical operation parameters of the specified vehicle.

[0273] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units, due to being based on the same concept as the method embodiment of the present application, for their specific functions and the technical effects brought, please refer to the method embodiment part for details, and will not be elaborated here.

[0274] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be elaborated here.

[0275] The embodiment of the present application also provides a terminal device, as Figure 6 shown. The terminal device 60 includes: at least one processor 601, a memory 602, and a computer program 603 stored in the memory and executable on at least one processor. When the processor 601 executes the computer program 603, the steps in any of the foregoing method embodiments are implemented.

[0276] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the foregoing method embodiments can be implemented.

[0277] The embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, it enables the mobile terminal to implement the steps in the foregoing method embodiments.

[0278] When an integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, a computer program can be used to instruct relevant hardware to complete the operations. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0279] In the above embodiments, the descriptions of the various embodiments have their own focuses. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0280] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0281] In the embodiments provided in this application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0282] The unit described as a separating component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0283] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An energy recovery method, characterized in that, Including: Obtain a first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque for the specified vehicle to operate stably obtained by performing predictive operations under the constraint of environmental prediction information; Modify the first recovery torque under the constraint of the environmental acquisition information to obtain a second recovery torque; Control the specified vehicle to perform energy recovery according to the second recovery torque; The step of obtaining the first recovery torque includes: Construct a prediction scenario and a prediction path according to the environmental prediction information; the prediction scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter other than the temperature distribution parameter, the humidity distribution parameter, and the rainfall distribution parameter; the prediction path is the path within the prediction scenario; Calculate the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with a prediction torque; Update the prediction torque, and return to the step of calculating the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with the prediction torque until the maximum value of the prediction torque that satisfies the preset slip ratio condition and the preset tire sideslip angle condition is obtained as the first recovery torque.

2. The energy recovery method according to claim 1, wherein The step of controlling the specified vehicle to perform energy recovery according to the second recovery torque includes: Obtain the historical recovery torque under the environmental acquisition information; Use the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque, and control the specified vehicle to perform energy recovery.

3. The energy recovery method according to claim 1 or 2, characterized in that The step of updating the prediction torque includes: If it is determined that under the prediction torque, the slip ratio satisfies the preset slip ratio condition and the tire sideslip angle satisfies the preset tire sideslip angle condition, then update the prediction torque to a torque value with a larger absolute value; If it is determined that under the prediction torque, the slip ratio does not satisfy the preset slip ratio condition, or the tire sideslip angle does not satisfy the preset tire sideslip angle condition, then update the prediction torque to a torque value with a smaller absolute value.

4. The energy recovery method according to claim 1 or 2, characterized in that, The step of modifying the first recovery torque under the constraint of the environmental acquisition information to obtain a second recovery torque includes: Construct an operation scenario and an operation path according to the environmental acquisition information; the operation scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter other than the temperature distribution parameter, the humidity distribution parameter, and the rainfall distribution parameter; the operation path is the path within the operation scenario; Calculate the slip ratio and the tire sideslip angle when the specified vehicle running on the operation path performs energy recovery with the first recovery torque; If the slip ratio satisfies the preset slip ratio condition and the tire sideslip angle satisfies the preset tire sideslip angle condition, then output the second recovery torque; the value of the second recovery torque is the same as that of the first recovery torque; If the slip ratio does not satisfy the preset slip ratio condition, or the tire sideslip angle does not satisfy the preset tire sideslip angle condition, then output the second recovery torque; the absolute value of the second recovery torque is less than that of the first recovery torque.

5. The energy recovery method according to claim 1 or 2, characterized in that The step of correcting the first recovery torque under the constraint of the environment acquisition information to obtain a second recovery torque includes: Construct an operating scenario and an operating path according to the environment acquisition information; the operating scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter other than the temperature distribution parameter, the humidity distribution parameter, and the rainfall distribution parameter; Obtain historical environment parameters matching the environment acquisition information, and construct a motion speed function according to the historical operating parameters of the specified vehicle under the historical environment parameters; Correct the first recovery torque with the operating scenario, the operating path, and the motion speed function as constraints to obtain the second recovery torque.

6. The energy recovery method according to claim 2, wherein The step of obtaining the historical recovery torque under the environment acquisition information includes: Calculate the road surface adhesion coefficient according to the environment acquisition information; Obtain the historical adhesion coefficient consistent with the road surface adhesion coefficient in the historical operating data of the specified vehicle, and the historical recovery torque corresponding to the historical adhesion coefficient.

7. The energy recovery method according to claim 1 or 2, characterized in that The step of obtaining the first recovery torque includes: Taking the environment prediction information as an input, running a first model to obtain a first recovery torque; wherein, the first model is a model for calculating the maximum energy recovery torque for the stable operation of the specified vehicle under the constraint of the environment prediction information.

8. The energy recovery method according to claim 7, wherein The first model includes a first virtual vehicle; The first virtual vehicle is simulated according to the power parameters, steering parameters, and braking parameters of the specified vehicle.

9. The energy recovery method according to claim 1 or 2, characterized in that, The step of correcting the first recovery torque under the constraint of the environment acquisition information to obtain a second recovery torque includes: Taking the first recovery torque and the environment acquisition information as inputs, running a second model to obtain a second recovery torque; wherein, the second model is used to correct the first recovery torque under the constraint of the environment acquisition information to obtain the second recovery torque.

10. The energy recovery method according to claim 9, wherein, The second model includes a second virtual vehicle; the second virtual vehicle is simulated according to the power parameters, steering parameters, and braking parameters of the specified vehicle.

11. The energy recovery method according to any one of claims 1, 2, 6, 8, and 10, characterized in that, The step of controlling the specified vehicle to perform energy recovery according to the second recovery torque includes: Calling a third model according to the environment acquisition information to obtain the historical recovery torque under the environment acquisition information; Taking the smaller absolute value of the historical recovery torque and the second recovery torque as the absolute value upper limit of the energy recovery torque, and controlling the specified vehicle to perform energy recovery; Wherein, the third model includes the historical environment parameters and historical operating parameters of the specified vehicle.

12. An energy recovery device, characterized in that, Includes: A first recovery torque module, configured to obtain a first recovery torque; wherein, the first recovery torque is the maximum energy recovery torque for the stable operation of the specified vehicle obtained by performing predictive operations under the constraint of the environment prediction information; A second recovery torque module, configured to correct the first recovery torque under the constraint of the environment acquisition information to obtain a second recovery torque; A recovery module, configured to control the specified vehicle to perform energy recovery according to the second recovery torque; The first recovery torque module includes: A prediction unit for constructing a prediction scenario and a prediction path according to the environmental prediction information; the prediction scenario includes at least one of a temperature distribution parameter, a humidity distribution parameter, a rainfall distribution parameter, and a road condition parameter other than the temperature distribution parameter, the humidity distribution parameter, and the rainfall distribution parameter; the prediction path is a path within the prediction scenario; An iteration unit for calculating a slip ratio and a tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with a predicted torque; An update unit for updating the predicted torque and returning to the step of calculating the slip ratio and the tire sideslip angle when the specified vehicle running on the prediction path performs energy recovery with the predicted torque until the maximum predicted torque that satisfies a preset slip ratio condition and a preset tire sideslip angle condition is obtained as the first recovery torque.

13. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 11 is implemented.

14. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

15. A vehicle, characterized in that, Including the energy recovery device according to claim 12 or the terminal device according to claim 13.

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