An energy recovery control method, device and electronic equipment

Abstract

The application provides an energy recovery control method and device and electronic equipment, and relates to the field of new energy vehicle control. The method comprises the following steps: collecting vehicle working condition information in real time, judging whether the working condition information is valid; if the working condition information is valid, setting a first target deceleration based on the graded working condition information, and executing a corresponding energy recovery mode in response to the operation of a man-machine interaction module to obtain a second target deceleration; monitoring the whole vehicle slip rate in real time, adjusting the second target deceleration to obtain a third target deceleration, so that the slip rate is in a preset slip rate interval; and using a PI controller to determine and adjust the recovery torque according to the third target deceleration and the actual deceleration. The scheme improves the energy recovery efficiency and improves the reliability and safety of the recovery control under complex and abnormal working conditions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy vehicle control, and particularly relates to an energy recovery control method and device and electronic equipment. BACKGROUND

[0002] In the field of new energy vehicles, energy recovery plays an important role in improving energy utilization efficiency, extending the cruising range, and reducing energy waste. Patent application US20220097676 discloses a regenerative braking and damping system for a hybrid heavy truck, which predicts road load changes using a three-dimensional electronic map, measures slope with high precision to adapt to changes, dynamically distributes power according to slope and load, realizes non-friction damping through regenerative braking, adjusts motor output according to battery capacity, and adjusts following distance according to vehicle state. However, since this technical solution is mainly optimized for specific needs of long-distance transportation and energy management, its original design does not fully consider the diversified scenarios of ordinary passenger cars and urban driving, and therefore has the following problems: dependence on electronic maps and RTK data may fail in remote areas, high demand for control strategy calculation leads to high cost and possible delayed response, deceleration effect is unstable under different slopes and loads, strategies for empty and full load states are not fully adjusted, sensors fail, and there is a lack of perfect emergency measures under extreme conditions. SUMMARY

[0003] The present application aims to at least solve the technical problems existing in the prior art. To this end, the present application proposes, in a first aspect, an energy recovery control method, which comprises:

[0004] collecting vehicle working condition information in real time and determining whether the working condition information is valid; the working condition information includes vehicle speed, slope, and load;

[0005] if the working condition information is valid, classifying the working condition information, setting a first target deceleration based on the classified working condition information, and in response to the operation of a human-machine interaction module, executing a corresponding energy recovery mode to correct the first target deceleration to obtain a second target deceleration; the first target deceleration is an adaptive kinetic energy recovery target deceleration; the energy recovery mode includes an economy mode, a sports mode, and a custom mode;

[0006] monitoring the vehicle slip ratio in real time, adjusting the second target deceleration to obtain a third target deceleration, so that the slip ratio is within a preset slip ratio range;

[0007] determining and adjusting the recovery torque according to the third target deceleration and the actual deceleration using a PI controller.

[0008] Optionally, before the step of determining and adjusting the recovery torque according to the third target deceleration and the actual deceleration using a PI controller, the method further comprises:

[0009] determining whether the vehicle is in a coasting energy recovery phase;

[0010] if the vehicle is in the coasting energy recovery phase, correcting the third target deceleration based on a driver behavior self-learning model and driver operation of a brake pedal and an accelerator pedal.

[0011] Optionally, the executing a corresponding energy recovery mode corrects the first target deceleration to obtain a second target deceleration, and the correcting the third target deceleration based on the driver behavior self-learning model and the driver operation of the brake pedal and the accelerator pedal comprises:

[0012] if an economy mode is executed, a negative correction value is used to correct the first target deceleration to maximize energy recovery of the vehicle;

[0013] if a sport mode is executed, a positive correction value is used to correct the first target deceleration or the first target deceleration is kept unchanged;

[0014] if a custom mode is executed, the first target deceleration is corrected in response to a recovery intensity level in a human-computer interaction module; the recovery intensity level is defined by a user through a center screen.

[0015] Optionally, the method further comprises:

[0016] if the vehicle slip ratio is greater than a preset slip ratio threshold, a recovery torque loading slope and an adaptive kinetic energy recovery torque protection upper limit are reduced.

[0017] Optionally, if the recovery torque is greater than the adaptive kinetic energy recovery torque protection upper limit, the torque protection upper limit is output.

[0018] Optionally, if the actual deceleration is less than the third target deceleration, a PI controller increases the recovery torque; if the actual deceleration is greater than the third target deceleration, the PI controller decreases the recovery torque.

[0019] Optionally, the method further comprises:

[0020] if the vehicle enters the coasting energy recovery phase, the actual deceleration is processed through a first-order low-pass filter; the actual deceleration is calculated through a vehicle speed sensor.

[0021] Optionally, the method further comprises:

[0022] real-time monitoring of an ESC state and a vehicle speed signal, if the state is an abnormal state, a backup control strategy is used; the backup control strategy is to determine a recovery torque according to a preset target deceleration and an actual deceleration through a PI controller, and keep the preset target deceleration unchanged.

[0023] A second aspect of the present application provides an energy recovery control device, the device comprising:

[0024] an information collection unit, configured to collect vehicle working condition information in real time, and determine whether the working condition information is valid; the working condition information includes vehicle speed, slope and load;

[0025] a first data processing unit, configured to, if the working condition information is valid, classify the working condition information, set a first target deceleration based on the classified working condition information, and in response to an operation of a human-computer interaction module, execute a corresponding energy recovery mode to correct the first target deceleration to obtain a second target deceleration; the first target deceleration is an adaptive kinetic energy recovery target deceleration; the energy recovery mode includes an economy mode, a sport mode and a self-defined mode;

[0026] a second data processing unit, configured to monitor a vehicle slip ratio in real time, adjust the second target deceleration to obtain a third target deceleration, so that the slip ratio is within a preset slip ratio range;

[0027] a control unit, configured to determine and adjust a recovery torque according to the third target deceleration and an actual deceleration by using a PI controller

[0028] A third aspect of the present application provides an electronic device, which comprises a processor and a memory, and the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the energy recovery control method as described in the first aspect.

[0029] The energy recovery control method, device and electronic device have the following beneficial effects: through the control strategy based on the vehicle slip ratio, the wheel slip ratio is controlled within an optimal range by actively adjusting the braking and energy recovery strategy of the vehicle before the risk of vehicle instability occurs, so that the tire adhesion is maximally maintained, and the driving safety and stability of the vehicle are ensured; the driver behavior self-learning model is constructed to realize the individualized adaptation of the recovery strategy, and the driving comfort is improved; the driver self-defined control is fused to return the control right to the driver to a certain extent, the flexibility of the system is greatly enhanced, and the diversified needs of the user in different driving scenarios are met; the target deceleration is implemented to perform the deceleration closed-loop control, the working condition information including the vehicle speed, the slope and the load is considered in the control process, and the standby control strategy is adopted through the abnormal state detection, so that the reliability and safety of the recovery control under the complex driving scenarios and abnormal working conditions are greatly improved. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 A flowchart of an energy recovery control method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0032] Hereinafter, the terms "first" and "second" are used only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, the meaning of "a plurality of" is two or more. In addition, the use of "based on" or "according to" means openness and inclusiveness, because the process, step, calculation or other action "based on" or "according to" one or more stated conditions or values can be based on additional conditions or values beyond the stated values in practice.

[0033] The embodiments of the present application provide an energy recovery control method, as shown in the figure, which can include the following steps: Figure 1

[0034] Step 101, collecting vehicle working condition information in real time, and judging whether the working condition information is valid; the working condition information includes vehicle speed, slope and load.

[0035] The control method in the embodiments of the present application is used for the energy recovery system of a pure electric or hybrid commercial vehicle, and the energy recovery includes coasting energy recovery and braking energy recovery. Specifically, the valid working condition information means that the signals collected by the sensor are not abnormal, that is, these signals are reliable. In the embodiments of the present application, the real-time slope can be estimated by an electronic stability control system or a transmission control unit. The vehicle speed signals from multiple sources such as ABS, TCU and GPS are collected to judge whether the vehicle speed signal is valid, and the main vehicle speed signal is compared with other signals in real time. The main vehicle speed signal refers to the vehicle speed signal obtained by reverse calculation through the transmission output shaft sensor. Only when the vehicle speed signals from multiple sources are all normal, it is considered that the vehicle speed is valid. If the vehicle speed signal from one source is abnormal, it is considered that the vehicle speed signal is invalid. The load information can be estimated by combining the ESC sensor with the slope sensor of the transmission. The vehicle control unit (VCU) receives the data collected by each sensor, executes the control algorithm and outputs the recovery torque instruction.

[0036] ​Step 102, if the working condition information is valid, grading the working condition information, setting a first target deceleration based on the graded working condition information, and in response to the operation of the human-computer interaction module, executing a corresponding energy recovery mode to correct the first target deceleration to obtain a second target deceleration; the first target deceleration is an adaptive kinetic energy recovery target deceleration; the energy recovery mode includes an economic mode, a sports mode, and a custom mode.

[0037] In a possible implementation, the step of executing a corresponding energy recovery mode to correct the first target deceleration to obtain a second target deceleration includes:

[0038] If the economic mode is executed, a negative correction value is used to correct the first target deceleration so that the vehicle maximizes energy recovery;

[0039] If the sports mode is executed, a positive correction value is used to correct the first target deceleration or the first target deceleration is kept unchanged;

[0040] If the custom mode is executed, the first target deceleration is corrected in response to a recovery intensity level in the human-computer interaction module; the recovery intensity level is customized by a user through a center control screen.

[0041] The first target deceleration is determined according to the vehicle speed, the slope, and the load, the working condition information is graded, and the first target deceleration is set according to the graded working condition information. The target deceleration in the embodiment of the application is an adaptive kinetic energy recovery target deceleration. Specifically, a first target deceleration table in an empty load state, a first target deceleration table in a half load state, and a first target deceleration table in a full load state are established respectively. In the three tables, different first target decelerations are set according to different vehicle speed and slope intervals. For example, in the empty load state, according to the current vehicle speed and the slope, the current vehicle speed and the slope are determined to correspond to the vehicle speed interval and the slope interval in the empty load state table, and the first target deceleration can be obtained by looking up the table.

[0042] The driver can select different energy recovery modes through the human-computer interaction module, and the user interface can be provided through the in-vehicle infotainment (IVI) system, so that the driver can switch between multiple preset energy recovery modes. The energy mode is part of the total energy recovery scheme in the embodiment of the application which can be determined by the driver according to the demand, and after the target deceleration is corrected according to the mode selected by the driver, it is still necessary to judge whether to automatically correct according to the actual situation. Through multi-mode switching, the driver is provided with the initiative to choose the recovery strategy, and the specific needs in different scenarios are met. The default mode is the economy mode, that is, if the driver does not select a specific mode, the economy mode is executed. The absolute value of the deceleration correction value in the economy mode is greater than the correction value of the deceleration in the sports mode. In the economy mode, the maximum energy recovery is achieved, while in the sports mode, the correction is made to provide a sliding experience closer to the traditional fuel vehicle. The driver can configure the parameters of the custom mode. In the custom mode, the driver can adjust the sliding bar on the vehicle touch screen within the preset recovery intensity range, that is, the minimum recovery intensity to the maximum recovery intensity, and the vehicle touch screen is the center control screen. Exemplarily, the driver can set the slider at 80% position, at which time the recovery intensity is 80% of the maximum recovery intensity. According to the mapping relationship, the setting is converted into a specific target acceleration correction value Δa_mode, for example, -0.2 m / s².

[0043] Step 103, real-time monitoring of the vehicle slip rate, adjusting the second target deceleration, obtaining a third target deceleration, so that the slip rate is in a preset slip rate interval.

[0044] In a possible implementation, further comprising:

[0045] If the vehicle slip rate is greater than a preset slip rate threshold, the energy recovery torque loading slope and the adaptive kinetic energy recovery torque protection upper limit are reduced.

[0046] During the driving process, especially in rainy and snowy weather, when braking or kinetic energy recovery is performed on icy or wet road surface, the driving wheel may slip due to excessive braking torque, i.e., the rotation speed of the wheel is lower than the actual driving speed of the vehicle. If not controlled, such slip may cause a sharp decrease in tire grip, leading to vehicle instability, and even risk of spin or loss of control. Therefore, it is necessary to determine in real time whether the vehicle is at risk of slip or spin through a vehicle traction control system. The core objective of the control strategy based on slip rate for target deceleration in the embodiment of the present application is to control the wheel slip rate within an optimal range by actively adjusting the braking and energy recovery strategy of the vehicle before the risk of vehicle instability occurs, so as to maximize the tire adhesion and ensure the driving safety and stability of the vehicle. Specifically, the rotation speed of each wheel is monitored in real time, and the actual speed of the vehicle is estimated based on the rotation speed of each wheel, the lateral acceleration of the vehicle and other information. The difference between the actual speed of the vehicle and the rotation speed of the wheel is calculated, and the ratio of the difference to the vehicle speed is the slip rate of the corresponding wheel. In the embodiment, when the slip rate of a certain driving wheel is greater than a preset slip rate threshold, the system determines that there is a risk of slip or spin, and then the target deceleration is reduced, the energy recovery torque loading slope is reduced, and the adaptive kinetic energy recovery torque protection upper limit is reduced.

[0047] Step 104, determining and adjusting the recovery torque by using a PI controller according to the third target deceleration and the actual deceleration.

[0048] In a possible implementation, before the step of determining and adjusting the recovery torque by using a PI controller according to the third target deceleration and the actual deceleration, the method further includes:

[0049] determining whether the vehicle is in a coasting energy recovery phase;

[0050] if the vehicle is in the coasting energy recovery phase, correcting the third target deceleration based on a driver behavior self-learning model and the operation of the brake pedal and the accelerator pedal by the driver.

[0051] A driver behavior self-learning model is deployed in the VCU, which is established by analyzing the long-term operation habits of the driver, i.e., continuously recording and analyzing the operation frequency, pedal opening and time sequence characteristics of the driver on the accelerator pedal and brake pedal, and dynamically updating the model. The driver behavior self-learning model is used to individually fine-tune the recovery strategy to improve the driving comfort and human-machine cooperation of the driver. Specifically, the model continuously monitors the operation of the driver during the coasting phase. If, in a plurality of consecutive driving cycles, the driver steps on the brake pedal multiple times at the end of the adaptive coasting recovery, and the frequency of stepping on the brake pedal at the end of the coasting recovery is greater than a first frequency threshold, and the pedal opening is less than a first opening threshold, the driver behavior self-learning model determines that the current recovery strength is too weak for the driver, and therefore generates a negative deceleration correction value Δa_driver to correct the third target deceleration, for example, the deceleration correction value can be set to -0.05 m / s 2 to increase the deceleration during coasting, thereby reducing the dependence of the driver on the brake pedal. The time when the coasting starts is denoted as t0, t1 is a time after coasting, and a time threshold T is preset. For drivers who are used to stepping on the accelerator pedal, if it is detected that the driver steps on the accelerator pedal n times to maintain the vehicle speed between t0 and t1 after coasting, where n is greater than a preset number threshold N, the driver behavior self-learning model determines that the current recovery strength is too strong for the driver, causing the vehicle speed to drop too quickly, and therefore generates a positive deceleration correction value Δa_driver to correct the third target deceleration, which can be set to +0.05 m / s 2 to reduce the deceleration during coasting, so that the speed transition is smoother, the comfort of the driver is improved, and unnecessary energy consumption is reduced.

[0052] In a possible implementation, the method further includes:

[0053] If the vehicle enters the coasting energy recovery phase, the actual deceleration is processed by a first-order low-pass filter; and the actual deceleration is calculated by a vehicle speed sensor.

[0054] Specifically, the actual deceleration of the vehicle is calculated by a vehicle speed sensor, and a first-order low-pass filter is used for processing, thereby improving the stability of the data.

[0055] In a possible implementation, if the recovery torque is greater than the upper limit of the adaptive kinetic energy recovery torque protection, the torque protection upper limit is output.

[0056] In a possible implementation, if the actual deceleration is less than the third target deceleration, the PI controller increases the recovery torque; and if the actual deceleration is greater than the third target deceleration, the PI controller decreases the recovery torque.

[0057] The PI controller dynamically adjusts the motor recovery torque in real time according to the acceleration error, specifically, the acceleration error is the difference between the third target deceleration and the actual deceleration. If the actual deceleration is less than the third target deceleration, for example, the vehicle accelerates when going downhill, at this time the acceleration error is positive, the integral term of the PI controller accumulates, and the output recovery torque is P1; if the actual deceleration is greater than the third target deceleration, for example, the vehicle decelerates too fast when going uphill, at this time the acceleration error is negative, the integral term of the PI controller decreases, and the output recovery torque is P2, wherein P is the recovery torque before adjustment, P1 is greater than P, and P is greater than P2. It should be noted that the output recovery torque in the embodiment of the application also needs to be subject to motor peak power, battery charging power, temperature and other multiple safety limits.

[0058] In a possible implementation, the method further includes:

[0059] The ESC state and the vehicle speed signal are monitored in real time, and if the state is abnormal, a backup control strategy is used; the backup control strategy is to determine the recovery torque according to the preset target deceleration and the actual deceleration by using a PI controller, and keep the preset target deceleration unchanged.

[0060] Specifically, when the ESC, slope, load and vehicle speed signals are monitored to be in an abnormal state, that is, the signals are not trustworthy, the adaptive control mode based on the deceleration closed loop is immediately exited, and the backup control strategy is switched to, so as to ensure the basic recovery function and driving safety. The backup control strategy is a set of preset open-loop torque control strategy based on vehicle speed lookup table. When the abnormal state occurs, a fixed target deceleration is directly used, for example, the fixed target deceleration can be -0.3 m / s 2 .

[0061] It should be noted that, in order to avoid frequent changes of the control target due to signal fluctuations near the slope and specific vehicle speed critical points, a slope hysteresis threshold and a vehicle speed hysteresis threshold are introduced. Only when the signal change exceeds the hysteresis threshold, the target deceleration is corrected, to ensure the smoothness of the adjustment. The hysteresis control improves the smoothness and stability of the adjustment.

[0062] If the absolute value of the difference between the actual deceleration and the third target deceleration is greater than or equal to the safety threshold for more than a time threshold M, it is judged that the closed-loop control is invalid or an extreme working condition is encountered, and the recovery torque is actively limited to a safety value. Exemplarily, the time threshold can be set to 2 seconds, and the safety threshold can be set to 1 m / s 2 .

[0063] When the driver activates the snow mode of the vehicle, the final output target deceleration is automatically reduced, and the dynamic change rate of the recovery torque is reduced, to adapt to the low adhesion coefficient road surface and prevent the risk of wheel lock and side slip.

[0064] In summary, based on the target deceleration closed-loop control, and by fusing the slip rate detection system, the driver behavior self-learning and the user-defined multi-dimensional cooperative control method, the traditional single vehicle passive control limitations are broken through, an intelligent kinetic energy recovery control system integrating global optimization, personalized adaptation, active adjustment and closed-loop feedback is established, the generation of the control target is decomposed into a hierarchical structure of basic calibration and multi-dimensional correction, so that each system can cooperatively act on the core control loop in a modular manner, and the logical clarity, expandability and robustness of the system are improved. No matter how the slope, speed or load changes, the deceleration of the vehicle during coasting is close to the third target deceleration, the driving safety and comfort are improved, and the method is applicable to various driving scenarios; by dynamically optimizing the recovery torque, more than 95% of the actual working conditions are covered, such as mountainous and hilly working conditions, and the energy recovery efficiency is significantly improved; on low adhesion road or under no load, tire slip is avoided, the downhill driving safety is ensured, and the safety is improved; the energy recovery system evolves from an isolated execution unit to an intelligent subsystem capable of learning, thinking and cooperation, which is an important part of realizing advanced automatic driving and vehicle-road cooperation technology, and improves the intelligent level of the whole vehicle. In addition, compared with the prior art which uses multiple complex algorithms and needs new hardware to match, the present scheme uses a processing method with lower system complexity and less dependence on the processing power of the processor.

[0065] In the embodiment of the present application, before the vehicle instability risk occurs, the wheel slip rate is controlled within the optimal range by actively adjusting the braking and energy recovery strategy of the vehicle, so as to maximize the tire adhesion and ensure the driving safety and stability of the vehicle; a driver behavior self-learning model is constructed, so that the vehicle control strategy can adapt to the driving style of different drivers, and through the fine adjustment of man-machine co-driving, the personalized adaptation of the recovery strategy is realized, the driving comfort and smoothness are improved, and the problems of "stiffness" and "not following" of the traditional recovery system are solved; the driver-defined control is fused, and the control right is partially returned to the driver, which greatly enhances the flexibility of the system and meets the diversified needs of users in different driving scenarios; based on the target deceleration, the deceleration closed-loop control is implemented, the working condition information including the speed, slope and load is considered in the control process, and through abnormal state detection and the use of backup control strategy, the reliability, comfort and safety of the recovery control under complex driving scenarios and abnormal working conditions are greatly improved.

[0066] The embodiment of the present application also provides an energy recovery control device, which comprises:

[0067] An information acquisition unit is configured to acquire vehicle working condition information in real time and determine whether the working condition information is valid; the working condition information comprises vehicle speed, slope and load;

[0068] The first data processing unit is configured to grade the working condition information if the working condition information is valid, set a first target deceleration based on the graded working condition information, and correct the first target deceleration by a corresponding energy recovery mode in response to an operation of the human-computer interaction module to obtain a second target deceleration; the first target deceleration is an adaptive kinetic energy recovery target deceleration; and the energy recovery mode includes an economy mode, a sport mode, and a self-defined mode.

[0069] The second data processing unit is configured to monitor a vehicle slip ratio in real time, adjust the second target deceleration, and obtain a third target deceleration so that the slip ratio is within a preset slip ratio range.

[0070] The control unit is configured to determine and adjust a recovery torque according to the third target deceleration and an actual deceleration by using a PI controller.

[0071] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0072] In another embodiment, an electronic device is provided, which includes a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or at least one program being loaded and executed by the processor to implement the energy recovery control method proposed in the embodiments of the present application.

[0073] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any change or replacement within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An energy recovery control method characterized by, The method comprises the following steps: Real-time acquisition of vehicle working condition information, judgment of whether the working condition information is valid; the working condition information includes vehicle speed, slope and load; If the working condition information is valid, the working condition information is graded, a first target deceleration is set based on the graded working condition information, and a second target deceleration is obtained by correcting the first target deceleration corresponding to the energy recovery mode in response to the operation of the human-computer interaction module; the first target deceleration is an adaptive kinetic energy recovery target deceleration; the energy recovery mode includes an economic mode, a sports mode and a self-defined mode; The execution of the corresponding energy recovery mode to correct the first target deceleration to obtain the second target deceleration comprises: If the economic mode is executed, a negative correction value is used to correct the first target deceleration to maximize energy recovery of the vehicle; If the sports mode is executed, a positive correction value is used to correct the first target deceleration or the first target deceleration is kept unchanged; If the self-defined mode is executed, the first target deceleration is corrected in response to the recovery intensity level in the human-computer interaction module; the recovery intensity level is defined by the user through the center screen; Real-time monitoring of the vehicle slip rate, adjustment of the second target deceleration to obtain a third target deceleration, so that the slip rate is in a preset slip rate interval; Using a PI controller to determine and adjust the recovery torque according to the third target deceleration and the actual deceleration.

2. The energy recovery control method according to claim 1, characterized by, Before using the PI controller to determine and adjust the recovery torque according to the third target deceleration and the actual deceleration, it further comprises: Judging whether the vehicle is in the sliding energy recovery stage; If the vehicle is in the sliding energy recovery stage, the third target deceleration is corrected based on the driver behavior self-learning model and the driver's operation of the brake pedal and the accelerator pedal.

3. The energy recovery control method according to claim 1, characterized by, Further comprising: If the vehicle slip rate is greater than the preset slip rate threshold, the energy recovery torque loading slope and the adaptive kinetic energy recovery torque protection upper limit are reduced.

4. The energy recovery control method according to claim 1, characterized by, If the recovery torque is greater than the adaptive kinetic energy recovery torque protection upper limit, the torque protection upper limit is output.

5. The energy recovery control method according to claim 1, characterized by, If the actual deceleration is less than the third target deceleration, the PI controller increases the recovery torque; if the actual deceleration is greater than the third target deceleration, the PI controller reduces the recovery torque.

6. The energy recovery control method according to claim 1, characterized by, Further comprising: If the sliding energy recovery stage is entered, the actual deceleration is processed by a first-order low-pass filter; The actual deceleration is calculated by a vehicle speed sensor.

7. The energy recovery control method according to claim 1, characterized by, Further comprising: Real-time monitoring of the ESC state and the vehicle speed signal, if it is an abnormal state, a backup control strategy is used; The backup control strategy is to determine the recovery torque according to the preset target deceleration and the actual deceleration using a PI controller, and keep the preset target deceleration unchanged.

8. An energy recovery control device, characterized by, The device comprises: An information acquisition unit for real-time acquisition of vehicle working condition information, judgment of whether the working condition information is valid; the working condition information includes vehicle speed, slope and load; The first data processing unit is configured to grade the working condition information if the working condition information is valid, set a first target deceleration based on the graded working condition information, and correct the first target deceleration by a corresponding energy recovery mode in response to an operation of the human-machine interaction module to obtain a second target deceleration; the first target deceleration is an adaptive kinetic energy recovery target deceleration; the energy recovery mode includes an economy mode, a sport mode, and a custom mode; and the correcting the first target deceleration by the corresponding energy recovery mode to obtain the second target deceleration includes: if the economy mode is executed, a negative correction value is used to correct the first target deceleration to maximize energy recovery of the vehicle; if the sport mode is executed, a positive correction value is used to correct the first target deceleration or the first target deceleration is kept unchanged; if the custom mode is executed, the first target deceleration is corrected in response to a recovery intensity level in the human-machine interaction module; the recovery intensity level is defined by a user through a center screen; a second data processing unit is configured to monitor a vehicle slip ratio in real time, adjust the second target deceleration to obtain a third target deceleration, and make the slip ratio in a preset slip ratio range; a control unit is configured to determine and adjust a recovery torque according to the third target deceleration and an actual deceleration by using a PI controller.

9. An electronic device, comprising: The electronic device includes a processor and a memory, and the memory stores at least one instruction or at least one program, which is loaded and executed by the processor to implement the energy recovery control method according to any one of claims 1-7.

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