Thermal management control methods, devices, electronic equipment, and computer-readable storage media

Abstract

This application relates to the field of automotive technology and provides a thermal management control method, device, electronic device, and computer-readable storage medium. The method includes: acquiring current driving habit information, the current external ambient temperature of the vehicle, the component temperature of each component in the current electric drive circuit, and the current coolant temperature of the electric drive circuit; determining the cooling value of the current electric drive circuit based on the current driving habit information, the current external ambient temperature, the current component temperature, and the current coolant temperature of the electric drive circuit; determining target adjustment parameters based on a preset cooling level corresponding to the current cooling value; and adjusting the water pump duty cycle, the active grille opening, and the cooling fan duty cycle according to the target adjustment parameters. The thermal management control method provided by this application can cool the electric drive circuit before it reaches a high temperature, thereby maintaining the temperature of the electric drive circuit within a relatively low range and matching the different thermal management requirements of the electric drive circuit corresponding to different driving styles.

Description

Technical Field

[0001] This application relates to the field of automotive technology, and in particular to a thermal management control method, device, electronic device, and computer-readable storage medium. Background Technology

[0002] In existing technologies, the thermal management system for the electric drive circuit of new energy vehicles detects the real-time temperature of relevant components in the vehicle to determine the corresponding thermal management control method and control the thermal management system to cool the electric drive circuit. However, during actual driving, the temperature of the electric drive circuit exhibits a cumulative effect; the detected temperature gradually increases and then gradually decreases, without rapid cooling after the initial cooling process. If the real-time temperature of relevant components is used as the detection standard, the temperature of the electric drive circuit will remain above normal for a period of time, posing a risk of overheating and compromising driving safety. Summary of the Invention

[0003] In view of this, embodiments of this application provide a thermal management control method, apparatus, electronic device, and computer-readable storage medium to solve the problem of cooling the electric drive circuit after the temperature of the electric drive circuit rises in the prior art.

[0004] A first aspect of this application provides a thermal management control method, including:

[0005] Acquire information on current driving habits, the current external ambient temperature of the vehicle, the component temperature of each part in the current electric drive circuit, and the current water temperature of the electric drive circuit;

[0006] Based on current driving habits, current ambient temperature, current temperature of each component, and current water temperature of the electric drive circuit, determine the current cooling value of the electric drive circuit.

[0007] Determine the target adjustment parameters based on the preset cooling level corresponding to the current cooling value;

[0008] Adjust the water pump duty cycle, active air intake grille opening, and cooling fan duty cycle according to the target parameters.

[0009] A second aspect of this application provides a thermal management control device, comprising:

[0010] The acquisition module is configured to acquire current driving habit information, the current external ambient temperature of the vehicle, the component temperature of each component in the current electric drive circuit, and the current water temperature of the electric drive circuit.

[0011] The determination module is configured to determine the cooling value of the current electric drive circuit based on current driving habit information, current external ambient temperature, current temperature of each component, and current electric drive circuit water temperature.

[0012] The processing module is configured to determine the target adjustment parameters based on the preset cooling level corresponding to the current cooling value;

[0013] The adjustment module is configured to adjust the water pump duty cycle, active air intake grille opening, and cooling fan duty cycle according to the target adjustment parameters.

[0014] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0015] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0016] The beneficial effects of this application's embodiments compared to existing technologies are as follows: It acquires current driving habit information, the current external ambient temperature of the vehicle, the component temperature of each part of the current electric drive circuit, and the current water temperature of the electric drive circuit. Based on this information, it determines the cooling value of the current electric drive circuit and the corresponding preset cooling level. It then determines target adjustment parameters based on the preset cooling level and adjusts the water pump duty cycle, active grille shutter opening, and cooling fan duty cycle according to these parameters. Through the thermal management control method provided in this application, it is possible to determine the temperature change of the electric drive circuit based on the user's driving habit data and the real-time temperature of relevant components, and determine the cooling level of the electric drive circuit and the corresponding target adjustment parameters for the water pump speed duty cycle, active grille shutter opening, and cooling fan speed duty cycle. This allows for cooling of the electric drive circuit before it reaches a high temperature, maintaining the temperature within a relatively low range, thereby matching the different thermal management needs of the electric drive circuit corresponding to different driving styles and improving driving safety. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an electric drive circuit provided in an embodiment of this application;

[0019] Figure 2This is a schematic flowchart of a thermal management control method provided in an embodiment of this application;

[0020] Figure 3 A schematic diagram of a PID control function provided in an embodiment of this disclosure;

[0021] Figure 4 This is a flowchart illustrating a method for determining a preset cooling level and target adjustment parameters provided in an embodiment of this application;

[0022] Figure 5 This is a schematic diagram of a thermal management control provided in an embodiment of this application;

[0023] Figure 6 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0024] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0025] A thermal management control method and apparatus according to embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0026] Figure 1 This is a schematic diagram of an electric drive circuit provided in an embodiment of this application. For example... Figure 1 As shown, the coolant temperature of the electric drive circuit (also referred to as the electric drive circuit water temperature in this application) is reduced by the active air intake grille, cooling fan, and low-temperature radiator. The cooled coolant is then transferred to the water pump of the electric drive circuit. The water pump controls the coolant flow rate to cool the DC / DC converter, the on-board charger (OBC), the front motor, and the rear motor. During the cooling of the electric drive circuit, the coolant temperature rises and is further reduced by the active air intake grille, cooling fan, and low-temperature radiator, forming a circulating cooling loop. An electric drive circuit water temperature sensor is installed before cooling the coolant to obtain the electric drive circuit water temperature.

[0027] Figure 2 This is a schematic flowchart of a thermal management control method provided in an embodiment of this application. Figure 2 As shown, the thermal management control method includes the following steps:

[0028] S201, obtain current driving habit information, current vehicle external ambient temperature, component temperature of each component in the current electric drive circuit, and current electric drive circuit water temperature;

[0029] S202, based on current driving habit information, current external ambient temperature, current temperature of each component, and current electric drive circuit water temperature, determines the current cooling value of the electric drive circuit;

[0030] S203, determine the target adjustment parameters based on the preset cooling level corresponding to the current cooling value;

[0031] S204, adjust the water pump duty cycle, active air intake grille opening and cooling fan duty cycle according to the target adjustment parameters.

[0032] In some embodiments, the user's driving habit information is obtained by collecting the vehicle's external ambient temperature, the component temperature of each part of the electric drive circuit, and the current water temperature of the electric drive circuit from the vehicle's temperature sensor.

[0033] Among them, driving habit information includes average energy consumption E User Average vehicle speed V User accelerator pedal change rate E ArPd Specifically, this refers to the average energy consumption, average vehicle speed, and current accelerator pedal change rate during the vehicle's current driving process, from the start of driving to the current time range.

[0034] The temperature of each component in the electric drive circuit includes the temperature of the DC / DC converter, the temperature of the on-board charger (OBC), the temperature of the front motor, and the temperature of the rear motor.

[0035] Based on current driving habits, current ambient temperature, current temperature of each component, and current electric drive circuit coolant temperature, the current cooling value of the electric drive circuit is determined. The cooling value of the electric drive circuit is compared with the preset cooling level to determine the cooling level corresponding to the current cooling value of the electric drive circuit and the target adjustment parameters corresponding to the cooling level. The water pump duty cycle, active air intake grille opening, and cooling fan duty cycle are adjusted according to the target adjustment parameters.

[0036] According to the technical solution provided in the embodiments of this application, the corresponding preset cooling level can be determined based on the current driving habit information, ambient temperature, temperature of each component and current electric drive circuit water temperature. Adjustment parameters are determined based on the cooling level to cool the electric drive circuit before it reaches a higher temperature, thereby maintaining the temperature of the electric drive circuit within a relatively low range. This can match the different electric drive circuit thermal management requirements corresponding to different driving styles and improve driving safety.

[0037] In some embodiments, the cooling value of the current electric drive circuit is determined based on current driving habit information, current ambient temperature, current temperature of each component, and current electric drive circuit coolant temperature, including:

[0038] The current driving habits, external ambient temperature, temperature of each component, and water temperature of the electric drive circuit are input into a pre-trained cooling value neural network model to obtain the current cooling value of the electric drive circuit output by the cooling value neural network model.

[0039] The cooling value of the current electric drive circuit is determined by a pre-trained cooling value neural network model. The cooling value neural network model includes an input layer, a hidden layer, and an output layer. The current driving habit information, external temperature environment, temperature of each component, and water temperature of the electric drive circuit are used as input layers, and the cooling value is used as the output layer.

[0040] In one exemplary embodiment, the specific input data of the input layer can be: average energy consumption E User Average vehicle speed V User accelerator pedal change rate E ArPd External ambient temperature T em DC / DC current temperature T DC / DC OBC current temperature T OBC Current temperature T of the front motor FMot The current temperature T of the rear motor RMot Electric drive circuit water temperature T ed .

[0041] According to the technical solution provided in the embodiments of this application, the cooling value is obtained through a cooling value neural network model, which can accurately and quickly determine the corresponding cooling value based on the current state of the vehicle, thereby determining the adjustment parameters.

[0042] In some embodiments, the pre-training process of the cooling value neural network model includes:

[0043] The highest temperature threshold for each component is obtained. The components include the current converter, the on-board charger, the front motor of the vehicle, and the rear motor of the vehicle.

[0044] Cooling is performed on each component based on the test cooling value. When each component does not exceed the corresponding maximum temperature threshold, the corresponding test driving habit information, the temperature of each test component, the water temperature of the test electric drive circuit and the test external ambient temperature are recorded.

[0045] The test driving habit information, the temperature of each test component, the external ambient temperature, the water temperature of the test electric drive circuit, and the test cooling value are determined as the input data of the training sample, and the corresponding test cooling value is determined as the output data of the training sample.

[0046] The cooling value neural network model was trained using training samples.

[0047] Determine the maximum temperature thresholds for DC / DC, OBC, front motor, and rear motor in the electric drive circuit. Using the standard that each component does not exceed the maximum temperature threshold, cool each component according to the test cooling value, and record the test driving habit information, temperature of each test component, water temperature of the test electric drive circuit, and test external ambient temperature corresponding to each test cooling value.

[0048] The test data is obtained through system testing or simulation. The method for determining the test data can be to control one or more of the following variables: average energy consumption, average vehicle speed, and the rate of change of the user's accelerator pedal. The standard is that each component does not exceed the maximum temperature threshold, while keeping other quantities constant or controlling the changes of other quantities within a preset range, and then conducting the test.

[0049] For example, the test data settings can correspond to the situation of "rapid acceleration and rapid deceleration", that is, recording various data while controlling the rate of change of the accelerator pedal at a high level and keeping the average vehicle speed and average energy consumption within the normal range. Alternatively, they can correspond to the situation of "gradual acceleration and gradual deceleration", that is, recording various data while controlling the rate of change of the accelerator pedal at a low level and keeping the average vehicle speed and average energy consumption within the normal range. The test data can also be recorded under conditions such as "high-speed driving", "idling driving", "high temperature environment", and "low temperature environment".

[0050] The recorded information on driving habits during each test, the temperature of each test component, the external ambient temperature, the water temperature of the electric drive circuit, and the test cooling value are determined as the input data for the training samples and input into the cooling value neural network model. At the same time, the corresponding preset cooling value is input into the input layer, and the cooling value neural network model is trained with the preset cooling value as the training target.

[0051] According to the technical solution provided in the embodiments of this application, a cooling value neural network model can be trained by experimental data and preset cooling values, so that the cooling value neural network model can output the corresponding cooling value when it receives current driving habit information, current external ambient temperature, current component temperature and current electric drive circuit water temperature.

[0052] In some embodiments, after training the cooling value neural network model is completed, the method further includes:

[0053] All test cooling values ​​are arranged from smallest to largest. Based on all the arranged test cooling values, multiple cooling value intervals are divided, and each cooling value interval corresponds to a preset cooling level.

[0054] In an exemplary embodiment of this disclosure, the cooling value is expressed as L. VUserThere are 11 preset cooling values. The preset cooling values ​​are sorted in ascending order. The first preset cooling value is set to 0. The second to eleventh preset cooling values ​​are named K1-K10 in sequence. Multiple cooling value intervals are divided into 0-K10, and each cooling value interval corresponds to a preset cooling level.

[0055] The method for determining the preset cooling level by dividing the cooling value range into multiple ranges is as follows:

[0056] When L VUser When L ≤ 0, the corresponding preset cooling level is the first preset cooling level, and 0 < L VUser When K1 ≤ L, the corresponding preset cooling level is the second preset cooling level; when K1 < L VUser When K2 ≤ L, the corresponding preset cooling level is the third preset cooling level; when K2 < L VUser When K3 ≤ L, the corresponding preset cooling level is the fourth preset cooling level; when K3 < L, the preset cooling level is... VUser When K is ≤10, the corresponding preset cooling level is the fifth preset cooling level.

[0057] Where 0 represents that the current water temperature of the electric drive circuit is within the preset range and there is no cooling requirement.

[0058] According to the technical solution provided in the embodiments of this application, the preset cooling level corresponding to each cooling value is defined, and the target adjustment parameter is determined according to the preset cooling level. This can cool down the electric drive circuit in advance, prevent the components in the electric drive circuit from overheating, and improve the safety of vehicle driving.

[0059] In some embodiments, determining the cooling value of the current electric drive circuit based on current driving habit information, current ambient temperature, current temperature of each component, and water temperature of the electric drive circuit further includes:

[0060] The current driving habits, external ambient temperature, temperature of each component, and coolant temperature of the electric drive circuit are used to obtain the current cooling value of the electric drive circuit from the output of the PID control function through a pre-trained PID (Proportion Integration Differentiation) control function.

[0061] Figure 3 This is a schematic diagram of a PID control function provided in an embodiment of the present disclosure, as shown below. Figure 3 As shown, the PID control function consists of a proportional unit (P), an integral unit (I), and a derivative unit (D).

[0062] The process of pre-training the PID control function is as follows: input experimental data or simulation data into the PID control function, compare the output result of the PID control function with the preset cooling value corresponding to the experimental data or simulation data, and adjust the parameters of the PID control function until the output corresponding to the experimental data or simulation data input into the PID control function corresponds one-to-one with the preset cooling value.

[0063] The current driving habits, ambient temperature, temperature of each component, and coolant temperature of the electric drive circuit are input to a pre-trained PID control function. The output of the PID control function determines the current cooling value of the electric drive circuit. Based on the range of this cooling value, a preset cooling level is determined. Target adjustment parameters are then established according to this preset cooling level to adjust the water pump duty cycle, active grille opening, and cooling fan duty cycle. The current cooling value of the electric drive circuit is used as the controlled object of the PID control function.

[0064] According to the technical solution provided in the embodiments of this application, a method for determining a preset cooling level through a PID control function is provided. This method can output a corresponding cooling value based on current driving habit information, current external ambient temperature, current component temperature, and current electric drive circuit water temperature, so as to determine the target adjustment parameters of water pump duty cycle, active air intake grille opening, and cooling fan duty cycle, and cool the electric drive circuit water temperature.

[0065] In some embodiments, in each preset cooling level, the priority of the water pump duty cycle is higher than the priority of the active air intake grille opening, and the priority of the active air intake grille opening is higher than the priority of the cooling fan duty cycle.

[0066] According to the preset order from smallest to largest, the priority of adjusting the water pump duty cycle is higher than the priority of adjusting the active air intake grille opening, which is higher than the priority of adjusting the cooling fan duty cycle. That is, after the water pump duty cycle is adjusted to 100%, the active air intake grille opening is adjusted, and so on, until the active air intake grille opening reaches 100%, and then the cooling fan duty cycle is adjusted.

[0067] Figure 4 This is a flowchart illustrating a method for determining a preset cooling level and target adjustment parameters provided in an embodiment of this application. Figure 4 As shown, with the water pump duty cycle being D pmp Cooling fan duty cycle D fan Active grille opening P ags For example, let's illustrate this:

[0068] a. When L VUser When the current cooling level of the electric drive circuit is ≤0, that is, when the cooling level of the electric drive circuit is the first preset cooling level, the water pump duty cycle D of the electric drive circuit is... pmpThe target adjustment parameter is 0%, and the active grille opening P ags The target adjustment parameters are 0% and the cooling fan duty cycle D. fan The target adjustment parameter is 0%;

[0069] b. When 0 < L VUser When K1 is less than or equal to the second preset cooling level of the current electric drive circuit, the water pump duty cycle D is... pmp The target adjustment parameters are Dp1 and active grille opening P. ags The target adjustment parameters are 0% and the cooling fan duty cycle D. fan The target adjustment parameter is 0%;

[0070] c. When K1 < LvUser ≤ K2, that is, when the current cooling level of the electric drive circuit is the third preset cooling level, the water pump duty cycle D pmp The target adjustment parameters are Dp2 and active grille opening P. ags The target adjustment parameters are 100% and the cooling fan duty cycle D. fan The target adjustment parameter is 0%;

[0071] d. When K2 < L VUser When K3 is ≤, that is, when the current cooling level of the electric drive circuit is the fourth preset cooling level, the water pump duty cycle D pmp The target adjustment parameter is 100%, and the active grille opening P ags The target adjustment parameters are 100% and the cooling fan duty cycle D. fan The target adjustment parameter is 50%;

[0072] e. When K3 < L VUser When K10 is ≤, that is, when the current cooling level of the electric drive circuit is the fifth preset cooling level, the water pump duty cycle D pmp The target adjustment parameter is 100%, and the active grille opening P ags The target adjustment parameters are 100% and the cooling fan duty cycle D. fan The target adjustment parameter is 100%.

[0073] Among the preset cooling levels, there are three different target adjustment parameters for the water pump duty cycle: Dp1, Dp2, and 100%. The specific values ​​for Dp1 and Dp2 can be set by dividing 100% equally, i.e., Dp1 is 1 / 3 of 100%, and Dp2 is 2 / 3 of 100%. After the water pump duty cycle is adjusted to 100%, the active air intake grille opening can be dynamically adjusted based on the current cooling value and the active air intake grille opening corresponding to the preset cooling value, but not exceeding the target adjustment parameters described above. The target adjustment parameters for the cooling fan duty cycle are similar.

[0074] According to the technical solution provided in the embodiments of this application, it is possible to meet the cooling requirements of each component at various temperatures while matching different driving styles, such as the thermal management requirements of different electric drive circuits corresponding to driving styles such as "emergency braking" and "rapid acceleration", which is in line with driving habit information and can better protect the safety of the vehicle.

[0075] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0076] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0077] Figure 5 This is a schematic diagram of a thermal management control provided in an embodiment of this application. For example... Figure 5 As shown, the thermal management control device includes: an acquisition module 501, a determination module 502, a processing module 503, and an adjustment module 504.

[0078] The acquisition module 501 is configured to acquire current driving habit information, current external ambient temperature of the vehicle, component temperature of each component in the current electric drive circuit, and current water temperature of the electric drive circuit.

[0079] The determination module 502 is configured to determine the cooling value of the current electric drive circuit based on current driving habit information, current external ambient temperature, current temperature of each component, and current electric drive circuit water temperature.

[0080] Processing module 503 is configured to determine target adjustment parameters based on a preset cooling level corresponding to the current cooling value;

[0081] The adjustment module 504 is configured to adjust the water pump duty cycle, the active air intake grille opening, and the cooling fan duty cycle according to the target adjustment parameters.

[0082] In some embodiments, the determining module is configured to determine the cooling value of the current electric drive circuit based on current driving habit information, current ambient temperature, current temperature of each component, and current electric drive circuit coolant temperature, for the purpose of:

[0083] The current driving habits, external ambient temperature, temperature of each component, and water temperature of the electric drive circuit are input into a pre-trained cooling value neural network model to obtain the current cooling value of the electric drive circuit output by the cooling value neural network model.

[0084] In some embodiments, the determination module is configured to cool the pre-training process of the value neural network model:

[0085] The highest temperature threshold for each component is obtained. The components include the current converter, the on-board charger, the front motor of the vehicle, and the rear motor of the vehicle.

[0086] Cooling is performed on each component based on the test cooling value. When each component does not exceed the corresponding maximum temperature threshold, the corresponding test driving habit information, the temperature of each test component, the water temperature of the test electric drive circuit and the test external ambient temperature are recorded.

[0087] The test driving habit information, the temperature of each test component, the external ambient temperature, the water temperature of the test electric drive circuit, and the test cooling value are determined as the input data of the training sample, and the corresponding test cooling value is determined as the output data of the training sample.

[0088] The cooling value neural network model was trained using training samples.

[0089] In some embodiments, after the determining module is configured to complete training of the cooling value neural network model, it is further configured to:

[0090] All test cooling values ​​are arranged from smallest to largest. Based on all the arranged test cooling values, multiple cooling value intervals are divided, and each cooling value interval corresponds to a preset cooling level.

[0091] In some embodiments, driving habit information includes average energy consumption, average vehicle speed, and accelerator pedal change rate.

[0092] In some embodiments, the determining module is configured to determine the current cooling value of the electric drive circuit based on current driving habit information, current ambient temperature, current temperature of each component, and water temperature of the electric drive circuit, and is further configured to:

[0093] The current driving habits, ambient temperature, temperature of each component, and coolant temperature of the electric drive circuit are used to obtain the current cooling value of the electric drive circuit output by the PID control function through a pre-trained PID control function.

[0094] In some embodiments, in each preset cooling level, the priority of the water pump duty cycle is higher than the priority of the active air intake grille opening, and the priority of the active air intake grille opening is higher than the priority of the cooling fan duty cycle.

[0095] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0096] Figure 6 This is a schematic diagram of the electronic device 6 provided in an embodiment of this application. Figure 6As shown, the electronic device 6 of this embodiment includes a processor 601, a memory 602, and a computer program 603 stored in the memory 602 and executable on the processor 601. When the processor 601 executes the computer program 603, it implements the steps in the various method embodiments described above. Alternatively, when the processor 601 executes the computer program 603, it implements the functions of each module / unit in the various device embodiments described above.

[0097] Electronic device 6 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 6 may include, but is not limited to, processor 601 and memory 602. Those skilled in the art will understand that... Figure 6 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or different components.

[0098] The processor 601 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0099] The memory 602 can be an internal storage unit of the electronic device 6, such as a hard disk or RAM of the electronic device 6. The memory 602 can also be an external storage device of the electronic device 6, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 6. The memory 602 can also include both internal and external storage units of the electronic device 6. The memory 602 is used to store computer programs and other programs and data required by the electronic device.

[0100] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), or a random access memory (RAM). The content contained in a computer-readable medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, a computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0102] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A thermal management control method, characterized in that, include: Acquire information on current driving habits, the current external ambient temperature of the vehicle, the component temperature of each part in the current electric drive circuit, and the current water temperature of the electric drive circuit; Based on the current driving habit information, the current external ambient temperature, the current temperature of each component, and the current water temperature of the electric drive circuit, the current cooling value of the electric drive circuit is determined through a pre-trained cooling value neural network model or a pre-trained PID control function. Based on the preset cooling level corresponding to the current cooling value, determine the target adjustment parameters; Adjust the water pump duty cycle, active air intake grille opening, and cooling fan duty cycle according to the target parameters. The neural network model and the PID control function are obtained through pre-training using experimental data. The process of determining the experimental data includes: One or more of the driving habit information are controlled as variables, with each component not exceeding the maximum temperature threshold as the standard, while keeping other quantities in the driving habit information unchanged or controlling the changes of other quantities within a preset range. The test is conducted and the relevant data of the vehicle are recorded as test data. The driving habit information includes average energy consumption, average vehicle speed and accelerator pedal change rate.

2. The method according to claim 1, characterized in that, The pre-training process of the cooling value neural network model includes: The highest temperature threshold corresponding to each of the components is obtained, including the current converter, the on-board charger, the front motor of the vehicle, and the rear motor of the vehicle. Cooling is performed on each component based on the test cooling value. When each component does not exceed the corresponding maximum temperature threshold, the corresponding test driving habit information, the temperature of each test component, the water temperature of the test electric drive circuit and the test external ambient temperature are recorded. The test driving habit information, the temperature of each test component, the test external ambient temperature, the test electric drive circuit water temperature, and the test cooling value are determined as the input data of the training sample, and the corresponding test cooling value is determined as the output data of the training sample. The cooling value neural network model is trained using the training samples.

3. The method according to claim 2, characterized in that, After training the cooling value neural network model, the process also includes: All the test cooling values ​​are arranged from smallest to largest, and multiple cooling value intervals are divided based on all the arranged test cooling values. Each cooling value interval corresponds to a preset cooling level.

4. The method according to claim 1, characterized in that, The driving habit information includes average energy consumption, average vehicle speed, and accelerator pedal change rate.

5. The method according to any one of claims 1 to 4, characterized in that, In each of the preset cooling levels, the priority of the water pump duty cycle is higher than the priority of the active air intake grille opening, and the priority of the active air intake grille opening is higher than the priority of the cooling fan duty cycle.

6. A thermal management control device, characterized in that, include: The acquisition module is configured to acquire current driving habit information, the current external ambient temperature of the vehicle, the component temperature of each component in the current electric drive circuit, and the current water temperature of the electric drive circuit. The determination module is configured to determine the cooling value of the electric drive circuit based on the current driving habit information, the current external ambient temperature, the current temperature of each component, and the current water temperature of the electric drive circuit, through a pre-trained cooling value neural network model or a pre-trained PID control function. The processing module is configured to determine the target adjustment parameters based on the preset cooling level corresponding to the current cooling value; The adjustment module is configured to adjust the water pump duty cycle, the active air intake grille opening, and the cooling fan duty cycle according to the target adjustment parameters. The neural network model and the PID control function are obtained through pre-training using experimental data. The process of determining the experimental data includes: One or more of the driving habit information are controlled as variables, with each component not exceeding the maximum temperature threshold as the standard, while keeping other quantities in the driving habit information unchanged or controlling the changes of other quantities within a preset range. The test is conducted and the relevant data of the vehicle are recorded as test data. The driving habit information includes average energy consumption, average vehicle speed and accelerator pedal change rate.

7. An electronic 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, it implements the steps of the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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