Control method for thermal management system, electronic device, computer readable storage medium, and vehicle

Abstract

A control method for a thermal management system. The control method for the thermal management system comprises: identifying an operating mode of a vehicle (S1); determining a thermal management mode of the vehicle on the basis of the operating mode of the vehicle (S2); and controlling a corresponding component of the vehicle to operate on the basis of the confirmed thermal management mode (S3). Intelligent control of the vehicle thermal management system can be realized. The present invention further relates to an electronic device, a computer readable storage medium, and a vehicle.

Description

Control method of thermal management system, electronic device, computer-readable storage medium, and vehicle

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This disclosure claims priority to Chinese patent application number 202410071826.0, filed with the State Intellectual Property Office of China on January 18, 2024, entitled “Control method, electronic device, computer-readable storage medium and vehicle for thermal management system,” the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present disclosure relates to the field of vehicle technology, and in particular to a control method for a thermal management system, an electronic device, a computer-readable storage medium, and a vehicle. Background Art

[0004] With the rapid development of hybrid vehicles and the iterative advancement of related technologies, vehicle thermal management systems are facing even more severe challenges. Hybrid vehicle thermal management systems are characterized by large size, complex structure, and redundant functions. At the vehicle integrated control level, current research focuses on improving system architecture, assembly methods, component structure, and other aspects to enhance the inherent connections between components. At the vehicle control level, most approaches rely on engineers' experience to set parameter thresholds, then use simple logic to formulate centralized cooling methods or thermal management strategies to determine and control the entire vehicle.

[0005] In existing technologies, each vehicle's thermal management subsystem is independently controlled, resulting in a high degree of isolation. Current approaches cover a limited range of driving scenarios, fail to comprehensively consider the vehicle's economic efficiency and heat dissipation, and are detrimental to intelligent control of the vehicle's thermal management system. Furthermore, the experimental calibration required to obtain parameter thresholds is labor-intensive and time-consuming.

[0006] Public content

[0007] The present disclosure aims to solve at least one of the technical problems existing in the prior art. To this end, one purpose of the present disclosure is to provide a control method for a vehicle thermal management system, which can realize intelligent control of the vehicle thermal management system.

[0008] Another object of the present disclosure is to provide an electronic device.

[0009] Yet another object of the present disclosure is to provide a computer-readable storage medium.

[0010] Yet another object of the present disclosure is to provide a vehicle.

[0011] According to an embodiment of the present disclosure, a control method for a vehicle's thermal management system includes: identifying an operating mode of the vehicle; confirming a thermal management mode of the vehicle according to the operating mode of the vehicle; and controlling corresponding components of the vehicle to operate based on the confirmed thermal management mode.

[0012] Therefore, by setting up a control method for the vehicle's thermal management system, the corresponding components of the vehicle are controlled to operate based on the confirmed thermal management mode according to the vehicle's operating mode. In this way, the corresponding thermal management mode can be matched according to the different operating conditions of the vehicle, so that the economy and heat dissipation can be comprehensively considered, and the control intelligence of the thermal management system of the whole vehicle can be improved.

[0013] In some examples of the present disclosure, the operating mode of the vehicle includes energy-saving operating conditions, normal operating conditions and power operating conditions, and the thermal management mode of the vehicle includes economic mode, conventional mode and strong cooling mode. Confirming the thermal management mode of the vehicle according to the operating mode of the vehicle includes the following steps: when the operating mode of the vehicle is an energy-saving operating condition, confirming that the thermal management mode of the vehicle is an economic mode; when the operating mode of the vehicle is a normal operating condition, confirming that the thermal management mode of the vehicle is a conventional mode; and when the operating mode of the vehicle is a power operating condition, confirming that the thermal management mode of the vehicle is a strong cooling mode.

[0014] In some examples of the present disclosure, confirming the thermal management mode of the vehicle based on the operating mode of the vehicle also includes: simultaneously confirming the thermal management mode of the vehicle's engine thermal management system, the thermal management mode of the motor electronic control thermal management system, the thermal management mode of the battery thermal management system, and the thermal management mode of the air-conditioning system based on the operating mode of the vehicle.

[0015] In some examples of the present disclosure, the step of identifying the operating mode of the vehicle includes: identifying the driver's driving intention, confirming the power mode, collecting the vehicle's operating parameters, control parameters and temperature parameters at the current moment; and confirming the vehicle's operating mode based on the vehicle's operating parameters, control parameters and temperature parameters.

[0016] In some examples of the present disclosure, the step of controlling the corresponding components of the vehicle to operate based on the confirmed thermal management mode includes: controlling the electronic thermostat, electronic water pump, electronic fan, electronically controlled water pump and active air intake grille to operate based on the confirmed thermal management mode.

[0017] In some examples of the present disclosure, the step of controlling the corresponding components of the vehicle to operate based on the confirmed thermal management mode also includes: selecting optimal operating parameters of the corresponding components of the vehicle in an optimization solution database based on the confirmed thermal management mode of the vehicle, wherein the optimization solution database is created in advance; and controlling the corresponding components of the vehicle to operate according to the selected optimal operating parameters.

[0018] In some examples of the present disclosure, pre-creating the optimization solution database includes: establishing a high- and low-temperature cooling circuit coupling simulation model for the entire vehicle; selecting a variety of typical driving conditions, and based on the high- and low-temperature cooling circuit coupling simulation model for the entire vehicle, conducting simulation analysis under multiple conditions to obtain a simulation data set; cleaning and processing the simulation data set to obtain an input data set and an output data set; building a deep learning model, and in the deep learning model, setting training process parameters based on the input data set and the output data set, completing the training of the deep learning model, and obtaining a deep learning model with the highest prediction accuracy; randomly generating a large number of driving conditions, and based on the deep learning model with the highest prediction accuracy, obtaining the optimal control parameters under different thermal management modes of the vehicle with energy consumption and heat dissipation as optimization targets under each condition; and organizing the optimal control parameters corresponding to the different thermal management modes of the vehicle into the optimization solution database.

[0019] In some examples of the present disclosure, the input data set includes operating parameters and control parameters, and the output data set includes temperature parameters.

[0020] In some examples of the present disclosure, building a deep learning model includes: building a convolutional neural network model, a long short-term memory network model, a gated recurrent unit model, and a nonlinear mapping relationship model between learning input data and output data.

[0021] In some examples of the present disclosure, setting the training process parameters includes: setting activation function, loss function, optimization algorithm, number of iterations, learning rate and training set size parameters.

[0022] In some examples of the present disclosure, the randomly generating a large number of driving conditions includes: applying a Latin hypercube sampling method to the input data set and the output data set, randomly sampling within a valid range of each data set, and generating a large number of driving conditions.

[0023] In some examples of the present disclosure, the step of randomly generating a large number of driving conditions, taking energy consumption and heat dissipation as optimization targets under each condition, and obtaining the optimal control parameters under different thermal management modes of the vehicles also includes: taking energy consumption and heat dissipation as optimization targets under each condition, using a gradient optimization algorithm to perform multi-objective optimization, and obtaining the optimal control parameters under different thermal management modes of the vehicles.

[0024] According to the electronic device disclosed herein, the electronic device includes a processor and a memory, wherein the memory stores a vehicle control program, and the vehicle control program can be run on the processor. When the vehicle control program is executed by the processor, the control method of the vehicle thermal management system described above is implemented.

[0025] According to the computer-readable storage medium of the present disclosure, a vehicle control program is stored on the computer-readable storage medium. When the vehicle control program is executed by a processor, the above-mentioned control method of the vehicle thermal management system is implemented.

[0026] A vehicle according to the present disclosure includes the electronic device described above.

[0027] Additional aspects and advantages of the present disclosure will be given in part in the description that follows and, in part, will be obvious from the description that follows, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and / or additional aspects and advantages of the present disclosure will become apparent and readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0029] FIG1 is a flowchart of a method for controlling a thermal management system of a vehicle according to an embodiment of the present disclosure;

[0030] FIG2 is a partial flow chart of a control method of a thermal management system of a vehicle according to an embodiment of the present disclosure;

[0031] FIG3 is a partial flow chart of a control method of a thermal management system of a vehicle according to an embodiment of the present disclosure;

[0032] FIG4 is a partial flow chart of a control method of a thermal management system of a vehicle according to an embodiment of the present disclosure;

[0033] FIG5 is a partial flow chart of a control method of a thermal management system of a vehicle according to an embodiment of the present disclosure;

[0034] FIG6 is a schematic block diagram of an electronic device according to an embodiment of the present disclosure;

[0035] FIG7 is a schematic block diagram of a vehicle according to an embodiment of the present disclosure.

[0036] Reference numerals:

[0037] 1000, electronic device; 100, processor; 200, memory; vehicle, 2000. DETAILED DESCRIPTION

[0038] Embodiments of the present disclosure are described in detail below, and the embodiments described with reference to the accompanying drawings are exemplary.

[0039] A control method of a thermal management system of a vehicle according to an embodiment of the present disclosure will be described below with reference to FIG. 1 to FIG. 5 . The control method of the thermal management system of a vehicle can be applied to a vehicle.

[0040] 1 , the control method of the vehicle thermal management system according to the present disclosure may mainly include:

[0041] S1. Identify the vehicle's operating mode;

[0042] S2. confirming a thermal management mode of the vehicle according to an operating mode of the vehicle; and

[0043] S3. Control corresponding components of the vehicle to operate based on the confirmed thermal management mode.

[0044] Specifically, the control method of the thermal management system of the vehicle disclosed herein is set to identify the operating mode of the vehicle, so that the control method of the thermal management system of the vehicle can control the thermal management system of the entire vehicle according to the operating mode of the vehicle. In this way, the operating mode of the vehicle can be judged by the control method of the thermal management system of the vehicle, so that the control method of the thermal management system of the vehicle can control the thermal management system of the entire vehicle according to different operating modes of the vehicle.

[0045] Furthermore, the vehicle's thermal management system control method can determine the thermal management mode that matches the vehicle's operating mode based on the identified vehicle operating mode. Because the power and heat generated by a vehicle vary in different operating modes, different thermal management modes are matched to each operating mode. This allows for intelligent control of the vehicle's thermal management system by considering the vehicle's fuel economy and heat dissipation in each operating mode.

[0046] Furthermore, after the control method of the vehicle's thermal management system confirms the thermal management mode corresponding to the vehicle's operating mode, it issues instructions to the corresponding components involved in the thermal management system. Each corresponding component begins to operate according to the instructions of the vehicle's thermal management system control method to operate the thermal management mode confirmed by the vehicle's thermal management system control method, so that the thermal management mode of the entire vehicle performs heat management on the corresponding components in the vehicle under the vehicle's operating mode to cool overheated components and improve the heat dissipation effect of the entire vehicle, which is conducive to improving the vehicle's performance under the vehicle's operating mode. By matching the vehicle's operating mode with the corresponding thermal management mode through the vehicle's thermal management system control method, the driving scenarios covered by the vehicle's thermal management system control method can be increased. Taking the vehicle's economy and heat dissipation under the driving mode as the starting point, the vehicle's thermal management control mode can be optimized, thereby making the vehicle's thermal management system control method more intelligent.

[0047] Therefore, by setting up a control method for the vehicle's thermal management system, the corresponding components of the vehicle are controlled to operate based on the confirmed thermal management mode according to the vehicle's operating mode. In this way, the corresponding thermal management mode can be matched according to the different operating conditions of the vehicle, so that the economy and heat dissipation can be comprehensively considered, and the control intelligence of the thermal management system of the whole vehicle can be improved.

[0048] According to an embodiment of the present disclosure, the operating modes of the vehicle include energy-saving conditions, normal conditions and power conditions, and the thermal management modes of the vehicle include economic mode, conventional mode and strong cooling mode. Specifically, when the vehicle is operating under different operating conditions, the weights of economy and heat dissipation that need to be considered in vehicle operation are different. When the operating mode of the vehicle is energy-saving conditions, the requirements of the whole vehicle operation on fuel economy are higher than the requirements on heat dissipation. When the operating mode of the vehicle is normal conditions, the operation of the whole vehicle needs to consider fuel economy and heat dissipation at the same time. When the operating mode of the vehicle is power conditions, the requirements of the whole vehicle operation on heat dissipation are higher than the requirements on fuel economy.

[0049] Furthermore, the vehicle's thermal management mode provides three corresponding thermal management modes based on the vehicle's three operating conditions: energy-saving, normal, and power. These modes are economic, normal, and strong cooling. This allows the vehicle to operate in different thermal management modes to meet the vehicle's varying requirements for economy and heat dissipation during operation.

[0050] Furthermore, in combination with FIG1 and FIG2 , step S2 further includes the following steps:

[0051] S2-1. When the vehicle's operating mode is energy-saving, confirm that the vehicle's thermal management mode is economic mode;

[0052] S2-2. When the vehicle's operating mode is a normal operating condition, confirm that the vehicle's thermal management mode is a normal mode; and

[0053] S2-3. When the vehicle's operating mode is a power-type operating condition, confirm that the vehicle's thermal management mode is a strong cooling mode.

[0054] In the embodiment of the present disclosure, the thermal management mode of the vehicle in economic mode corresponds to the energy-saving operating condition of the vehicle, which can meet the minimum energy consumption requirement under the premise of meeting the heat dissipation performance of the vehicle. The thermal management mode of the vehicle in conventional mode corresponds to the ordinary operating condition of the vehicle, at which time the vehicle's requirements for energy consumption and heat dissipation are comprehensively balanced. The thermal management mode of the vehicle in strong cooling mode corresponds to the vehicle's operating dynamic operating condition, at which time the vehicle operation does not consider energy consumption restrictions but gives priority to ensuring that the thermal management system has sufficient safety margin. With such a setting, appropriate thermal management modes can be provided for the vehicle under different operating conditions according to the different driving needs of the user, so as to enhance the diversification of the control methods of the vehicle's thermal management system, thereby helping to improve the overall vehicle performance.

[0055] As shown in FIG1 and FIG2 , step S2 further includes:

[0056] S2-4. According to the vehicle's operating mode, simultaneously confirm the thermal management mode of the vehicle's engine thermal management system, the thermal management mode of the motor electronic control thermal management system, the thermal management mode of the battery thermal management system, and the thermal management mode of the air conditioning system.

[0057] Specifically, in an embodiment of the present disclosure, the thermal management system of the vehicle includes an engine thermal management system, a motor and electronic control thermal management system, a battery thermal management system and an air-conditioning system. Among them, the engine thermal management system can perform thermal management on the engine in the vehicle during operation, so that the engine can dissipate heat normally and ensure the working efficiency of the engine. The motor and electronic control thermal management system can perform thermal management on the motor and electronic control core components of the vehicle, so that the motor and electronic control core components in the vehicle can dissipate heat normally and ensure the working performance of the motor and electronic control. The battery thermal management system can perform thermal management on the battery in the vehicle to ensure the heat dissipation of the battery, thereby improving the battery performance, ensuring that the battery can supply power to the electrical components in the vehicle normally, and ensuring the battery's endurance. The air-conditioning system can perform thermal management on the vehicle's passenger compartment and the vehicle's functional components to achieve heat circulation for the entire vehicle.

[0058] After the control method of the vehicle's thermal management system confirms the vehicle's thermal management mode according to the vehicle's operating mode, the vehicle's engine thermal management system, motor electronic control thermal management system, battery thermal management system and air-conditioning system are simultaneously confirmed to perform integrated control of the vehicle's engine, motor electronic control, battery and air-conditioning. This can eliminate the control isolation of a single thermal management system and enhance the control effect of the entire vehicle.

[0059] As shown in FIG1 and FIG3 , step S1 further includes:

[0060] S1-1, identifying the driver's driving intention, confirming the power mode, and collecting the vehicle's current operating parameters, control parameters, and temperature parameters; and

[0061] S1-2. Confirming the vehicle's operating mode based on the vehicle's operating parameters, control parameters, and temperature parameters;

[0062] Specifically, when the control method of the vehicle's thermal management system identifies the vehicle's operating mode, it is necessary to first confirm the driver's driving intention to ensure that when the vehicle's thermal management system is controlled, the vehicle drives in accordance with the driver's driving intention. According to some embodiments of the present disclosure, before step S1-1, the control method of the vehicle's thermal management system can confirm the driver's driving intention and the power mode based on the vehicle's operating mode manually selected by the driver. When the driver manually selects the energy-saving mode, the vehicle's operating mode is an energy-saving condition; when the driver manually selects the normal mode, the vehicle's operating mode is a normal condition; when the driver manually selects the power mode, the vehicle's operating mode is a power condition.

[0063] According to other embodiments of the present disclosure, before step S1-1, when the driver has not manually selected the operating mode of the vehicle, the control method of the vehicle's thermal management system can confirm the driver's driving intention and the power mode based on the engine speed. When the engine speed is lower than a preset range, the control method of the vehicle's thermal management system identifies the vehicle's operating mode as an energy-saving condition. When the engine speed is within a preset range, the control method of the vehicle's thermal management system identifies the vehicle's operating mode as a normal condition. When the engine speed exceeds a preset range, the control method of the vehicle's thermal management system identifies the vehicle's operating mode as a dynamic condition. In an embodiment of the present disclosure, the preset range of the engine speed can be set according to different types of vehicles.

[0064] Furthermore, after the vehicle's thermal management system control method confirms the vehicle's power mode, it can collect the current vehicle operating parameters, control parameters, and temperature parameters. This allows thermal management of the vehicle's thermal management system based on the various parameters in the vehicle's current power mode. The vehicle's thermal management system control method can confirm the vehicle's current operating mode based on the current vehicle operating parameters, control parameters, and temperature parameters. Operating parameters include ambient temperature, vehicle speed, slope, intake air temperature, engine speed, engine torque, generator speed, generator torque, motor speed, motor torque, battery charge, and compressor power. Control parameters include electronic thermostat opening, electronic water pump speed, electronic fan speed, electronically controlled water pump speed, and active air intake grille opening. Temperature parameters include engine coolant temperature, generator temperature, motor temperature, generator IGBT temperature, motor IGBT temperature, battery temperature, and vehicle interior temperature.

[0065] As shown in FIG1 and FIG4 , step S3 includes:

[0066] S3-3, controlling the electronic thermostat, electronic water pump, electronic fan, electronically controlled water pump, and active air intake grille to operate based on the confirmed thermal management mode;

[0067] Specifically, the engine thermal management system manages engine thermal performance through the combined functions of an electronic thermostat, electronic water pump, electronic fan, and active air intake grille. The motor and electronic control thermal management system manages thermal performance of the motor and core electronic control components through the combined functions of a mechanical oil pump, electronic water pump, electronic fan, and active air intake grille. The battery thermal management system manages battery thermal performance through the electronic water pump. The air conditioning system regulates air conditioning through the combined functions of an electronic fan and active air intake grille.

[0068] Furthermore, after confirming the vehicle's thermal management mode, the vehicle's thermal management system control method controls the electronic thermostat, electronic water pump, electronic fan, electronically controlled water pump, and active air intake grille based on the confirmed vehicle thermal management mode. This allows for integrated control of the engine's thermal management system, the motor's electronically controlled thermal management system, the battery's thermal management system, and the air conditioning system, thereby enhancing overall vehicle control. In embodiments of the present disclosure, the vehicle's thermal management system includes, but is not limited to, subsystems such as the engine's thermal management system, the motor's electronically controlled thermal management system, the battery's thermal management system, and the air conditioning system.

[0069] As shown in FIG1 and FIG4 , step S3 includes:

[0070] S3-1. Based on the confirmed thermal management mode of the vehicle, selecting optimal operating parameters of corresponding components of the vehicle from an optimization solution database, wherein the optimization solution database is pre-created and used for rapid indexing in the optimization solution database according to the confirmed thermal management mode of the vehicle; and

[0071] S3-2. Control the corresponding components of the vehicle to operate according to the selected optimal operating parameters.

[0072] Specifically, the control method of the vehicle's thermal management system has a pre-created optimization solution database. After the control method of the vehicle's thermal management system controls the corresponding components of the vehicle to operate based on the confirmed thermal management mode, the control method of the vehicle's thermal management system can quickly index in the pre-created optimization solution database of the vehicle's corresponding components under different vehicle thermal management modes, so that after confirming the vehicle's thermal management mode, the optimal operating parameters of the vehicle's corresponding components can be quickly selected, including the optimal opening of the electronic thermostat, the optimal speed of the electronic water pump, the optimal speed of the electronic fan, the optimal speed of the electronically controlled water pump, and the optimal opening of the active air intake grille. In this way, the control method of the vehicle's thermal management system can control the engine's thermal management system, the motor's electronically controlled thermal management system, the battery thermal management system, and the air-conditioning system to operate according to the selected optimal operating parameters of the vehicle's corresponding components, thereby improving the operating speed of the vehicle's thermal management system control method and improving the efficiency of the vehicle's thermal management system.

[0073] As shown in FIG1 and FIG5 , the steps of pre-creating the optimization solution database include:

[0074] S3-3-1. Establish a coupled simulation model of high and low temperature cooling circuits for the entire vehicle;

[0075] S3-3-2. Select multiple typical driving conditions and conduct simulation analysis under multiple conditions based on the vehicle's high and low temperature cooling circuit coupling simulation model to obtain a simulation data set;

[0076] S3-3-3. Clean and process the simulation data set to obtain input data set and output data set;

[0077] S3-3-4. Build a deep learning model. In the deep learning model, set the training process parameters based on the input data set and the output data set, complete the training of the deep learning model, and obtain the deep learning model with the highest prediction accuracy;

[0078] S3-3-5. Randomly generate a large number of driving conditions and, based on the deep learning model with the highest prediction accuracy, obtain the optimal control parameters for different vehicle thermal management modes with energy consumption and heat dissipation as the optimization targets under each condition.

[0079] S3-3-6. Organize the optimal control parameters corresponding to the thermal management modes of different vehicles into an optimization solution database; and

[0080] S3-3-7. Based on the confirmed thermal management mode of the vehicle, the optimal operating parameters of the corresponding components of the vehicle are selected from the optimization solution database.

[0081] Specifically, the specific process of the control method of the vehicle's thermal management system for selecting the optimal operating parameters of the corresponding components of the vehicle based on the vehicle's thermal management mode includes steps S3-3-1 to S3-3-7. Among them, a high and low temperature cooling circuit coupling simulation model of the whole vehicle is established, including constructing a high and low temperature cooling circuit coupling simulation model of the whole vehicle for the engine thermal management system, the motor electronic control thermal management system, the battery thermal management system and the air-conditioning system. When conducting multi-condition simulation analysis on the vehicle, a variety of typical driving conditions can be selected, which is conducive to covering the vast majority of driving conditions and can save the time cost of the whole vehicle calibration test. In an embodiment of the present disclosure, the control method of the vehicle's thermal management system can carry out simulation analysis under multiple conditions based on the simulation model in step S3-1 to obtain a simulation data set.

[0082] Furthermore, for the simulation data set obtained in step S3-2, the required driving data can be extracted through data cleaning, and the driving data can be processed into matrix data form to obtain an input data set and an output data set. After obtaining these input data sets and output data, the control method of the vehicle's thermal management system can build a deep learning model. Compared with traditional machine learning models, deep learning models have higher accuracy. Deep learning models applied to the vehicle's thermal management system can automatically learn complex data features and reduce the need for manual feature engineering. In addition, deep learning models can also process large amounts of data and can be trained on distributed computing systems, making them scalable to large data sets. Based on the input data set and output data set in the deep learning model, the training process parameters can be set, and the training of the deep learning model is completed, so that the control method of the vehicle's thermal management system can obtain the deep learning model with the highest prediction accuracy, so that the vehicle's thermal management mode can select the optimal operating parameters of the corresponding components of the vehicle.

[0083] Furthermore, after training the deep learning model, the vehicle's thermal management system control method randomly generates a large number of driving conditions to cover the vast majority of driving conditions, which is beneficial to improving the control accuracy of the vehicle's thermal management system control method. Based on the deep learning model with the highest prediction accuracy obtained through training, the control parameters of different vehicle thermal management modes are obtained under each randomly generated driving condition. The obtained control parameters are the optimal control parameters obtained with energy consumption and heat dissipation as the optimization objectives, thereby improving the control accuracy of the vehicle's thermal management system control method for the engine thermal management system, motor electronic control thermal management system, battery thermal management system, and air conditioning system, which is beneficial to improving the operating performance of the vehicle's thermal management system. The control method of the vehicle's thermal management system in economy mode considers economy and heat dissipation with a weighting of 9:1, the control method of the vehicle's thermal management system in normal mode considers economy and heat dissipation with a weighting of 5:5, and the control method of the vehicle's thermal management system in strong cooling mode considers economy and heat dissipation with a weighting of 1:9.

[0084] Furthermore, after obtaining the corresponding optimal control parameters under the thermal management modes of different vehicles, these optimal control parameters can be organized into an optimization solution database, so that the control method of the vehicle's thermal management system can be quickly indexed in the optimization solution database according to the vehicle's thermal management mode and operating conditions. This allows the control method of the vehicle's thermal management system to quickly select the optimal operating parameters of the corresponding components of the vehicle under the thermal management mode of the corresponding vehicle for different driving conditions. In this way, the control method of the vehicle's thermal management system in the embodiment of the present disclosure can quickly obtain the optimal control solution based on the current driving conditions, with simple execution and efficient control.

[0085] As shown in FIG5 , the input data set in step S3-3-3 includes operating parameters and control parameters, and the output data set includes temperature parameters;

[0086] Specifically, the input data set used in training the deep learning model includes operating parameters and control parameters, and the output data set used in training the deep learning model includes temperature parameters. That is, the deep learning model built on the control method of the vehicle's thermal management system can be trained by using the simulation data obtained after conducting multi-operating condition simulation analysis.

[0087] Among them, the operating parameters include ambient temperature, vehicle speed, slope, intake temperature, engine speed, engine torque, electric motor speed, generator torque, motor speed, motor torque, battery power and compressor power, and other operating parameters of the engine, motor and electronic control core components, battery and air conditioning and other thermal management mode operating components; control parameters include electronic thermostat opening, electronic water pump speed, electronic fan speed, electronic water pump speed and active air intake grille opening, and other control parameters of the device with regulating and control functions in the vehicle's heat pipe system; temperature parameters include engine coolant temperature, generator temperature, motor temperature, generator insulated gate bipolar transistor temperature, motor insulated gate bipolar transistor temperature, battery temperature and vehicle interior temperature, and other temperature parameters controlled by the vehicle's thermal management system.

[0088] As shown in Figure 5, the steps of building a deep learning model also include:

[0089] Build convolutional neural network models, long short-term memory network models, gated recurrent unit models, and models that learn the nonlinear mapping relationship between input data and output data.

[0090] Specifically, the deep learning model used in the vehicle thermal management system control method is a neural network model. Deep neural networks offer high prediction accuracy and fast computational speed, improving not only the accuracy of the deep learning model but also the speed of its operation, thereby improving the control accuracy and operational rate of the vehicle thermal management system control method. In embodiments of the present disclosure, deep neural network models include, but are not limited to, convolutional neural network models, long short-term memory network models, gated recurrent unit models, and models that learn nonlinear mapping relationships between input and output data.

[0091] As shown in Figure 5, the training process parameter setting step includes setting the activation function, loss function, optimization algorithm, number of iterations, learning rate, and training set size parameters. Specifically, when training a deep learning model based on input and output datasets, it is necessary to set the training process parameters, including the activation function, loss function, optimization algorithm, number of iterations, learning rate, and training set size, to complete the training of the deep learning model and enable the vehicle thermal management system control method to obtain a model with the highest prediction accuracy.

[0092] As shown in Figure 5, the steps for randomly generating a large number of driving conditions include: applying the Latin Hypercube sampling method to the input and output datasets, randomly sampling within the valid range of each dataset to generate a large number of driving conditions. Specifically, the Latin Hypercube sampling method divides the sample space into several equally divided subintervals and then randomly selects a sample point within each subinterval. This ensures a uniform distribution of sample points along each dimension, effectively avoiding duplicate samples and sample clustering while maintaining randomness.

[0093] Furthermore, the Latin hypercube sampling method is used to randomly sample within the effective range of each data set, so that a large number of driving conditions generated in this way are random. When the deep learning model with the highest prediction accuracy is used and the control weight ratio of economy and heat dissipation is obtained by using energy consumption and heat dissipation under each working condition, it is not only beneficial to reduce the number of experiments carried out by the control method of the vehicle's thermal management system, saving acquisition time and cost, but also to avoid deviations and errors between the obtained results and the actual results of the vehicle, which is beneficial to improve the reliability and accuracy of the obtained results, thereby improving the control efficiency and effect of the vehicle's thermal management system control method on the vehicle's thermal management system under different thermal management modes.

[0094] According to some embodiments of the present application, step S3-3-5 further includes:

[0095] Taking energy consumption and heat dissipation as optimization targets under various working conditions, a gradient optimization algorithm is used to perform multi-objective optimization to obtain the optimal control parameters under the thermal management modes of different vehicles.

[0096] Specifically, the control method of the vehicle's thermal management system obtains the optimal control parameters under the thermal management mode of different vehicles through a gradient optimization algorithm. The gradient optimization algorithm has a fast convergence speed and high optimization efficiency, and can quickly obtain the optimal control parameters under the thermal management mode of different vehicles. Compared with the existing technology in which the whole vehicle calibration needs to rely on the experience of engineers, the gradient optimization algorithm used in the present disclosure can greatly save the time cost of the whole vehicle calibration test, thereby effectively improving the control efficiency of the control method of the vehicle's thermal management system.

[0097] According to an embodiment of the present disclosure, an electronic device 1000, as shown in FIG6 , may primarily include a processor 100 and a memory 200. The memory 200 stores a vehicle control program, which can be run on the processor 100. When the vehicle control program is executed by the processor, the vehicle thermal management system control method of the embodiment of the present disclosure is implemented. Thus, the vehicle control program stored in the memory 200 is applied to the processor 100. Under the processing of the processor 100, the vehicle control program can implement the vehicle thermal management system control method of the embodiment of the present disclosure. To reduce redundancy, this will not be further described here.

[0098] The vehicle 2000 according to the embodiment of the present disclosure, as shown in FIG7 , may mainly include the electronic device 1000 described above. This not only improves the intelligence and reliability of the vehicle 2000 , but also facilitates the user's driving and use of the vehicle 2000 .

[0099] According to the computer-readable storage medium (e.g., non-volatile computer-readable storage medium) of the embodiment of the present disclosure, a vehicle control program is stored thereon, and when the vehicle control program is executed by the processor, the control method of the vehicle thermal management system in the embodiment of the present disclosure is implemented.

[0100] According to an embodiment of the present disclosure, a control method for a vehicle's thermal management system is applicable to vehicle 2000. Vehicle 2000, which is equipped with the control method for a vehicle's thermal management system according to an embodiment of the present disclosure, sets three vehicle thermal management modes: economy, conventional, and strong cooling, to correspond to the vehicle's energy-saving, ordinary, and power-type operating conditions, and can provide a variety of thermal management control solutions. The control method for a vehicle's thermal management system according to an embodiment of the present disclosure combines the vehicle's engine thermal management system, motor electronic control thermal management system, battery thermal management system, and air conditioning system to achieve integrated control of the vehicle's thermal management subsystems. This can comprehensively consider the vehicle's economy and heat dissipation, and can enhance the control effect of the vehicle's thermal management.

[0101] Furthermore, in the embodiments of the present disclosure, the control method of the vehicle's thermal management system can realize multi-objective optimization of the vehicle's thermal management mode based on deep learning methods and gradient optimization methods, which comprehensively considers economy and heat dissipation, can improve algorithm optimization efficiency and save time costs.

[0102] In addition, in the embodiment of the present disclosure, the control method of the vehicle's thermal management system can form an optimization solution database, and embed the optimal control parameters of different operating conditions under different thermal management modes into the vehicle control solution in the form of a database, so that the control method of the vehicle's thermal management system can quickly obtain the optimal control solution based on the current driving conditions. This can make the control method of the vehicle's thermal management system in the embodiment of the present disclosure applicable to a variety of driving conditions and thermal management modes, thereby helping to reduce the complexity of the vehicle control system and making the control process of the vehicle's thermal management system simpler and more efficient.

[0103] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "circumferential", "radial", "circumferential" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation to the present disclosure.

[0104] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "example," "specific example," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0105] Although the embodiments of the present disclosure have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents.

Claims

1. A control method for a thermal management system of a vehicle, characterized in that, Including: Identifying the operation mode of the vehicle (S1); Confirming the thermal management mode of the vehicle according to the operation mode of the vehicle (S2); And Controlling the corresponding components of the vehicle to operate based on the confirmed thermal management mode (S3).

2. The control method of the thermal management system of the vehicle according to claim 1, characterized in that, The operation modes of the vehicle include an energy-saving working condition, a normal working condition, and a power working condition, and the thermal management modes of the vehicle include an economy mode, a conventional mode, and a strong cooling mode. Confirming the thermal management mode of the vehicle according to the operation mode of the vehicle (S2) includes the following steps: When the operation mode of the vehicle is the energy-saving working condition, confirming that the thermal management mode of the vehicle is the economy mode (S2-1); When the operation mode of the vehicle is the normal working condition, confirming that the thermal management mode of the vehicle is the conventional mode (S2-2); and When the operation mode of the vehicle is the power working condition, confirming that the thermal management mode of the vehicle is the strong cooling mode (S2-3).

3. The control method of the thermal management system of a vehicle according to claim 2, characterized in that, The confirming the thermal management mode of the vehicle according to the operation mode of the vehicle (S2) further includes: Simultaneously confirming the thermal management modes of the engine thermal management system, the motor and electronic control thermal management system, the battery thermal management system, and the air conditioning system of the vehicle according to the operation mode of the vehicle (S4).

4. The control method of the thermal management system of a vehicle according to any one of claims 1-3, characterized in that, The identifying the operation mode of the vehicle (S1) includes: Identifying the driving intention of the driver, confirming the power mode, and collecting the working condition parameters, control parameters, and temperature parameters of the vehicle at the current moment (S1-1); and Confirming the operation mode of the vehicle according to the working condition parameters, control parameters, and temperature parameters of the vehicle (S1-2).

5. The control method of the thermal management system of a vehicle according to any one of claims 1-4, characterized in that, The controlling the corresponding components of the vehicle to operate based on the confirmed thermal management mode (S3) includes: Controlling the electronic thermostat, the electronic water pump, the electronic fan, the electronic control water pump, and the active intake grille to operate based on the confirmed thermal management mode (S3-3).

6. The control method of the thermal management system of a vehicle according to any one of claims 1-5, characterized in that, The controlling the corresponding components of the vehicle to operate based on the confirmed thermal management mode (S3) includes: Selecting the optimal operation parameters of the corresponding components of the vehicle from an optimization solution database based on the confirmed thermal management mode of the vehicle, where the optimization solution database is pre-created; and Controlling the corresponding components of the vehicle to operate according to the selected optimal operation parameters (S3-2).

7. The control method of the thermal management system of a vehicle according to claim 6, wherein Pre-creating the optimization solution database includes: Establishing a coupled simulation model of the vehicle's high and low temperature cooling circuits (S3-3-1); Selecting a variety of typical driving conditions, and based on the coupled simulation model of the vehicle's high and low temperature cooling circuits, carrying out simulation analysis under multiple conditions to obtain a simulation data set (S3-3-2); Cleaning and processing the simulation data set to obtain an input data set and an output data set (S3-3-3); Building a deep learning model, setting training process parameters in the deep learning model based on the input data set and the output data set, completing the training of the deep learning model, and obtaining the deep learning model with the highest prediction accuracy (S3-3-4); Randomly generate a large number of driving conditions. Based on the deep learning model with the highest prediction accuracy, take energy consumption and heat dissipation as the optimization objectives under each condition to obtain the optimal control parameters under different thermal management modes of the vehicle (S3-3-5); and Sort out the optimal control parameters corresponding to different thermal management modes of the vehicle into the optimization scheme database (S3-3-6).

8. The control method of the thermal management system of a vehicle according to claim 7, characterized in that, The input data set includes condition parameters and control parameters, and the output data set includes temperature parameters.

9. The control method of the thermal management system of a vehicle according to claim 7 or 8, characterized in that, The building of the deep learning model includes: Build a convolutional neural network model, a long short-term memory network model, a gated recurrent unit model, and a model for learning the non-linear mapping relationship between input data and output data.

10. The control method of the thermal management system of a vehicle according to any one of claims 7-9, characterized in that, The setting of the training process parameters includes: setting the activation function, loss function, optimization algorithm, number of iteration steps, learning rate, and training set size parameters.

11. The control method of the thermal management system of a vehicle according to any one of claims 7-10, characterized in that, The randomly generating a large number of driving conditions includes: Adopt the Latin hypercube sampling method for the input data set and the output data set, randomly sample within the effective range of each data set to generate a large number of driving conditions.

12. The control method of the thermal management system of a vehicle according to any one of claims 7-11, characterized in that, The randomly generating a large number of driving conditions, based on the deep learning model with the highest prediction accuracy, taking energy consumption and heat dissipation as the optimization objectives under each condition to obtain the optimal control parameters under different thermal management modes of the vehicle (S3-3-5) further includes: Taking energy consumption and heat dissipation as the optimization objectives under each condition, use a gradient-based optimization algorithm for multi-objective optimization to obtain the optimal control parameters under different thermal management modes of the vehicle.

13. An electronic device (1000), characterized in that, Comprising: A processor (100); And A memory (200), on which a control program of the vehicle is stored. The control program of the vehicle can run on the processor (100), and when the control program of the vehicle is executed by the processor (100), it realizes the control method of the thermal management system of the vehicle as described in any one of claims 1-12.

14. A computer-readable storage medium, characterized in that, A control program of the vehicle is stored on the computer-readable storage medium, and when the control program is executed by the processor, it realizes the control method of the thermal management system of the vehicle as described in any one of claims 1-12.

15. A vehicle (2000), characterized in that, Including the electronic device (1000) according to claim 14.

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