New energy automobile thermal management system test method

Abstract

The invention discloses a new energy automobile thermal management system test method, which comprises the steps of simulating working condition data corresponding to a current working condition, and inputting the working condition data into a new energy automobile thermal management system; cooling liquid inlet and outlet temperatures corresponding to M water pumps in the new energy automobile thermal management system are collected; the working condition data and the cooling liquid inlet and outlet temperatures corresponding to the M water pumps are sequentially input into a trained heat management model, so that the optimal duty ratios corresponding to the M water pumps under the current working condition are obtained; and actual duty ratios corresponding to the M water pumps in the new energy automobile thermal management system are collected in real time, the actual duty ratios corresponding to the M water pumps are compared with the optimal duty ratio, and the water pumps with the duty ratios needing to be adjusted and optimized are determined. According to the new energy automobile thermal management system test method, the performance of the thermal management system can be optimized conveniently, and the energy efficiency and reliability of the new energy automobile are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and particularly to a test method for the thermal management system of new energy vehicles. Background Art

[0002] In the development process of new energy vehicles, the thermal management system plays a crucial role in ensuring the performance, safety, and service life of core components such as batteries and motors. Since the heat generation of batteries and motors varies greatly under different working conditions of new energy vehicles, such as idling, low-speed driving, high-speed driving, rapid acceleration, and rapid braking, and the external environmental temperature also has a significant impact on the thermal management requirements. Traditional thermal management systems often struggle to accurately match the heat dissipation requirements under various working conditions, resulting in excessive energy consumption of the water pump or poor heat dissipation effect, thereby affecting the overall performance and driving range of new energy vehicles. Therefore, it is urgent to develop an efficient and intelligent test method for the thermal management system. Summary of the Invention

[0003] To solve the technical problems in the background art, the present invention proposes a test method for the thermal management system of new energy vehicles.

[0004] The test method for the thermal management system of new energy vehicles proposed by the present invention includes: Simulating the working condition data corresponding to the current working condition and inputting the working condition data into the thermal management system of the new energy vehicle, where the thermal management system of the new energy vehicle includes M water pumps, a coolant circulation system, and multiple temperature sensors; Collecting the coolant inlet and outlet temperatures corresponding to each of the M water pumps in the thermal management system of the new energy vehicle; Sequentially inputting the working condition data and the coolant inlet and outlet temperatures corresponding to each of the M water pumps into the trained thermal management model to obtain the optimal duty cycle corresponding to each of the M water pumps under the current working condition; Real-time collecting the actual duty cycles corresponding to each of the M water pumps in the thermal management system of the new energy vehicle, and comparing the actual duty cycles corresponding to each of the M water pumps with the optimal duty cycle to determine the water pumps that need to adjust and optimize the duty cycle.

[0005] Preferably, the current working condition includes, but is not limited to, idling, low-speed driving, high-speed driving, rapid acceleration, and rapid braking; any one working condition corresponds to a set of working condition data.

[0006] Preferably, the working condition data includes, but is not limited to, vehicle driving speed , acceleration , ambient temperature , average battery temperature , motor winding temperature ; the training process of the thermal management model is as follows: Obtain test sample data, where the test sample data includes multiple working conditions, multiple pieces of working condition data corresponding to the multiple working conditions, and duty cycle data; Slice the test sample data according to a preset strategy to form a training set, a test set, and a validation data set; Take the vehicle driving speed , acceleration , ambient temperature average battery temperature , motor winding temperature and the coolant inlet and outlet temperatures corresponding to each of the M water pumps as input features, and input them into a preset thermal management network for model training to obtain a thermal management model; Adjust the network parameters of the preset thermal management network according to the training results until the error between the duty cycle obtained through the thermal management network and the actual duty cycle is within a preset range to obtain a trained thermal management model.

[0007] Preferably, the preset strategy is specifically: the ratio of the training set, validation set, and test set is 8:1:1.

[0008] Preferably, the comparison of the actual duty cycle corresponding to each of the M water pumps with the optimal duty cycle to determine the water pumps that need to adjust and optimize the duty cycle specifically includes: Taking the optimal duty cycle as a benchmark, when the actual duty cycle corresponding to each of the M water pumps is not equal to the optimal duty cycle, the corresponding water pump is taken as the water pump that needs to adjust and optimize the duty cycle.

[0009] Preferably, in the thermal management model, the calculation process of the optimal duty cycle of the water pump is as follows: ; where D is the optimal duty cycle of the water pump; k0 - k7 are regression coefficients obtained by fitting a large amount of test data through the least squares method or the gradient descent method; is a random error term used to compensate for the influence of complex real factors that the model cannot accurately cover; Tin is the coolant inlet temperature; Tout is the coolant outlet temperature.

[0010] The new energy vehicle thermal management system test system proposed by the present invention includes: A first simulation module for simulating the working condition data corresponding to the current working condition and inputting the working condition data into the new energy vehicle thermal management system, where the new energy vehicle thermal management system includes M water pumps, a coolant circulation system, and multiple temperature sensors; A data acquisition module for collecting the coolant inlet and outlet temperatures corresponding to each of the M water pumps in the new energy vehicle thermal management system; The first processing module is configured to input the working condition data and the coolant inlet and outlet temperatures corresponding to each of the M water pumps into the trained thermal management model in sequence, so as to obtain the optimal duty cycle corresponding to each of the M water pumps under the current working condition; The second processing module is configured to collect in real time the actual duty cycles corresponding to each of the M water pumps in the new energy vehicle thermal management system, and compare the actual duty cycles corresponding to each of the M water pumps with the optimal duty cycles to determine the water pumps that need to adjust and optimize the duty cycles.

[0011] Correspondingly, the present invention also provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor executes the steps of the above-mentioned new energy vehicle thermal management system testing method.

[0012] Correspondingly, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the new energy vehicle thermal management system testing method are implemented.

[0013] In the present invention, the proposed new energy vehicle thermal management system testing method can effectively calculate the optimal duty cycle of the water pumps in the new energy vehicle thermal management system by simulating the working condition data and collecting the temperature data in real time, in combination with the thermal management model, which is convenient for optimizing the performance of the thermal management system and improving the energy efficiency and reliability of the new energy vehicle. Description of the Drawings

[0014] Figure 1 It is a schematic structural diagram of the working process of the new energy vehicle thermal management system testing method proposed by the present invention; Figure 2 It is a schematic system architecture diagram of the new energy vehicle thermal management system testing method proposed by the present invention. Detailed Embodiments

[0015] Referring to Figure 1 and Figure 2 , the new energy vehicle thermal management system testing method proposed by the present invention includes the following steps: S1. Simulate the working condition data corresponding to the current working condition, and input the working condition data into the new energy vehicle thermal management system, where the new energy vehicle thermal management system includes M water pumps, a coolant circulation system, and multiple temperature sensors.

[0016] In this embodiment, the current working condition includes but is not limited to idle speed, low-speed driving, high-speed driving, rapid acceleration, and rapid braking; any one of the working conditions corresponds to a set of working condition data.

[0017] In this embodiment, the new energy vehicle thermal management system is composed of the following core components: M water pumps, which are used to drive the coolant circulation, each water pump is independently controlled, and the flow rate can be adjusted according to the duty cycle.

[0018] The coolant circulation system, including the radiator, cooling pipes, battery cooling plate, motor cooling jacket, etc., forms a closed loop.

[0019] Temperature sensors are deployed at key locations such as coolant inlet and outlet, battery modules, and motor windings to collect temperature data in real time.

[0020] In this embodiment, it also includes: a control unit, integrating a thermal management model algorithm, receiving sensor data and outputting an optimal duty cycle instruction; a working condition simulation module, simulating the vehicle driving state (such as vehicle speed, acceleration, ambient temperature, etc.) and generating dynamic working condition data.

[0021] S2. Collect the coolant inlet and outlet temperatures corresponding to M water pumps in the thermal management system of the new energy vehicle.

[0022] S3. Input the operating condition data and the coolant inlet and outlet temperatures corresponding to the M water pumps into the trained thermal management model in sequence to obtain the optimal duty cycle corresponding to the M water pumps under the current operating condition.

[0023] In this embodiment, the operating condition data includes but is not limited to the vehicle speed. , acceleration , Ambient temperature , average battery temperature , Motor winding temperature The training process of the thermal management model is as follows: obtain test sample data, which includes multiple working conditions, multiple working condition data corresponding to multiple working conditions, and duty cycle data; divide the test sample data according to the preset strategy to form a training set, a test set, and a verification data set; , acceleration , Ambient temperature , average battery temperature , Motor winding temperature The coolant inlet and outlet temperatures corresponding to the M water pumps are used as input features and input into a preset thermal management network for model training to obtain a thermal management model; the network parameters of the preset thermal management network are adjusted according to the training results until the error between the duty cycle obtained through the thermal management network and the actual duty cycle is within a preset range to obtain a trained thermal management model.

[0024] In this embodiment, the preset strategy is specifically: the corresponding ratios of the training set, the validation set and the test set are 8:1:1.

[0025] In this embodiment, in the thermal management model, the optimal duty cycle calculation process of the water pump is as follows: ; Among them, D is the optimal duty cycle of the water pump; k0 - k7 are regression coefficients, obtained by fitting a large amount of test data through the least squares method or the gradient descent method; is the random error term, used to compensate for the influence of complex real - world factors that the model cannot precisely cover; Tin is the coolant inlet temperature; Tout is the coolant outlet temperature.

[0026] S4. Real - time collect the actual duty cycles corresponding to each of the M water pumps in the new - energy vehicle thermal management system, and compare the actual duty cycles corresponding to each of the M water pumps with the optimal duty cycle to determine the water pumps that need to adjust and optimize the duty cycle.

[0027] In this embodiment, comparing the actual duty cycles corresponding to each of the M water pumps with the optimal duty cycle to determine the water pumps that need to adjust and optimize the duty cycle specifically includes: Taking the optimal duty cycle as a benchmark, when the actual duty cycle corresponding to each of the M water pumps is not equal to the optimal duty cycle, then the corresponding water pump is taken as the water pump that needs to adjust and optimize the duty cycle.

[0028] In this embodiment, the working process of this application is as follows: Data input: The working - condition simulation module generates current working - condition data (such as vehicle driving speed , acceleration , ambient temperature ), and inputs it into the new - energy vehicle thermal management system.

[0029] Temperature collection: The temperature sensor real - time collects the coolant inlet and outlet temperatures (Tin, Tout) corresponding to the M water pumps.

[0030] Model calculation: The control unit inputs the working - condition data and temperature data into the trained thermal management model to calculate the optimal duty cycle of each water pump .

[0031] Duty - cycle adjustment: Compare the actual duty cycle with . If , then dynamically adjust the duty cycle of the corresponding water pump until the error is less than the preset threshold (such as ±2%).

[0032] In this embodiment, through closed - loop control, the system can dynamically optimize the energy consumption of the water pump according to the real - time working condition and temperature change, ensure that the battery and the motor work in the best temperature range, and at the same time extend the life of key components.

[0033] Specifically, when the vehicle is in a high - speed driving working condition (vehicle speed , ambient temperature ), the average temperature of the battery rises to 45°C, and the temperature of the motor winding The implementation steps of this application are as follows: Data input: The working condition simulation module generates high-speed working condition data and inputs it into the control unit.

[0034] Temperature acquisition: The coolant inlet temperature and outlet temperature of water pump 1.

[0035] Model calculation: The thermal management model outputs the optimal duty cycle of water pump 1 。

[0036] Duty cycle adjustment: Detect the actual duty cycle , and the control unit gradually reduces the duty cycle of water pump 1 to 75%.

[0037] Effect verification: After adjustment, the power consumption of water pump 1 is reduced by 18%, the battery temperature is stabilized at 42 °C, the motor temperature is reduced to 55 °C, and the overall energy efficiency of the system is increased by 12%.

[0038] Refer to Figure 1 and Figure 2 , the new energy vehicle thermal management system test system proposed by the present invention includes: The first simulation module is used to simulate the working condition data corresponding to the current working condition and input the working condition data into the new energy vehicle thermal management system. The new energy vehicle thermal management system includes M water pumps, a coolant circulation system, and multiple temperature sensors; The data acquisition module is used to acquire the coolant inlet and outlet temperatures corresponding to each of the M water pumps in the new energy vehicle thermal management system; The first processing module is used to sequentially input the working condition data and the coolant inlet and outlet temperatures corresponding to each of the M water pumps into the trained thermal management model to obtain the optimal duty cycle corresponding to each of the M water pumps under the current working condition; The second processing module is used to collect in real time the actual duty cycles corresponding to each of the M water pumps in the new energy vehicle thermal management system, and compare the actual duty cycles corresponding to each of the M water pumps with the optimal duty cycle to determine the water pumps that need to adjust and optimize the duty cycle.

[0039] Correspondingly, the present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above thermal management system test method are implemented. At the same time, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, the steps of the above thermal management system test method are implemented.

[0040] The above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, shall be covered by the protection scope of the present invention.

Claims

1. Testing method for thermal management system of new energy vehicle, characterized in that: include: Simulating the operating condition data corresponding to the current operating condition, and inputting the operating condition data into the new energy vehicle thermal management system, wherein the new energy vehicle thermal management system includes M water pumps, a coolant circulation system, and multiple temperature sensors; Collecting the coolant inlet and outlet temperatures corresponding to each of the M water pumps in the thermal management system of the new energy vehicle; The operating condition data and the coolant inlet and outlet temperatures corresponding to the M water pumps are sequentially input into the trained thermal management model to obtain the optimal duty cycle corresponding to the M water pumps under the current operating condition; The actual duty ratios of the M water pumps in the thermal management system of the new energy vehicle are collected in real time, and the actual duty ratios of the M water pumps are compared with the optimal duty ratio to determine the water pumps that need to be adjusted to optimize the duty ratio.

2. The new energy vehicle thermal management system testing method according to claim 1 is characterized in that: The current operating condition includes but is not limited to idling, low-speed driving, high-speed driving, sudden acceleration, and sudden braking; any operating condition corresponds to a set of operating condition data.

3. The new energy vehicle thermal management system testing method according to claim 2 is characterized in that: The operating condition data includes but is not limited to the vehicle speed , acceleration , Ambient temperature , average battery temperature , Motor winding temperature ; The training process of the thermal management model is as follows: Acquire test sample data, wherein the test sample data includes multiple operating conditions, multiple operating condition data corresponding to the multiple operating conditions, and duty cycle data; The test sample data is divided according to the preset strategy to form a training set, a test set, and a validation set; The vehicle speed , acceleration , Ambient temperature , average battery temperature , Motor winding temperature The coolant inlet and outlet temperatures corresponding to the M water pumps are used as input features and input into a preset thermal management network for model training to obtain a thermal management model; The network parameters of the preset thermal management network are adjusted according to the training results until the error between the duty cycle obtained through the thermal management network and the actual duty cycle is within a preset range, so as to obtain a trained thermal management model.

4. The new energy vehicle thermal management system testing method according to claim 3 is characterized in that: The preset strategy is specifically: the corresponding ratios of the training set, validation set and test set are 8:1:

1.

5. The new energy vehicle thermal management system testing method according to claim 1, characterized in that: The comparing the actual duty cycle corresponding to each of the M water pumps with the optimal duty cycle to determine the water pump whose duty cycle needs to be adjusted and optimized specifically includes: Taking the optimal duty cycle as a reference, when the actual duty cycle corresponding to each of the M water pumps is not equal to the optimal duty cycle, the corresponding water pump is regarded as the water pump that needs to adjust the optimized duty cycle.

6. The new energy vehicle thermal management system testing method according to claim 3 is characterized in that: In the thermal management model, the optimal duty cycle of the water pump is calculated as follows: ； Where D is the optimal duty cycle of the water pump; k0-k7 are regression coefficients, which are calculated by fitting massive test data using the least squares method or gradient descent method; It is a random error term, which is used to compensate for the influence of complex real factors that cannot be accurately covered by the model; Tin is the coolant inlet temperature; Tout is the coolant outlet temperature.

7. New energy vehicle thermal management system test system, characterized in that: include: A first simulation module is used to simulate the working condition data corresponding to the current working condition, and input the working condition data into the new energy vehicle thermal management system, wherein the new energy vehicle thermal management system includes M water pumps, a coolant circulation system and multiple temperature sensors; A data acquisition module, used to collect the coolant inlet and outlet temperatures corresponding to each of the M water pumps in the thermal management system of the new energy vehicle; The first processing module is used to input the working condition data and the coolant inlet and outlet temperatures corresponding to the M water pumps into the trained thermal management model in sequence to obtain the optimal duty cycle corresponding to the M water pumps under the current working condition; The second processing module is used to collect the actual duty cycle corresponding to each of the M water pumps in the thermal management system of the new energy vehicle in real time, and compare the actual duty cycle corresponding to each of the M water pumps with the optimal duty cycle to determine the water pump whose duty cycle needs to be adjusted and optimized.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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