A method for constructing a strong fitting capability pure electric vehicle whole vehicle thermal management system simulation model

Abstract

This invention belongs to the technical field of thermal management for pure electric vehicles. It discloses a method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability. The method includes: sequentially calibrating and correcting corresponding components in a pre-built thermal management system simulation model using test data from performance tests of various components in the target vehicle, test data from performance tests of the thermal management system, and test data from overall vehicle performance tests, thereby obtaining a calibrated simulation model and completing the construction of the simulation model; and using the calibrated simulation model to conduct simulation research on the overall vehicle thermal management system. This invention proposes conducting performance tests on various components, the thermal management system, and the entire vehicle of the target vehicle separately, and using test data to calibrate and correct the simulation model from three levels: components, system, and the entire vehicle. The resulting simulation model has high accuracy and strong fitting capability.

Description

Technical Field

[0001] This invention belongs to the technical field of thermal management of pure electric vehicles, and more specifically, relates to a method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting ability. Background Technology

[0002] With the rapid development of pure electric vehicles, the number of vehicle models and items that need to be calculated on vehicle testing platforms is increasing daily. The overall vehicle parameters and individual component parameters differ for each model and item, making it difficult to manually build models and input parameters for each application and model within a limited timeframe. This results in long project development cycles and high testing costs. Due to the limitations of real-vehicle testing methods, conducting research on electric vehicle thermal management energy consumption through testing is time-consuming, labor-intensive, and time-consuming. Analyzing electric vehicle thermal management energy consumption through simulation methods can effectively address the limitations of testing methods, improve the efficiency of thermal management energy consumption research, and reduce costs.

[0003] Current simulation models for electric vehicle thermal management systems suffer from several issues, including system complexity and the volatile nature of energy consumption. These issues result in significant discrepancies between simulation results and actual conditions, as well as low generalization ability. Furthermore, simulation models often exhibit high accuracy only under a few specific operating conditions, thus limiting the application of simulation methods in the study of energy consumption in vehicle thermal management systems. Consequently, the reliability of simulation models needs to be improved. Summary of the Invention

[0004] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a method for constructing a simulation model of a pure electric vehicle's thermal management system with strong fitting capabilities. This method solves the problems of large errors between simulation results and actual conditions, heavy reliance on experiments, and low generalization ability in current electric vehicle thermal management system simulation models.

[0005] To achieve the above objectives, according to the present invention, a method for constructing a simulation model of a pure electric vehicle's thermal management system with strong fitting capability is provided, comprising: By using test data from various component performance tests, thermal management system performance tests, and whole vehicle performance tests, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected sequentially to obtain the calibrated simulation model, thus completing the construction of the simulation model.

[0006] The method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability according to the present invention includes a heat exchanger, which comprises an evaporator and a condenser. The performance test of the heat exchanger specifically includes: The heat exchanger is placed in an air duct with adjustable temperature, humidity, and air velocity. Refrigerant is introduced into the heat exchanger to conduct a heat exchange performance test. Multiple test conditions are designed by changing the variable parameters in the test. The variable parameters include multiple parameters such as air duct volume, air velocity, inlet air temperature, refrigerant flow rate, and refrigerant inlet temperature. Key performance parameters are obtained under each test condition. Key performance parameters include multiple parameters such as refrigerant side inlet and outlet pressure drop, refrigerant side heat exchange, and air side heat exchange. Accordingly, the test data of the components are used to calibrate and correct the corresponding components in the pre-built thermal management system simulation model, specifically including: Under multiple test conditions, simulation analysis with the same operating parameters was performed using the simulation model. By adjusting the structural parameters of the corresponding heat exchanger in the simulation model, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

[0007] According to the method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability provided by the present invention, the components also include a compressor, and the performance test of the compressor specifically includes: The compressor is subjected to refrigerant gas compression tests; the test conditions include different discharge pressures and different speeds; under each test condition, the inlet and outlet temperatures, pressures, flow rates, and power data are monitored, and the volumetric efficiency, isentropic compression efficiency, and mechanical efficiency of the compressor are obtained based on the monitoring data; by combining the data from multiple test conditions, the volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve of the compressor are obtained. Accordingly, the obtained volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve are used to calibrate the compressor efficiency parameters in the simulation model.

[0008] According to the method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability provided by the present invention, the performance test of the thermal management system includes the performance test of the air conditioning system circuit, specifically: An air conditioning system circuit test bench was built according to the actual vehicle principle of the target model to conduct heating and cooling performance tests. The relevant components of the air conditioning system circuit were arranged in two controllable air ducts and the pipes were connected according to the actual connection relationship. The controllable air ducts are air ducts with adjustable intake air temperature, humidity and wind speed. One of the two controllable air ducts simulates the indoor environment of the driver's cab and the other simulates the outdoor environment. Temperature and pressure sensors were installed at the compressor inlet and outlet, the heat exchanger inlet and outlet, and a temperature sensor was installed at the air outlet of the controllable air duct. A mass flow meter was added to the circuit, and a power meter was connected to the compressor to obtain the monitoring values ​​during the test.

[0009] According to the method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability provided by the present invention, the test condition design for performance testing of the air conditioning system circuit is as follows: Based on the purpose of the cold source in the cooling mode, the cooling mode is divided into multiple types; based on the source of the heat source in the heating mode, the heating mode is divided into multiple types; for each cooling mode, the compressor speed, the temperature and / or flow rate of the cold source on the convection side are changed to form multiple test conditions; for each heating mode, the compressor speed, the temperature and / or flow rate of the heat source are changed to form multiple test conditions.

[0010] According to the method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability provided by the present invention, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected using system test data, specifically including: For each set of test conditions, key performance parameters were obtained, including at least one of the following: heat exchanger heat exchange capacity, compressor inlet and outlet pressure, and compressor power consumption. Under multiple test conditions, simulation analysis with the same operating parameters was performed using a simulation model. By adjusting at least one of the following parameters in the simulation model: compressor efficiency parameter, heat exchanger structural parameter, pressure drop gain coefficient, and expansion valve opening flow characteristics, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

[0011] The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability according to the present invention, which uses system test data to calibrate and correct corresponding components in the pre-built thermal management system simulation model, further includes: Record the transitional data of the monitored quantities during the change of test conditions, and compile the curves of the changes in the monitored quantities; The same experimental conditions are performed in the simulation model, and the trend of the monitored quantities in the simulation is recorded. By adjusting at least one of the following: the expansion valve time constant, the compressor speed switching rate, and the specific heat capacity property of the heat exchanger material, the trend of the simulation is made consistent with that in the experiment.

[0012] According to the method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability provided by the present invention, the performance tests on various components, thermal management system and whole vehicle of the target model also include: obtaining the flow rate change of the refrigerant in the flow path under each set of test conditions, using the refrigerant flow rate change to judge the validity of the test, and selecting the test data under the valid test conditions for simulation calibration.

[0013] The method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability according to the present invention, specifically includes the following aspects for conducting performance tests on the vehicle: Conduct driving range tests under different temperature conditions, and obtain vehicle energy consumption distribution information and driving range information under each set of test conditions; Accordingly, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected using vehicle test data, specifically including: The vehicle simulation model, which includes a pre-built simulation model of the thermal management system, is used to simulate multiple sets of driving range test parameters. The energy consumption data of the main energy-consuming components in the simulation is compared with the energy consumption data in the test. By adjusting the efficiency model or operating characteristic curve of each main energy-consuming component, the consistency between the simulation data and the test data is achieved. The main energy-consuming components include multiple components such as the air conditioning compressor, PTC, cooling fan, electric water pump and air conditioning blower.

[0014] The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability according to the present invention, which uses vehicle test data to calibrate and correct corresponding components in the pre-built thermal management system simulation model, further includes: By comparing the key performance parameters of the battery system in simulation and experiment, and correcting the battery model parameters, consistency between the simulation data and the experimental data is achieved. The key performance parameters of the battery system include at least one of the following: terminal voltage information, output current information, and cumulative energy consumption information.

[0015] In summary, compared with the prior art, the method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting ability provided by the present invention offers the following advantages: 1. This paper proposes to conduct performance tests on various related components, thermal management systems, and the entire vehicle of a target model, obtain and analyze basic data from electric vehicle-related tests that can be used to build simulation models, and use the test data to calibrate and correct the simulation model from three levels: components, systems, and the entire vehicle. This effectively solves the problem of insufficient component accuracy in the process of building simulation models, which is conducive to improving the simulation accuracy and reliability of the simulation model, achieving strong fitting and high-precision simulation, and providing a reliable data foundation and methodological support for the construction of simulation models of electric vehicle thermal management systems. 2. Research and refine the testing methods and basic specifications for the general thermal management system and its components for electric vehicles. Each performance test involves multiple operating conditions, which is beneficial for covering a variety of practical application conditions, thereby obtaining more comprehensive and effective performance data. The simulation model calibrated using this performance data can cover more operating conditions, which is beneficial for simulation analysis applicable to a variety of different operating conditions, thereby improving the applicability and practicality of the simulation model. This simulation model can provide more comprehensive analysis results for the research of the whole vehicle thermal management system. 3. Selecting the target vehicle model for a full-vehicle range test yields basic data from electric vehicle-related tests that can be used to build a simulation model. This is beneficial for constructing an accurate simulation model of the thermal management system of a pure electric vehicle. Using the obtained simulation model to study the thermal management system effectively solves the problems of long construction cycle and high cost of electric vehicle test benches, and facilitates the prediction of system performance, making the research results more accurate and more in line with engineering practice. 4. This method aims to provide a method for constructing a simulation model of the thermal management system of electric vehicles. The simulation model constructed by this method can realize the simulation analysis functions of thermal management system performance, thermal management system energy consumption, vehicle power consumption and vehicle driving range under various typical operating conditions. It provides an industry reference for improving the standardization, efficiency and overall performance, reliability and safety of electric vehicle thermal management system simulation methods. Attached Figure Description

[0016] Figure 1 This is a flowchart of the simulation model construction method provided in the embodiments of the present invention.

[0017] Figure 2 This is a schematic diagram of the evaporator calibration model provided in an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the condenser calibration model provided in an embodiment of the present invention.

[0019] Figure 4 This is a schematic diagram of a compressor model provided in an embodiment of the present invention.

[0020] Figure 5 This is a schematic diagram of the air conditioning system circuit test bench layout provided in an embodiment of the present invention.

[0021] Figure 6 This is a schematic diagram of an air conditioning system simulation model provided in an embodiment of the present invention.

[0022] Figure 7 This is a schematic diagram of the simulation method for thermal management of pure electric vehicles provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] Please see Figure 1This embodiment provides a method for constructing a simulation model of the thermal management system of a pure electric vehicle with strong fitting capability. The method includes: By utilizing test data from performance tests of various components in the target vehicle model, performance tests of the thermal management system, and overall vehicle performance tests, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected sequentially to obtain the calibrated simulation model, thus completing the construction of the simulation model. The calibrated simulation model is then used to conduct simulation research on the vehicle's thermal management system.

[0025] This embodiment addresses the significant discrepancy between simulation results and actual conditions in current electric vehicle thermal management simulation studies. The main reason for this discrepancy lies in the fact that existing simulations of electric vehicle thermal management typically focus on the battery, with limited research on other components such as the air conditioning system. Therefore, this embodiment proposes conducting performance tests on various key components to obtain experimental data. This data can then be used to calibrate and correct the corresponding components in the simulation model, ensuring consistency between the simulation results and the experimental data. This improves the accuracy and reliability of the component models within the simulation model. Furthermore, this embodiment proposes conducting performance tests on both the thermal management system and the entire vehicle. The system and vehicle test data are then used to further calibrate and correct the simulation model, ensuring reliable and accurate analytical results at both the system and vehicle levels. This multi-layered calibration and correction approach achieves high simulation accuracy, making the model suitable for simulation analysis of the entire vehicle's thermal management system. This effectively solves the problems of long setup times and high costs associated with electric vehicle test benches.

[0026] Specifically, the component performance testing method proposed in this embodiment isolates core components such as compressors and heat exchangers from the system. On a controllable test bench, by precisely adjusting one or more input boundary conditions, the output response is comprehensively and independently measured to obtain the inherent performance of the component across the entire operating range. This data will be directly used to generate or modify the characteristic parameter files or high-fidelity sub-models of the corresponding components in simulation software (such as AMESim). The performance test aims to establish a quantitative mapping relationship between the input and output parameters of key individual components by accurately measuring their performance characteristics under controlled boundary conditions.

[0027] In some embodiments, the component includes a heat exchanger, which includes an evaporator and a condenser. The performance test of the heat exchanger specifically includes: The heat exchanger is placed in an air duct with adjustable temperature, humidity, and air velocity. Refrigerant is introduced into the heat exchanger to conduct a heat exchange performance test. Multiple test conditions are designed by changing the variable parameters in the test. The variable parameters include multiple parameters such as air duct volume, air velocity, inlet air temperature, refrigerant flow rate, and refrigerant inlet temperature. Key performance parameters are obtained under each test condition. Key performance parameters include multiple parameters such as refrigerant side inlet and outlet pressure drop, refrigerant side heat exchange, and air side heat exchange. Accordingly, the test data of the components are used to calibrate and correct the corresponding components in the pre-built thermal management system simulation model, specifically including: Under multiple test conditions, simulation analysis with the same operating parameters was performed using the simulation model. By adjusting the structural parameters of the corresponding heat exchanger in the simulation model, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

[0028] In this embodiment, multiple sets of operating conditions are created by changing variable parameters during the design of the test conditions. For example, the airflow, velocity, and inlet air temperature in the duct can be changed to simulate the airflow, velocity, and temperature on the air side in the heat exchanger application. By designing tests under different refrigerant flow rates and temperature parameters (which can be refrigerant inlet subcooling / superheating), different levels of cooling / heating demand can be simulated. By designing multiple sets of test conditions, various operating conditions in actual heat exchanger applications can be covered, thereby enabling more comprehensive acquisition of relevant performance data. Using the performance data from multiple sets of test conditions for simulation model calibration also facilitates more comprehensive and effective correction of the simulation model, achieving accurate simulation of the model under typical operating conditions. The specific test condition parameter values ​​can be selected based on practical application experience, with the aim of approximating actual application conditions, and are not specifically limited.

[0029] Specifically, refer to Figure 2 In this embodiment, taking the heat exchanger as the evaporator and changing the inlet air volume of the air duct as an example, the test conditions for performance testing can be designed as follows: Dry bulb temperature of air at the duct inlet: 27±0.5 ℃; Relative humidity of air at the duct inlet: 50%; Evaporator inlet refrigerant pressure: 1.47 MPa (g); Evaporator inlet refrigerant subcooling: 5°C; Evaporator outlet refrigerant pressure: 0.2 MPa (g); Evaporator outlet refrigerant superheat: 5 °C; Air inlet volume: 150 m³ 3 / h, 250 m 3 / h, 350 m 3 / h, 450 m 3 / h.

[0030] The specific test measurement data includes: measuring multiple parameters under each test condition, such as refrigerant side inlet pressure (MPa), refrigerant flow rate (kg / h), refrigerant side pressure loss (kPa), air side resistance loss (kPa), refrigerant side heat exchange (kW), and air side heat exchange (kW).

[0031] The simulation calibration specifically involves correcting the heat exchanger's structural parameters, including fin size, flat tube size, number of channels within the flat tube, and hydraulic diameter. Based on the evaporator's individual performance test results, a calibration data table is compiled as input information for evaporator calibration. A calibration model of the evaporator is built, and the parameters are optimized using the software's built-in calibration module to ensure consistency in key performance parameters such as heat exchange, pressure drop, and outlet superheat.

[0032] refer to Figure 3 In this embodiment, taking the heat exchanger as the condenser and changing the inlet air velocity of the air duct as an example, the test conditions for performance testing can be designed as follows: Dry bulb temperature of air at the air inlet of the air duct: 35℃; Relative humidity of air at the air inlet of the air duct: 50%; Condenser refrigerant inlet pressure: 1.47 MPa (g); Condenser refrigerant inlet superheat: 25℃; Condenser refrigerant outlet subcooling: 5℃; Condenser frontal area dimensions: 488×435mm; Air intake velocities in the duct: 1.5m / s, 2.5m / s, 4.5m / s, 6m / s.

[0033] The specific test measurement data are as follows: the refrigerant side outlet pressure (MPa), refrigerant flow rate (kg / h), refrigerant side pressure loss (kPa), air side resistance loss (kPa), refrigerant side heat exchange (kW), and air side heat exchange (kW) are measured under each test condition.

[0034] The simulation calibration specifically involves correcting the condenser structural parameters, including fin dimensions, flat tube dimensions, number of channels within the flat tubes, and cross-sectional area. Based on the condenser's individual performance test results, a calibration data table is compiled as input information for the evaporator calibration. Key performance parameters such as heat transfer, pressure drop, and outlet subcooling are then calibrated.

[0035] In some embodiments, the component further includes a compressor, and the performance test of the compressor specifically includes: The compressor is subjected to refrigerant gas compression tests; the test conditions include different discharge pressures and different speeds; under each test condition, the inlet and outlet temperatures, pressures, flow rates, and power data are monitored, and the volumetric efficiency, isentropic compression efficiency, and mechanical efficiency of the compressor are obtained based on the monitoring data; by combining the data from multiple test conditions, the volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve of the compressor are obtained. Accordingly, the obtained volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve are used to calibrate the compressor efficiency parameters in the simulation model.

[0036] Specifically, the test conditions for the individual thermal performance test of the electric compressor can be designed as follows: Compressor inlet pressure (absolute pressure): 0.3 MPaA; Compressor discharge pressure (absolute pressure): 1.2 MPaA, 1.5 MPaA, 1.8 MPaA, 2.1 MPaA; Compressor inlet superheat: 10℃; The compressor speeds are 2000 / 4000 / 6000 / 8000 r / min.

[0037] This means that four speeds can be tested at each exhaust pressure, resulting in 16 test conditions. The specific test measurement data includes: measuring the exhaust temperature, refrigerant flow rate (kg / h), and compressor shaft work (kW) (obtainable via a power meter) for each test condition, thereby obtaining the compressor volumetric efficiency (%), isentropic compression efficiency (%), and mechanical efficiency (%).

[0038] The simulation calibration is specifically as follows: Reference Figure 4 A compressor simulation model is built, inputting compressor speed and receiving feedback signals from inlet and outlet pressures and compressor power consumption. Based on thermodynamic formulas, the volumetric efficiency, isentropic efficiency, and mechanical efficiency are calculated for each test operating point, and the raw data is organized into a multidimensional table (e.g., a MAP plot). The generated MAP plot is then directly imported into the simulation model as standard data, replacing the original theoretical compressor model. Alternatively, using this high-precision experimental data, undetermined coefficients (such as polynomial coefficients) in the empirical formula model are calibrated through curve fitting methods, thereby obtaining a compressor simulation model that is both accurate and computationally efficient.

[0039] In some embodiments, performance testing of the thermal management system includes performance testing of the air conditioning system circuit, specifically: An air conditioning system circuit test bench was built according to the actual vehicle principle of the target model to conduct heating and cooling performance tests. The relevant components of the air conditioning system circuit were arranged in two controllable air ducts and the pipes were connected according to the actual connection relationship. The controllable air ducts are air ducts with adjustable intake air temperature, humidity and wind speed. One of the two controllable air ducts simulates the indoor environment of the driver's cab and the other simulates the outdoor environment. Temperature and pressure sensors were installed at the compressor inlet and outlet, the heat exchanger inlet and outlet, and a temperature sensor was installed at the air outlet of the controllable air duct. A mass flow meter was added to the circuit, and a power meter was connected to the compressor to obtain the monitoring values ​​during the test.

[0040] The specific test condition design for performance testing of the air conditioning system circuit is as follows: Based on the purpose of the cold source in the cooling mode, the cooling mode is divided into multiple types; based on the source of the heat source in the heating mode, the heating mode is divided into multiple types; for each cooling mode, the compressor speed, the temperature and / or flow rate of the cold source on the convection side are changed to form multiple test conditions; for each heating mode, the compressor speed, the temperature and / or flow rate of the heat source are changed to form multiple test conditions.

[0041] The corresponding components in the pre-built thermal management system simulation model are calibrated and corrected using system test data, specifically including: For each set of test conditions, key performance parameters were obtained, including at least one of the following: heat exchanger heat exchange capacity, compressor inlet and outlet pressure, and compressor power consumption. Under multiple test conditions, simulation analysis with the same operating parameters was performed using a simulation model. By adjusting at least one of the following parameters in the simulation model: compressor efficiency parameter, heat exchanger structural parameter, pressure drop gain coefficient, and expansion valve opening flow characteristics, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

[0042] The calibration and correction of corresponding components in the pre-built thermal management system simulation model using system test data also includes: Record the transitional data of the monitored quantities during the change of test conditions, and compile the curves of the changes in the monitored quantities; The same experimental conditions are performed in the simulation model, and the trend of the monitored quantities in the simulation is recorded. By adjusting at least one of the following: the expansion valve time constant, the compressor speed switching rate, and the specific heat capacity property of the heat exchanger material, the trend of the simulation is made consistent with that in the experiment.

[0043] Furthermore, performance tests on various components, thermal management systems, and the entire vehicle of the target model also include: acquiring changes in refrigerant flow rate in the flow path under each set of test conditions, using these changes to determine the validity of the test, and selecting test data from valid test conditions for simulation calibration. For example, in component performance tests, changes in refrigerant flow rate at the component's inlet and outlet can be monitored. The validity of the test can be determined by these changes; if the inlet and outlet refrigerant flow rate changes are too large, leakage may occur, making the test invalid. Test data from invalid tests will not be used for model calibration. In system performance tests, multiple flow data points can be monitored in the loop. The validity of the test conditions can be determined by analyzing the refrigerant flow rate in the loop, and finally, valid tests are selected for model calibration.

[0044] Specifically, with Figure 5 Taking the air conditioning system circuit shown as an example, the system calibration is specifically as follows: the system test is conducted through bench testing. A system bench is built according to the actual vehicle system principle, and the relevant condensers and evaporators are installed in two controllable air ducts made of insulating material. The air ducts are connected to a device that can adjust temperature, humidity, and airflow, simulating the interior and exterior of the vehicle. In this embodiment, the heat exchanger in the air conditioning system circuit includes the indoor condenser, i.e. Figure 5 The system consists of a water-cooled (refrigerant side), an outdoor condenser, an evaporator, and a chiiller heat exchanger. The indoor condenser's convection side, i.e., the water-cooled (water side), is connected to the HVAC circuit, while the chiiller (heat side) is connected to the battery fluid circuit. This air conditioning system circuit represents only one example vehicle model and is not the only configuration.

[0045] The test condition analysis is as follows: In the cooling mode, the chiller simulates a refrigerant-coolant secondary heat exchange cooling method, primarily used to test the performance of the battery cooling system. In the evaporator, refrigerant evaporates and absorbs heat, directly cooling the flowing air, which is then transported by a fan. The Chiller + Evaporator mode simulates a vehicle-wide coordinated cooling method; the chiller and evaporator operate simultaneously, and the compressor needs to simultaneously meet the dual requirements of cooling the passenger compartment and the battery pack. That is, in cooling mode, the cold source serves two purposes: cooling the passenger compartment at the evaporator and / or cooling the battery pack at the chiller. This is mainly used to test the system's comprehensive performance under complex conditions, such as control strategies and refrigerant distribution logic.

[0046] In heating mode, the refrigerant absorbs heat from the ambient heat source in the outdoor heat exchanger and releases heat in the evaporator to heat the air. When heating the passenger compartment is required, the system switches to heat pump mode. In this mode, the chiller absorbs heat from the waste coolant of the battery / electric drive system, using this waste heat as the "heat source" for the heat pump, thus efficiently converting it into heat for the passenger compartment. In other words, the heat sources in heating mode include the air heat source at the outdoor condenser, the waste heat source from the battery pack at the chiller, and in the mixed mode, the refrigerant simultaneously absorbs heat from both the chiller and the outdoor heat exchanger.

[0047] The test conditions are designed as follows: The system test includes an air conditioning system test. The air conditioning system mainly supplies energy to the chiller and evaporator. Due to different requirements and energy supply components, there are three operating modes: single evaporator operation, single chiller operation, and simultaneous operation of chiller and evaporator. When the air conditioning system is a heat pump air conditioner, there are six operating modes: single evaporator operation, single chiller operation, and simultaneous operation of chiller and evaporator in cooling mode; and single outdoor condenser heat source, single chiller heat source, and mixed mode heat source in heating mode.

[0048] The test bench strictly replicates the actual vehicle's piping connections for components such as the compressor, electronic expansion valve, heat exchanger, and receiver-drier. Measuring equipment was placed at key points: high-precision temperature and pressure sensors (accuracies ±0.5℃ and ±0.2% FS, respectively) were installed at the compressor's suction port, exhaust port, internal condenser outlet, and external condenser inlet and outlet; a Coriolis mass flow meter (accuracy ±0.2% Rd) was installed in the refrigerant main circuit to monitor refrigerant mass flow in real time; a power analyzer continuously recorded the compressor's input electrical power; and temperature sensors were placed at the air outlet of the simulated indoor air duct. During the test, by comprehensively adjusting the compressor speed, electronic expansion valve opening, temperature, humidity, and airflow of the internal and external environmental air ducts, as well as coolant circuit parameters, a systematic operating point encompassing various characteristics such as high and low temperature refrigeration and heating was generated. Steady-state and transient data from all sensors and instruments were simultaneously collected to obtain the monitored values.

[0049] The specific operating parameters are shown in Tables 1 and 2 below: Table 1. Operating Parameter Design in Cooling Mode

[0050] Table 2 Design of operating parameters under heating mode

[0051] The system test measurement data include: refrigerant side inlet pressure (MPa), refrigerant flow rate (kg / h), refrigerant side pressure loss of heat exchange core (kPa), air side resistance loss (kPa), refrigerant side heat exchange (kW), and air side heat exchange (kW).

[0052] Air conditioning system simulation model such as Figure 6 As shown, the model is integrated based on the previously calibrated component models (compressor, heat exchanger, etc.), and the corresponding pipe lengths, volumes, and insulation characteristics are set according to the actual dimensions and layout of the test bench. The core objective of calibration is to ensure that the key output parameters of the simulation model closely match the experimental measurements under the same input conditions (compressor speed, expansion valve opening, and internal and external environmental conditions). In the simulation model, the initial state of the air conditioning system is set to be the same as that of the experiment, and the experimental operating condition parameters are input into the simulation model. The specific benchmark parameters are selected as key performance parameters that can comprehensively reflect the thermodynamic state and performance of the system. The benchmarking process includes steady-state simulation benchmarking and transient simulation benchmarking.

[0053] The steady-state simulation and experimental comparisons are as follows: The bench test parameters include condenser fan speed, compressor speed, evaporator airflow, and chiller coolant flow rate. A system simulation model is built, and steady-state simulations are performed under identical conditions. The heat exchange rates of a single evaporator, a single chiller, and both evaporator and chiller are statistically analyzed. The compressor inlet and outlet pressures, compressor power consumption, and the mass flow rates of the compressor refrigerant, evaporator, chiller, and both evaporator and chiller are also statistically analyzed. The results are compared with experimental results, and the error should be controlled within a reasonable range.

[0054] If the comparison error is large, the efficiency parameters of the compressor, the heat exchange and pressure drop gain coefficient of the evaporator, the heat exchange and pressure drop gain coefficient of the condenser, the heat exchange and pressure drop gain coefficient of the chiller, and the opening and flow characteristics of the expansion valve can be appropriately corrected.

[0055] The transient simulation and experimental comparisons are as follows: To accurately reflect the transient response of the refrigeration system to pressure, flow rate, and heat exchange under various changing boundary conditions, transient simulations and experimental results are compared.

[0056] Transitional data of monitored quantities between operating conditions are recorded. Variation curves of variables such as condenser fan speed, compressor speed, evaporator airflow, and chiller coolant flow rate under experimental conditions are compiled and used as input to the simulation model. This means the experimental operating conditions are varied according to the same variation curves as in the experiment. Initial conditions are set for simulation calculations, and the trends of monitored parameters such as compressor mass flow rate and compressor inlet / outlet pressure are compared between the simulation and the experiment. The values ​​of these data throughout the entire experimental process are used for comparison and adjustment of the expansion valve time constant, compressor speed switching rate, and the specific heat capacity properties of the materials used in the evaporator, condenser, and chiller to ensure the simulation and experimental trends are as consistent as possible.

[0057] In some embodiments, performance testing of the whole vehicle specifically includes: Conduct driving range tests under different temperature conditions, and obtain vehicle energy consumption distribution information and driving range information under each test condition.

[0058] This embodiment proposes parameter calibration of the simulation model based on the results of the whole vehicle range test, and finally quantifies the accuracy of the model by comparing the experimental data and simulation results, providing a reliable tool for subsequent model-based control strategy research and performance optimization. To comprehensively evaluate the range and energy consumption characteristics of pure electric vehicles under different ambient temperatures, this experiment conducts a whole vehicle range test in accordance with GB / T 183861—2021 "Test Methods for Energy Consumption and Driving Range of Electric Vehicles Part 1: Light Vehicles". Considering that most existing studies on energy consumption analysis of thermal management systems are limited to single operating conditions and lack analysis of complex multi-condition scenarios in actual driving, this embodiment proposes conducting range tests under three typical operating conditions: normal temperature, high temperature, and low temperature. Specifically, this includes test preparation, vehicle sensor arrangement, energy consumption analysis using current and voltage sensors of key components, and temperature analysis using water-side and air-side temperature sensors.

[0059] The calibration work must meet the following specific requirements: Vehicle energy consumption and driving range benchmarking: Based on the WLTC cycle, driving range simulations were conducted under high temperature (e.g., 35℃), low temperature (e.g., -7℃), and normal temperature (e.g., 23℃) conditions, and the results were compared with actual measurements. Supplementary verification was also performed under a constant speed of 100km / h at normal temperature. This benchmarking aims to ensure the accuracy of the vehicle energy demand model.

[0060] Energy consumption decomposition and benchmarking of key components: For major energy-consuming components such as air conditioner compressors, PTC, cooling fans, electric water pumps, and air conditioner blowers (the main energy consumption comes from these), the simulated power consumption and experimental data are compared one by one. By fine-tuning the efficiency models or operating characteristic curves of each component, accurate reproduction of component-level power consumption is achieved.

[0061] Battery system energy consumption benchmarking and energy flow closed-loop verification: Compare the terminal voltage, output current, and cumulative energy consumption of the battery pack in simulation and experiment. By appropriately adjusting the battery model parameters such as internal resistance and open-circuit voltage, consistency between simulation data and experimental data is achieved; at the same time, it is ensured that the battery output energy and thermal management energy consumption in the simulation (i.e., comparing the power consumption of each component) are balanced with the battery charging / discharging energy in the experiment, thus achieving a closed loop for the total energy flow.

[0062] Through the above systematic calibration and parameter adjustment, the ultimate goal is to control the relative error between the predicted results of the total energy consumption and driving range of the vehicle and the measured data under various test conditions to within 5%, thereby providing a reliable foundation for energy consumption analysis and control strategy optimization based on the model.

[0063] This involves using vehicle test data to calibrate and correct corresponding components in a pre-built simulation model of the thermal management system. Specifically, this includes: The vehicle simulation model, which includes a pre-built simulation model of the thermal management system, is used to simulate multiple sets of driving range test parameters. The energy consumption data of the main energy-consuming components in the simulation is compared with the energy consumption data in the test. By adjusting the efficiency model or operating characteristic curve of each main energy-consuming component, the consistency between the simulation data and the test data is achieved. The main energy-consuming components include multiple components such as the air conditioning compressor, PTC, cooling fan, electric water pump and air conditioning blower.

[0064] The calibration and correction of corresponding components in the pre-built thermal management system simulation model using whole vehicle test data also includes: By comparing the key performance parameters of the battery system in simulation and experiment, and correcting the battery model parameters, consistency between the simulation data and the experimental data is achieved. The key performance parameters of the battery system include at least one of the following: terminal voltage information, output current information, and cumulative energy consumption information.

[0065] This embodiment tests the driving range of the target electric vehicle through a full-vehicle range test and obtains energy consumption analysis. The range test is conducted in a controlled environmental chamber, and the specific operation is as follows: All test vehicles underwent pretreatment before the official start. For normal temperature conditions, the vehicles were briefly immersed in an environmental chamber to allow the vehicle temperature to equalize with the ambient temperature. No additional weight was used except for the driver throughout the test. The test was conducted in two phases: First, two WLTC cycles were performed with the air conditioning off, followed by driving at a constant speed until the battery level reached 10%; second, two more WLTC cycles were performed without air conditioning, followed by driving at a constant speed until the battery was depleted, to separate the energy consumption contribution of different driving modes. For high and low temperature conditions, more stringent pretreatment procedures were implemented, namely, immersion of the vehicles in an environmental chamber for up to 2 hours (high temperature) and 10 hours (low temperature) to simulate the static state of the vehicle under extreme climate conditions, ensuring that the initial temperature of the battery and passenger compartment was consistent with the test environment.

[0066] During the tests, the vehicle's initial battery level was 100%. In the dynamic testing phase, the vehicle strictly followed the WLTC cycle on a chassis dynamometer until the minimum battery level was reached. To simulate real-world user scenarios, the air conditioning system was initially set to the lowest temperature in the high-temperature test, then gradually increased to 22°C; conversely, in the low-temperature test, it was initially set to the highest temperature, then gradually decreased to 22°C. This setup aimed to examine the dynamic impact of the air conditioning system's instantaneous peak power and steady-state maintenance power under extreme cooling and heating demands on the driving range. Driving range data was directly collected by a high-precision chassis dynamometer. After each test, the battery was fully charged using slow charging within two hours, and the charging power and total charging energy were recorded throughout the process to calculate the vehicle's charging characteristics and overall energy efficiency under different environments.

[0067] refer to Figure 7 The pre-construction of a full-vehicle simulation model involves building models related to power performance and power consumption, models related to thermal management performance and power consumption, and control models for thermal management components consistent with the real vehicle, ensuring a high degree of realism in the simulation environment. After model integration, a "power-thermal coupling energy management simulation model" (referred to as the power-thermal model) is formed. This model comprehensively considers the interaction between the power system and the thermal management system, achieving efficient energy management and distribution. Post-processing is performed on the parameters in the power-thermal model to calculate the energy consumption of thermal management-related power components such as the compressor, fan, water pump, PTC, and blower, as well as the energy consumption of the battery and motor, driving range, and other parameters, outputting the energy distribution and flow direction. Finally, the results are compared with the vehicle energy consumption test results to correct parameters such as driving range and battery consumption in the simulation results.

[0068] This embodiment proposes to acquire energy consumption and range performance data of a typical electric vehicle under real-world operating conditions through a full-vehicle range test. It focuses on analyzing the energy consumption proportion of the thermal management system, thereby revealing its key role in improving the energy efficiency of electric vehicles and its potential for optimization. To further understand the performance characteristics of the thermal management system, it also proposes to conduct individual performance tests and system bench tests on thermal management components to obtain operating data for corresponding components or systems under various key operating conditions. This allows for in-depth exploration of the performance and energy consumption characteristics of core components under different operating conditions. Through system bench testing, key data such as the overall energy consumption of the system are comprehensively acquired, providing a solid experimental foundation for subsequent simulation model construction. To more efficiently predict and optimize the performance of the thermal management system, a simulation model of the full-vehicle thermal management system, consistent with the actual vehicle structure and parameters, is constructed. The model is calibrated using experimental data to ensure the accuracy of the output results. Finally, after repeated debugging and optimization, accurate simulation capabilities under different temperatures and operating conditions are achieved.

[0069] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for constructing a strong-fitting-capability simulation model of a whole-vehicle thermal management system of a pure electric vehicle, characterized in that, include: By using test data from various component performance tests, thermal management system performance tests, and whole vehicle performance tests, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected sequentially to obtain the calibrated simulation model, thus completing the construction of the simulation model.

2. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 1, characterized in that, The components include heat exchangers, which consist of evaporators and condensers. Performance testing of the heat exchangers specifically includes: The heat exchanger is placed in an air duct with adjustable temperature, humidity, and air velocity. Refrigerant is introduced into the heat exchanger to conduct a heat exchange performance test. Multiple test conditions are designed by changing the variable parameters in the test. The variable parameters include multiple parameters such as air duct volume, air velocity, inlet air temperature, refrigerant flow rate, and refrigerant inlet temperature. Key performance parameters are obtained under each test condition. Key performance parameters include multiple parameters such as refrigerant side inlet and outlet pressure drop, refrigerant side heat exchange, and air side heat exchange. Accordingly, the test data of the components are used to calibrate and correct the corresponding components in the pre-built thermal management system simulation model, specifically including: Under multiple test conditions, simulation analysis with the same operating parameters was performed using the simulation model. By adjusting the structural parameters of the corresponding heat exchanger in the simulation model, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

3. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 1, characterized in that, The components also include the compressor, and the performance tests on the compressor specifically include: The compressor is subjected to refrigerant gas compression tests; the test conditions include different discharge pressures and different speeds; under each test condition, the inlet and outlet temperatures, pressures, flow rates, and power data are monitored, and the volumetric efficiency, isentropic compression efficiency, and mechanical efficiency of the compressor are obtained based on the monitoring data; by combining the data from multiple test conditions, the volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve of the compressor are obtained. Accordingly, the obtained volumetric efficiency curve, isentropic compression efficiency curve, and mechanical efficiency curve are used to calibrate the compressor efficiency parameters in the simulation model.

4. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 1, characterized in that, Performance testing of the thermal management system includes performance testing of the air conditioning system circuits, specifically: An air conditioning system circuit test bench was built according to the actual vehicle principle of the target model to conduct heating and cooling performance tests. The relevant components of the air conditioning system circuit were arranged in two controllable air ducts and the pipes were connected according to the actual connection relationship. The controllable air ducts are air ducts with adjustable intake air temperature, humidity and wind speed. One of the two controllable air ducts simulates the indoor environment of the driver's cab and the other simulates the outdoor environment. Temperature and pressure sensors were installed at the compressor inlet and outlet, the heat exchanger inlet and outlet, and a temperature sensor was installed at the air outlet of the controllable air duct. A mass flow meter was added to the circuit, and a power meter was connected to the compressor to obtain the monitoring values ​​during the test.

5. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 4, characterized in that, The specific test condition design for performance testing of the air conditioning system circuit is as follows: Based on the purpose of the cold source in the cooling mode, the cooling mode is divided into multiple types; based on the source of the heat source in the heating mode, the heating mode is divided into multiple types; for each cooling mode, the compressor speed, the temperature and / or flow rate of the cold source on the convection side are changed to form multiple test conditions; for each heating mode, the compressor speed, the temperature and / or flow rate of the heat source are changed to form multiple test conditions.

6. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 5, characterized in that, The corresponding components in the pre-built thermal management system simulation model are calibrated and corrected using system test data, specifically including: For each set of test conditions, key performance parameters were obtained, including at least one of the following: heat exchanger heat exchange capacity, compressor inlet and outlet pressure, and compressor power consumption. Under multiple test conditions, simulation analysis with the same operating parameters was performed using a simulation model. By adjusting at least one of the following parameters in the simulation model: compressor efficiency parameter, heat exchanger structural parameter, pressure drop gain coefficient, and expansion valve opening flow characteristics, the key performance parameters obtained by the simulation model under the same operating parameters were made consistent with the experimental data.

7. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 5, characterized in that, The calibration and correction of corresponding components in the pre-built thermal management system simulation model using system test data also includes: Record the transitional data of the monitored quantities during the change of test conditions, and compile the curves of the changes in the monitored quantities; The same experimental conditions are performed in the simulation model, and the trend of the monitored quantities in the simulation is recorded. By adjusting at least one of the following: the expansion valve time constant, the compressor speed switching rate, and the specific heat capacity property of the heat exchanger material, the trend of the simulation is made consistent with that in the experiment.

8. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting ability as described in any one of claims 2-7, characterized in that, The performance tests on various components, thermal management system and whole vehicle of the target model also include: obtaining the flow rate change of refrigerant in the flow path under each test condition, using the refrigerant flow rate change to judge the validity of the test, and selecting the test data under the valid test conditions for simulation calibration.

9. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 1, characterized in that, The performance tests conducted on the entire vehicle specifically include: Conduct driving range tests under different temperature conditions, and obtain vehicle energy consumption distribution information and driving range information under each set of test conditions; Accordingly, the corresponding components in the pre-built thermal management system simulation model are calibrated and corrected using vehicle test data, specifically including: The vehicle simulation model, which includes a pre-built simulation model of the thermal management system, is used to simulate multiple sets of driving range test parameters. The energy consumption data of the main energy-consuming components in the simulation is compared with the energy consumption data in the test. By adjusting the efficiency model or operating characteristic curve of each main energy-consuming component, the consistency between the simulation data and the test data is achieved. The main energy-consuming components include multiple components such as the air conditioning compressor, PTC, cooling fan, electric water pump and air conditioning blower.

10. The method for constructing a simulation model of a pure electric vehicle thermal management system with strong fitting capability as described in claim 9, characterized in that, The calibration and correction of corresponding components in the pre-built thermal management system simulation model using whole vehicle test data also includes: By comparing the key performance parameters of the battery system in simulation and experiment, and correcting the battery model parameters, consistency between the simulation data and the experimental data is achieved. The key performance parameters of the battery system include at least one of the following: terminal voltage information, output current information, and cumulative energy consumption information.

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