Multi-actuator cooperative thermal management system adaptive PID control method and controller
By employing a multi-actuator collaborative adaptive PID control method, combined with feedforward and cascade PID control and a multi-heat source coupled prediction model, the problems of unstable temperature control and high energy consumption in the thermal management system of new energy vehicles are solved, achieving high-precision, low-energy-consumption, and high-reliability thermal management control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING XIEZHONG AUTO AIRCONDITIONER (GROUP) CO LTD
- Filing Date
- 2026-05-09
- Publication Date
- 2026-07-10
AI Technical Summary
Existing automotive thermal management systems suffer from problems such as unstable temperature control, high energy consumption, frequent actuator operation, and mode switching shocks in multi-actuator collaborative control. Furthermore, existing control strategies have poor adaptability under complex operating conditions, making it difficult to meet the high precision, low energy consumption, and high reliability requirements of new energy vehicles.
An adaptive PID control method with multi-actuator collaboration is adopted, which combines feedforward and cascade PID control to establish a multi-heat source coupled prediction model. By adaptively adjusting PID parameters and actuator anti-jitter control, the temperature control accuracy of the thermal management system is improved and energy consumption is reduced, and smooth mode switching is performed under complex operating conditions.
It achieves improved temperature control accuracy of the thermal management system to within ±0.5℃, reduces energy consumption by 8%~12%, maintains system stability and comfort under complex operating conditions, has strong adaptability, and supports the mass production needs of the whole vehicle.
Smart Images
Figure CN122354162A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automotive thermal management system technology, specifically to an adaptive PID control method and controller for a multi-actuator collaborative thermal management system. Background Technology
[0002] With the rapid development of new energy vehicles, the vehicle thermal management system has evolved from a single air conditioning control to a multi-loop collaborative system integrating battery cooling and heating, motor electronic control heat dissipation, and heat pump air conditioning regulation. The system includes multiple actuators such as electronic water pumps, electronic expansion valves, PTC heaters, and four-way valves. The operating states of these actuators are coupled, placing higher demands on temperature control accuracy, response speed, and energy consumption control. Currently, traditional thermal management control often uses independent PID regulation, with actuators such as water pumps, expansion valves, and heating modules each operating in a closed loop based on a single temperature signal. This fails to fully consider the coupled effects of multiple heat sources, such as battery temperature rise, motor heat loss, and ambient temperature, easily leading to problems such as temperature overshoot, large steady-state deviation, and frequent actuator actuation. Furthermore, existing control strategies often use fixed PID parameters, resulting in poor adaptability to changes in operating conditions such as high-speed driving, fast charging, and low-temperature environments, leading to unstable temperature control and high system energy consumption. In addition, some existing solutions lack smooth transition logic when switching between cooling, heating, waste heat recovery, and defrosting modes, easily causing temperature shocks and actuator actuation shocks, affecting system reliability and ride comfort. Although some collaborative control strategies have been proposed, they generally suffer from problems such as insufficient feedforward prediction, weak parameter adaptation capability, and lack of actuator anti-jitter mechanism, making it difficult to meet the high-precision, low-energy-consumption, and high-reliability thermal management control requirements of the new generation of new energy vehicles. Summary of the Invention
[0003] Technical objective: To address the shortcomings of existing automotive thermal management systems, this invention discloses an adaptive PID control method and controller for a multi-actuator collaborative thermal management system.
[0004] Technical solution: To achieve the above technical objectives, the present invention adopts the following technical solution: An adaptive PID control method for a multi-actuator cooperative thermal management system includes the following steps: S01. Collect parameters of the thermal management system; S02. Establish a multi-heat source coupling prediction model and calculate the heat load demand of the thermal management system. S03. Based on the heat load demand and the collected thermal management system parameters, a feedforward and cascade PID collaborative control method is adopted to output the control quantity. The feedforward output control quantity of the thermal management system is calculated based on the heat load demand of the thermal management system. The deviation value e between the target temperature and the actual collected temperature is calculated based on the collected thermal management system parameters. Based on the deviation value e, the main loop of the cascade PID uses the heat exchange outlet water temperature of the thermal management system as the main loop output control quantity, and uses the electric water pump speed and the opening degree of the electric expansion valve of the thermal management system as the PID secondary loop. The output control quantity of the main loop is distributed as the electric water pump speed control quantity and the electric expansion valve opening degree control quantity, and the feedforward output control quantity is corrected to obtain the final output control quantity.
[0005] Preferably, in step S03 of the present invention, the feedforward output control quantity includes the initial control quantity n0 of the electronic water pump speed and the initial control quantity θ0 of the electronic expansion valve opening: n0=k3×Q, θ0=k4×Q, k3 and k4 are both proportional coefficients, and Q is the calculated heat load requirement.
[0006] Preferably, in step S03 of the present invention, the main loop output control quantity U_main = Kp_main×e + Ki_main×∫e dt + Kd_main×de / dt, where Kp_main, Ki_main, and Kd_main are the main loop PID parameters.
[0007] Preferably, in step S03 of the present invention, the electronic water pump speed control quantity U_pump = Kp_pump×(n_target - n_actual) + Ki_pump×∫(n_target-n_actual)dt + Kd_pump×d(n_target -n_actual) / dt; the electronic expansion valve opening control quantity U_valve = Kp_valve×(θ_target-θ_actual) + Ki_valve×∫(θ_target - θ_actual)dt + Kd_valve×d(θ_target - θ_actual) / dt, where Kp_pump, Ki_pump, and Kd_pump are the PID parameters of the electronic water pump secondary loop, and Kp_valve, Ki_valve, and Kd_valve are the PID parameters of the electronic expansion valve secondary loop; the final output control quantity is the electronic water pump speed n = n0 + U_pump, and the electronic expansion valve opening θ = θ0 + U_valve.
[0008] Preferably, the thermal management system parameters of the present invention include: acquiring battery pack temperature, motor winding temperature, and ambient temperature and humidity through an NTC temperature sensor; receiving vehicle speed, battery charging rate, and motor output power signals sent by the vehicle's VCU via a CAN bus; and acquiring thermal management system pipeline pressure through a pressure sensor.
[0009] Preferably, the initial values of Kp_main, Ki_main, and Kd_main are 2.5, 0.1, and 0.05, respectively; the initial values of Kp_pump, Ki_pump, and Kd_pump are 1.8, 0.08, and 0.03, respectively; and the initial values of Kp_valve, Ki_valve, and Kd_valve are 1.8, 0.08, and 0.03, respectively. The PID parameters are adaptively adjusted based on the thermal management system parameters collected in step S01, as follows: Under operating conditions, when the vehicle speed is ≥100km / h, adjust the main ring Kp_main to 3.0 and Ki_main to 0.08; Under charging conditions, when the battery charging rate is ≥1C, adjust the main ring Kp_main to 3.2, Ki_main to 0.12, and the secondary ring Kp_pump to 2.0; Under low-temperature conditions, when the ambient temperature is ≤-10℃, adjust the main ring Ki_main to 0.15 and the secondary ring Ki_valve to 0.1; Under steady-state conditions, when the heat load fluctuation is ≤5% and the temperature deviation is ≤0.3℃, adjust the main loop Kd_main to 0.03 and Kd_pump and Kd_valve to 0.02.
[0010] Preferably, in step S02 of the present invention, when establishing the multi-heat source coupling prediction model, the battery temperature rise rate calculation formula is obtained based on the experimental data fitting: ΔT_bat = k1×C_rate² + k2×(T_env-25), where ΔT_bat is the battery temperature rise rate in °C / min, C_rate is the battery charging rate in C, T_env is the ambient temperature in °C, and k1 and k2 are fitting coefficients calibrated according to the specific battery type; The formula for calculating the real-time heat loss of the motor is: P_loss = P_out×(1 - η), where P_loss is the heat loss of the motor in W, P_out is the output power of the motor in W, and η is the motor efficiency. The heat dissipation of the pipeline is calculated based on the pipeline material and structure, and the heat dissipation coefficient of the pipeline is calibrated, with the heat dissipation amount Q_radiation in W. The real-time heat load demand of the thermal management system is obtained by integrating the formula: Q = ΔT_bat×m_bat×c_bat + P_loss - Q_radiation, where m_bat is the mass of the battery pack in kg, and c_bat is the specific heat capacity of the battery in J / (kg·℃).
[0011] Preferably, when performing PID control on the actuators of the thermal management system, the present invention sets dead zones and rate of change limits for each actuator of the thermal management system: when the temperature deviation is ≤ ±0.3℃, the actuator control quantity is not adjusted; the rate of change of the electronic water pump speed is limited to ≤ 500 rpm / s; and the rate of change of the electronic expansion valve opening is limited to ≤ 5 steps / s.
[0012] Preferably, the thermal management system of the present invention switches between four working modes—cooling, heating, waste heat recovery, and defrosting—based on heat load demand and ambient temperature. One second before switching working modes, the speed of the electronic water pump and the opening of the electronic expansion valve are adjusted to the initial control value of the target mode. Simultaneously, the PTC and four-way valve of the thermal management system are gradually switched. During the switching process, the PID parameters are corrected in real time to maintain the target temperature deviation ≤0.8℃. Two seconds after switching, the PID control parameters and actuator control values are stabilized to complete the mode transition.
[0013] This invention provides a controller for the above-described control method, comprising: a signal acquisition module for executing step S01, acquiring parameters of the thermal management system; a control core module, which incorporates a multi-heat source coupling prediction model, an adaptive PID control algorithm, and mode switching logic, for executing steps S02 and S03; and a drive output module for driving the thermal management system actuators according to the calculated final output control quantity.
[0014] Beneficial Effects: The adaptive PID control method and controller for a multi-actuator collaborative thermal management system disclosed in this invention have the following beneficial effects: 1. The thermal management system of the present invention adopts a feedforward and cascade PID control strategy, combined with multi-heat source coupling prediction of the automotive thermal management system, effectively solving the problems of temperature overshoot and oscillation in traditional control methods, and improving the temperature control accuracy of the thermal management system to within ±0.5℃; the temperature control accuracy is significantly improved.
[0015] 2. This invention reduces the frequency of actuator operation by more than 30% through PID parameter adaptive tuning and actuator anti-vibration control, and reduces energy consumption by 8% to 12% under low temperature heat pump conditions, effectively improving the vehicle's driving range and significantly reducing energy consumption.
[0016] 3. This invention can dynamically adjust control parameters for various complex operating conditions such as high speed, fast charging, and low temperature, and achieve smooth switching between multiple modes. It can adapt to the complex operating needs of new energy vehicles and has strong adaptability to operating conditions.
[0017] 4. The controller of the present invention can use automotive-grade components, has complete fault detection and protection functions, supports UDS diagnosis, and can be directly connected to the mass production requirements of the whole vehicle, which facilitates industrial application and promotion. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.
[0019] Figure 1 This is a flowchart of the control method of the present invention; Figure 2 This is a block diagram of the controller structure of the present invention; Detailed Implementation
[0020] Reference will now be made in detail to embodiments of the present disclosure, one or more of which are set forth herein. Each embodiment and example is provided by way of explanation of the apparatus, composition, and materials of the present disclosure, and not by way of limitation. Rather, the following description provides convenient illustrations for implementing exemplary embodiments of the present disclosure. Indeed, it will be apparent to those skilled in the art that various modifications and variations can be made to the teachings of the present disclosure without departing from the scope or spirit of the present disclosure.
[0021] like Figure 1 As shown, an adaptive PID control method for a multi-actuator collaborative thermal management system includes the following steps: S01. Collect parameters of the thermal management system; The thermal management system acquires multiple parameters from seven sources, including battery pack temperature, motor winding temperature, and ambient temperature and humidity, all acquired via an NTC temperature sensor. The temperature acquisition accuracy is ±0.1℃, and the acquisition frequency is 10Hz. The ambient temperature and humidity acquisition frequency is 5Hz. The system also receives vehicle speed, battery charging rate, and motor output power signals from the vehicle's VCU via the CAN bus, with the motor output power signal acquisition frequency at 10Hz. Finally, the system acquires the thermal management system pipeline pressure via a pressure sensor, with an acquisition accuracy of ±0.01MPa and an acquisition frequency of 5Hz.
[0022] For the above multi-source parameters, filtering is performed after acquisition to remove interference noise and ensure signal accuracy.
[0023] S02. Establish a multi-heat source coupling prediction model and calculate the heat load demand Q of the thermal management system; In step S02 of this invention, when establishing the multi-heat source coupling prediction model, the battery temperature rise rate calculation formula is obtained based on the fitting of experimental data: ΔT_bat = k1×C_rate² + k2×(T_env-25), where ΔT_bat is the battery temperature rise rate in °C / min, C_rate is the battery charging rate in C, T_env is the ambient temperature in °C, and k1 and k2 are fitting coefficients calibrated according to the specific battery type. In this embodiment, k1=0.8 and k2=0.05.
[0024] The formula for calculating the real-time heat loss of the motor is: P_loss = P_out×(1 - η), where P_loss is the heat loss of the motor in W, P_out is the output power of the motor in W, and η is the motor efficiency. The heat dissipation of the pipeline is calculated based on the pipeline material and structure, with the pipeline heat dissipation coefficient in W. In this embodiment, the pipeline heat dissipation coefficient of the thermal management system is 12W / (m·℃). The real-time heat load demand of the thermal management system is obtained as Q = ΔT_bat×m_bat×c_bat + P_loss - Q_radiation, where m_bat is the mass of the battery pack in kg, and c_bat is the specific heat capacity of the battery in J / (kg·℃).
[0025] S03. Based on the heat load demand and the collected thermal management system parameters, a feedforward and cascade PID collaborative control method is adopted to output the control quantity. The feedforward output control quantity of the thermal management system is calculated based on the heat load demand of the thermal management system. The deviation value e between the target temperature and the actual collected temperature is calculated based on the collected thermal management system parameters. Based on the deviation value e, the main loop of the cascade PID uses the heat exchange outlet water temperature of the thermal management system, i.e., the target outlet water temperature, as the main loop output control quantity, and uses the electronic water pump speed and electronic expansion valve opening of the thermal management system as the PID secondary loop. The main loop output control quantity is distributed as the electronic water pump speed control quantity and the electronic expansion valve opening control quantity, and the feedforward output control quantity is corrected to obtain the final output control quantity.
[0026] The target temperature T_target of the thermal management system is set according to the thermal management object. The target temperature for normal operation of the battery pack is 25℃~35℃, the target temperature for fast charging is 30℃, and the target temperature for normal driving is 28℃. The target temperature for the motor winding is ≤120℃, and the target outlet temperature of the thermal management system is 45℃±0.5℃.
[0027] The deviation value e = T_target - T_actual, where T_actual is the actual collected temperature.
[0028] In step S03 of this invention, the feedforward output control quantity includes the initial control quantity n0 of the electronic water pump speed and the initial control quantity θ0 of the electronic expansion valve opening: n0=k3×Q, θ0=k4×Q, k3 and k4 are both proportional coefficients, and Q is the calculated heat load requirement. In this embodiment, k3=0.02rpm / W and k4=0.01step / W.
[0029] The main loop output control quantity of this invention is U_main = Kp_main×e + Ki_main×∫e dt + Kd_main×de / dt, where Kp_main, Ki_main, and Kd_main are the main loop PID parameters, which are the main loop proportional coefficient, integral coefficient, and derivative coefficient, respectively, with initial values of 2.5, 0.1, and 0.05, respectively.
[0030] The electronic water pump speed control value U_pump = Kp_pump×(n_target - n_actual) + Ki_pump×∫(n_target-n_actual)dt + Kd_pump×d(n_target - n_actual) / dt; The electronic expansion valve opening control quantity U_valve = Kp_valve×(θ_target-θ_actual) + Ki_valve×∫(θ_target - θ_actual)dt + Kd_valve×d(θ_target - θ_actual) / dt, where Kp_pump, Ki_pump, and Kd_pump are the PID parameters of the electronic water pump secondary loop, and the initial values of the parameters in this embodiment are 1.8, 0.08, and 0.03 respectively; Kp_valve, Ki_valve, and Kd_valve are the PID parameters of the electronic expansion valve secondary loop, and the initial values of the parameters in this embodiment are 1.8, 0.08, and 0.03 respectively.
[0031] The final output control quantities are: the electronic water pump speed n = n0 + U_pump, and the electronic expansion valve opening θ = θ0 + U_valve.
[0032] Meanwhile, the PID parameters of the main loop and the secondary loop are adaptively adjusted and corrected based on the thermal management system parameters collected in step S01, as follows: Under operating conditions, when the vehicle speed is ≥100km / h, adjust the main ring Kp_main to 3.0 and Ki_main to 0.08; Under charging conditions, when the battery charging rate is ≥1C, adjust the main ring Kp_main to 3.2, Ki_main to 0.12, and the secondary ring Kp_pump to 2.0; Under low-temperature conditions, when the ambient temperature is ≤-10℃, adjust the main ring Ki_main to 0.15 and the secondary ring Ki_valve to 0.1; When the heat load fluctuation is ≤5% and the temperature deviation is ≤0.3℃, and the duration reaches more than 45 minutes, it indicates that the vehicle thermal management system is in steady state. At this time, the main loop Kd_main is adjusted to 0.03, and Kd_pump and Kd_valve are adjusted to 0.02. The judgment duration of steady state can be shortened or extended according to specific needs.
[0033] In order to ensure stable system operation and avoid frequent system actions when performing PID control on the actuators of the thermal management system, this invention preferably sets dead zones and rate of change limits for each actuator of the thermal management system: when the temperature deviation is ≤ ±0.3℃, the actuator control quantity is not adjusted; the rate of change of the electronic water pump speed is limited to ≤ 500 rpm / s; and the rate of change of the electronic expansion valve opening is limited to ≤ 5 steps / s.
[0034] Meanwhile, in response to different operating modes of the thermal management system, the thermal management system of the present invention can also switch between four working modes—cooling, heating, waste heat recovery, and defrosting—according to heat load demand and ambient temperature, and control the operation of the thermal management system in each working mode.
[0035] To ensure a smooth switching of operating modes, this invention adjusts the speed of the electronic water pump and the opening of the electronic expansion valve to the initial control value of the target mode 1 second before switching. The initial control value of the target mode is preset according to different operating modes. Then, the PTC and four-way valve of the thermal management system are controlled synchronously to gradually switch states. During the switching process, the aforementioned feedforward and cascade PID control methods are used to correct the PID parameters in real time to maintain the target temperature deviation ≤0.8℃. 2 seconds after the switch, the PID control parameters and actuator control values are stabilized to complete the transition of the wheel's operating mode.
[0036] like Figure 2As shown, the present invention also provides a controller for the above-described control method, comprising: a signal acquisition module for executing step S01, acquiring parameters of the thermal management system; a control core module, which incorporates a multi-heat source coupling prediction model, an adaptive PID control algorithm, and mode switching logic, for executing steps S02 and S03; and a drive output module for driving the thermal management system actuator according to the calculated final output control quantity.
[0037] The signal acquisition module includes four NTC temperature sensor interfaces, which are respectively connected to the battery pack, motor winding, ambient temperature, and pipeline outlet water temperature sensors; two analog signal acquisition channels for connecting pressure sensors; and one CAN signal receiving interface, supporting the CAN2.0B protocol with a baud rate of 500kbps, for connecting to the control core module.
[0038] The signal acquisition module adopts a differential acquisition method, which has strong anti-interference capability. The acquired signal is stably transmitted to the control core module after low-pass filtering.
[0039] The control core module uses an automotive-grade MCU. In this embodiment, the Infineon AURIX TC234 chip is selected. This chip has high computing speed and high reliability and can meet the functional safety requirements of ISO 26262 ASIL-B level.
[0040] The core control module incorporates a multi-heat source coupling prediction model, an adaptive PID control algorithm, and mode switching logic. It receives input signals from the signal acquisition module, performs real-time calculations, and outputs precise actuator control commands. Simultaneously, the core control module includes a built-in Flash memory to store PID parameters, fault information, and control logic programs, facilitating subsequent debugging and maintenance.
[0041] The drive output module includes two PWM drive units for driving electronic water pumps and PTC heaters; and one H-bridge drive unit for driving electronic expansion valves and four-way valves. The PWM drive units have a flexibly adjustable output frequency (1kHz~10kHz), an output duty cycle range of 0%~100%, and a maximum drive current of 5A to meet the drive requirements of different actuators. The H-bridge drive unit supports bidirectional drive, enabling precise step control of electronic expansion valves and smooth commutation control of four-way valves. The drive output module integrates overcurrent and overtemperature protection functions. When a drive fault is detected, the corresponding output is immediately cut off, and a fault signal is simultaneously reported to the control core module.
[0042] The controller also includes auxiliary modules for assisting the operation of the thermal management system, including a fault detection module, a CAN interaction module, and a power supply module.
[0043] The CAN communication module uses an automotive-grade CAN transceiver; in this embodiment, the TJA1050 is selected. It supports the CAN 2.0B protocol, and the baud rate can be configured according to the vehicle's requirements (250kbps~1Mbps). The CAN communication module is mainly used to exchange signals with the vehicle's VCU, BMS, and air conditioning controller, synchronizing vehicle operating information such as vehicle speed, battery charging rate, and motor output power, as well as key information such as temperature, pressure, and actuator status of the thermal management system. Simultaneously, it supports the UDS diagnostic protocol, allowing fault codes to be read via 0x22 DID and cleared via 0x2 EDID, facilitating vehicle diagnostics and subsequent maintenance.
[0044] The power module adopts a wide voltage input design, with an input voltage range of 9V~16V, which can be adapted to the 12V power supply system of new energy vehicles. The power module has overvoltage (≥18V), overcurrent (≥10A), and reverse connection protection functions. Through a DC-DC conversion circuit, it stably outputs 5V and 3.3V voltages to power the various modules of the controller, ensuring that the controller operates stably in complex vehicle environments.
[0045] The fault detection module, integrated into the control core module, is used to detect actuator drive faults (overcurrent, overtemperature) and sensor faults (open circuit, short circuit, overrange) in real time. When a fault is detected, the corresponding actuator drive output is immediately cut off, the fault status (including fault code, fault type, and fault occurrence time) is reported via CAN message, and the fault information is stored in the Flash memory for subsequent fault investigation and analysis.
[0046] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. An adaptive PID control method for a multi-actuator collaborative thermal management system, characterized in that, Including the following steps: S01. Collect parameters of the thermal management system; S02. Establish a multi-heat source coupling prediction model and calculate the heat load demand of the thermal management system. S03. Based on the heat load demand and the collected thermal management system parameters, a feedforward and cascade PID collaborative control method is adopted to output the control quantity. The feedforward output control quantity of the thermal management system is calculated based on the heat load demand of the thermal management system. The deviation value e between the target temperature and the actual collected temperature is calculated based on the collected thermal management system parameters. Based on the deviation value e, the main loop of the cascade PID uses the heat exchange outlet water temperature of the thermal management system as the main loop output control quantity, and uses the electric water pump speed and the opening degree of the electric expansion valve of the thermal management system as the PID secondary loop. The output control quantity of the main loop is distributed as the electric water pump speed control quantity and the electric expansion valve opening degree control quantity, and the feedforward output control quantity is corrected to obtain the final output control quantity.
2. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 1, characterized in that, In step S03, the feedforward output control quantity includes the initial control quantity n0 of the electronic water pump speed and the initial control quantity θ0 of the electronic expansion valve opening: n0=k3×Q, θ0=k4×Q, k3 and k4 are both proportional coefficients, and Q is the calculated heat load demand.
3. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 1, characterized in that, In step S03, the main loop output control quantity U_main = Kp_main×e + Ki_main×∫e dt + Kd_main×de / dt, where Kp_main, Ki_main, and Kd_main are the main loop PID parameters.
4. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 3, characterized in that, In step S03, the electronic water pump speed control quantity U_pump = Kp_pump×(n_target - n_actual) + Ki_pump×∫(n_target-n_actual)dt + Kd_pump×d(n_target - n_actual) / dt; the electronic expansion valve opening control quantity U_valve = Kp_valve×(θ_target-θ_actual) + Ki_valve×∫(θ_target -θ_actual)dt + Kd_valve×d(θ_target - θ_actual) / dt, where Kp_pump, Ki_pump, and Kd_pump are the PID parameters of the electronic water pump secondary loop, and Kp_valve, Ki_valve, and Kd_valve are the PID parameters of the electronic expansion valve secondary loop; the final output control quantity is the electronic water pump speed n = n0 + U_pump, and the electronic expansion valve opening θ = θ0 + U_valve.
5. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 3, characterized in that, The thermal management system parameters include battery pack temperature, motor winding temperature, and ambient temperature and humidity collected via NTC temperature sensors; vehicle speed, battery charging rate, and motor output power signals received from the vehicle's VCU via CAN bus; and thermal management system pipeline pressure collected via pressure sensors.
6. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 5, characterized in that, The initial values of Kp_main, Ki_main, and Kd_main are 2.5, 0.1, and 0.05, respectively; the initial values of Kp_pump, Ki_pump, and Kd_pump are 1.8, 0.08, and 0.03, respectively; and the initial values of Kp_valve, Ki_valve, and Kd_valve are 1.8, 0.08, and 0.03, respectively. The PID parameters are adaptively adjusted based on the thermal management system parameters collected in step S01, as follows: Under operating conditions, when the vehicle speed is ≥100km / h, adjust the main ring Kp_main to 3.0 and Ki_main to 0.08; Under charging conditions, when the battery charging rate is ≥1C, adjust the main ring Kp_main to 3.2, Ki_main to 0.12, and the secondary ring Kp_pump to 2.0; Under low-temperature conditions, when the ambient temperature is ≤-10℃, adjust the main ring Ki_main to 0.15 and the secondary ring Ki_valve to 0.1; Under steady-state conditions, when the heat load fluctuation is ≤5% and the temperature deviation is ≤0.3℃, adjust the main loop Kd_main to 0.03 and Kd_pump and Kd_valve to 0.
02.
7. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 1, characterized in that, In step S02, when establishing the multi-heat source coupling prediction model, the battery temperature rise rate calculation formula is obtained based on the experimental data fitting: ΔT_bat = k1×C_rate² + k2×(T_env-25), where ΔT_bat is the battery temperature rise rate in °C / min, C_rate is the battery charging rate in C, T_env is the ambient temperature in °C, and k1 and k2 are fitting coefficients calibrated according to the specific battery type; The formula for calculating the real-time heat loss of the motor is: P_loss = P_out×(1 - η), where P_loss is the heat loss of the motor in W, P_out is the output power of the motor in W, and η is the motor efficiency. The heat dissipation of the pipeline is calculated based on the pipeline material and structure, and the heat dissipation coefficient of the pipeline is calibrated, with the heat dissipation amount Q_radiation in W. The real-time heat load demand of the thermal management system is obtained by integrating the formula: Q = ΔT_bat×m_bat×c_bat + P_loss - Q_radiation, where m_bat is the mass of the battery pack in kg, and c_bat is the specific heat capacity of the battery in J / (kg·℃).
8. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 1, characterized in that, When performing PID control on the actuators of the thermal management system, the dead zone and rate of change limits for each actuator are set: when the temperature deviation is ≤ ±0.3℃, the actuator control quantity is not adjusted; the rate of change of the electronic water pump speed is limited to ≤ 500 rpm / s; and the rate of change of the electronic expansion valve opening is limited to ≤ 5 steps / s.
9. The adaptive PID control method for a thermal management system of a multi-actuator system according to claim 1, characterized in that, The thermal management system switches between four working modes—cooling, heating, waste heat recovery, and defrosting—based on heat load demand and ambient temperature. One second before switching modes, the electronic water pump speed and electronic expansion valve opening are adjusted to the initial control values of the target mode. Simultaneously, the PTC and four-way valve of the thermal management system are gradually switched. During the switching process, the PID parameters are corrected in real time to maintain the target temperature deviation ≤0.8℃. Two seconds after switching, the PID control parameters and actuator control values are stabilized to complete the mode transition.
10. A controller for executing the control method according to any one of claims 1-9, characterized in that, include: The signal acquisition module is used to execute step S01 and acquire the parameters of the thermal management system; the control core module has a built-in multi-heat source coupling prediction model, adaptive PID control algorithm and mode switching logic, and is used to execute steps S02 and S03; the drive output module is used to drive the thermal management system actuators according to the calculated final output control quantity.