Vehicle thermal management unit control method, system and equipment for cabin air conditioning system

Abstract

The invention relates to the technical field of thermal management control, and discloses a vehicle thermal management unit control method, system and equipment for a cabin air conditioning system. The method comprises the steps that temperature data of a battery pack, a heating system, an evaporator and the environment are collected, temperature priority judgment calculation is conducted in combination with a user set temperature and a battery target temperature, and a working state characteristic value and a mode signal are obtained; based on the signal and the characteristic value, the temperature difference is calculated through a PID algorithm, and a compressor control instruction is generated; the valve opening degree is calculated according to the compressor parameters and the superheat degree data, and an electronic expansion valve control signal is output; the liquid level and the water pump state are obtained for safety judgment, and a water pump and PTC control instruction is generated; monitoring operation parameters of the compressor and executing oil return control; and carrying out validity judgment on the sensor, and carrying out parameter correction and fault reporting when the sensor fails. According to the invention, reasonable distribution and accurate control of the cooling capacity are realized in a two-in-one system in which the battery cooling and the cabin air conditioner share one compressor.

Description

Technical Field

[0001] The present application relates to the field of thermal management control technology, and in particular to a method, system and device for controlling a thermal management unit of a cabin air conditioning system. Background Art

[0002] The cabin air conditioning and battery thermal management system of electric vehicles are key components to ensure safe vehicle operation and passenger comfort. At present, the mainstream thermal management solutions for electric vehicles usually adopt a design method that separates the battery cooling system and the cabin air conditioning system, that is, using independent refrigeration circuits to provide cooling for the battery pack and the cabin respectively. Although this design has a simple control logic, it requires the configuration of two independent sets of core components such as compressors and condensers, which not only increases the system cost and weight, but also reduces the space utilization of the vehicle. In recent years, some vehicle manufacturers have begun to try a two-in-one system that integrates battery cooling and cabin air conditioning functions. Through the integration of the system architecture, the battery cooling and cabin air conditioning share a compressor to achieve the purpose of reducing costs and improving system efficiency.

[0003] However, the existing two-in-one thermal management system still has some technical difficulties in practical application: because the system needs to meet the temperature requirements of two different objects, the cabin and the battery, the control difficulty of the refrigerant system is significantly increased. In particular, in terms of system oil return, low-temperature refrigerant migration, cold distribution calibration, valve control, etc., the existing control strategies are often difficult to achieve precise control. For example, when cooling the battery in a low-temperature environment, the refrigerant is easy to accumulate in the evaporator, resulting in a decrease in the system's refrigeration performance; when the cabin air conditioning and battery cooling are running at the same time, unreasonable cold distribution may affect passenger comfort or battery temperature control effects; in addition, improper system oil return control may also lead to poor lubrication of the compressor, affecting the reliability and life of the system. Summary of the invention

[0004] One purpose of the present application is to provide a vehicle thermal management unit control method, system and equipment for a cabin air-conditioning system, which is used to achieve reasonable distribution and precise control of cooling capacity in a two-in-one system in which battery cooling and cabin air-conditioning share a compressor, while solving key technical problems such as system oil return and low-temperature refrigerant migration, to ensure that the system can operate stably and reliably under various operating conditions.

[0005] To achieve the above objectives, some embodiments of the present application provide the following aspects:

[0006] In a first aspect, the present application provides a method for controlling a thermal management unit of a cabin air conditioning system, the method comprising: combining the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller, with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and performing a determination and calculation according to a preset temperature priority to obtain a system working state characteristic value and a system working mode signal; based on the system working mode signal and the system working state characteristic value, using P The ID control algorithm calculates the difference between the battery target temperature and the actual temperature or the difference between the target evaporation temperature and the actual evaporation temperature, and generates the compressor reference speed value and the compressor operation control instruction in combination with the compressor minimum operation time parameter; the valve reference opening value is calculated by the preset opening algorithm based on the compressor reference speed value, the compressor operation control instruction and the system superheat data, and the valve reference opening value is compensated according to the high and low pressure sensor data, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are output; the liquid level sensor and the water pump working state signal are obtained, and the system working state characteristic value, the compressor reference speed value and the valve reference opening value are combined to perform safety judgment calculations, generate the water pump speed optimization value and the PTC power control instruction, and the water pump speed optimization value and the PTC power control instruction are combined. The control command is sent to the vehicle controller through the CAN bus; based on the compressor reference speed value, the compressor operation control command and the valve reference opening value, the compressor operation current value is obtained, and the oil return demand is calculated according to the preset judgment threshold. When the oil return demand calculation result exceeds the threshold, the compressor oil return speed value and the electronic expansion valve oil return opening value are output; the validity of each sensor signal in the system working state characteristic value is judged. When a sensor failure is detected, the normal sensor data is used to perform parameter interpolation calculation to generate a corrected system working state characteristic value, and the compressor operation control command, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control command are adjusted based on the corrected system working state characteristic value, and the fault information is recorded and uploaded to the vehicle system through the CAN bus.

[0007] In a second aspect, the present application provides a vehicle thermal management unit control system for a cabin air conditioning system, the system comprising:

[0008] The acquisition module is used to combine the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and perform determination and calculation according to the preset temperature priority to obtain the system working state characteristic value and the system working mode signal;

[0009] a calculation module, for calculating the difference between the target battery temperature and the actual battery temperature or the difference between the target evaporation temperature and the actual evaporation temperature based on the system working mode signal and the system working state characteristic value by using a PID control algorithm, and generating a compressor reference speed value and a compressor operation control instruction in combination with a compressor minimum operation time parameter;

[0010] A compensation module, used to calculate a valve reference opening value through a preset opening algorithm according to the compressor reference speed value, the compressor operation control instruction and the system superheat data, and to perform compensation operation on the valve reference opening value according to the high and low pressure sensor data, and output an evaporator electronic expansion valve opening control signal and an electronic expansion valve opening control signal;

[0011] A control module is used to obtain the working state signals of the liquid level sensor and the water pump, perform safety determination calculations in combination with the system working state characteristic value, the compressor reference speed value and the valve reference opening value, generate a water pump speed optimization value and a PTC power control instruction, and send the water pump speed optimization value and the PTC power control instruction to the vehicle controller via the CAN bus;

[0012] an acquisition module, configured to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, calculate the oil return demand according to a preset determination threshold, and output the compressor oil return speed value and the electronic expansion valve oil return opening value when the oil return demand calculation result exceeds the threshold;

[0013] A correction module is used to judge the validity of each sensor signal in the system working state characteristic value. When a sensor failure is detected, normal sensor data is used to perform parameter interpolation calculation to generate a corrected system working state characteristic value, and based on the corrected system working state characteristic value, the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction are adjusted, and fault information is recorded and uploaded to the vehicle system through the CAN bus.

[0014] In a third aspect, some embodiments of the present application further provide an electronic device, comprising: one or more processors; and a memory storing computer program instructions, wherein the computer program instructions, when executed, cause the processor to perform the steps of the method described above.

[0015] In the technical solution provided by the present application, by comprehensively analyzing the inlet and outlet temperatures of the battery pack, the inlet and outlet temperatures of the warm air system, the evaporator temperature and the ambient temperature data, the accurate judgment of the system working state and the mode switching control are realized, and the stability and reliability of the system operation are improved. The PID control algorithm is used to accurately control the temperature difference, and combined with the setting of the minimum operating time parameters of the compressor, the frequent start and stop of the compressor is effectively avoided, and the service life of the compressor is extended. The electronic expansion valve is accurately controlled by the preset opening algorithm and pressure compensation operation, ensuring that the system can maintain an appropriate superheat under different working conditions, thereby improving the refrigeration efficiency of the system. At the same time, based on the real-time monitoring of the working status of the liquid level sensor and the water pump, combined with the safety judgment operation, the reliable operation of the water system is realized, and the dry burning and other faults of the water system are effectively prevented. In addition, the method also includes a complete oil return control strategy. By continuously monitoring and analyzing the operating status of the compressor, the oil return control is carried out in time to ensure the lubrication effect of the compressor. In terms of sensor fault handling, the parameter interpolation calculation and system state characteristic value correction are adopted to enable the system to maintain basic functions in the case of sensor failure, thereby improving the fault tolerance of the system. The entire control process communicates with the vehicle system through the CAN bus, realizing real-time transmission of control information and timely reporting of fault information, which facilitates system maintenance and fault diagnosis. This application realizes efficient integration of battery temperature control and cabin air conditioning through multiple protection strategies and precise control algorithms, improving energy efficiency while ensuring system reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0017] Figure 1 A schematic diagram of an embodiment of a method for controlling a vehicle thermal management unit of a cabin air conditioning system in an embodiment of the present application;

[0018] Figure 2 A schematic diagram of an embodiment of a control system for a vehicle thermal management unit of a cabin air conditioning system in an embodiment of the present application;

[0019] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of a vehicle thermal management unit control method of a cabin air conditioning system in an embodiment of the present application includes:

[0022] Step S101, the battery pack water inlet and outlet temperatures, the heating system water inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller are combined with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and a determination and calculation are performed according to the preset temperature priority to obtain the system working state characteristic value and the system working mode signal;

[0023] Step S102: Based on the system working mode signal and the system working state characteristic value, the difference between the battery target temperature and the actual temperature or the difference between the target evaporation temperature and the actual evaporation temperature is processed by using the PID control algorithm, and combined with the compressor minimum operating time parameter, a compressor reference speed value and a compressor operating control instruction are generated;

[0024] Step S103, according to the compressor reference speed value, the compressor operation control instruction and the system superheat data, the valve reference opening value is calculated by a preset opening algorithm, and the valve reference opening value is compensated according to the high and low pressure sensor data, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are output;

[0025] Step S104, obtaining the working state signals of the liquid level sensor and the water pump, combining the system working state characteristic value, the compressor reference speed value and the valve reference opening value, performing safety determination calculation, generating the water pump speed optimization value and the PTC power control instruction, and sending the water pump speed optimization value and the PTC power control instruction to the vehicle controller through the CAN bus;

[0026] Step S105, based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, the compressor operation current value is obtained, and the oil return demand is calculated according to the preset judgment threshold value. When the oil return demand calculation result exceeds the threshold value, the compressor oil return speed value and the electronic expansion valve oil return opening value are output;

[0027] Step S106, judging the validity of each sensor signal in the system working state characteristic value. When a sensor failure is detected, using normal sensor data to perform parameter interpolation calculation, generate a corrected system working state characteristic value, and adjust the compressor operation control instruction, evaporator electronic expansion valve opening control signal, electronic expansion valve opening control signal, water pump speed optimization value and PTC power control instruction based on the corrected system working state characteristic value. At the same time, record the fault information and upload it to the vehicle system through the CAN bus.

[0028] It is understandable that the execution subject of the present application may be a vehicle thermal management unit control system of a cabin air conditioning system, or may be a terminal or a server, which is not specifically limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0029] Specifically, the energy exchange controller collects various key temperature parameters. The inlet and outlet temperatures of the battery pack are used to monitor the cooling effect of the battery. The current battery heat dissipation status can be known by calculating the inlet and outlet temperature difference; the inlet and outlet temperatures of the warm air system reflect the working status of the cabin heating system; the evaporator temperature is an important indicator of the cooling effect of the air conditioning system; and the ambient temperature is used as a reference for the entire system. At the same time, the control method also needs to receive the user-set temperature issued by the air conditioning controller, which represents the passenger's expected value for the cabin temperature, and the target temperature requirement issued by the battery management system. This temperature is the temperature range to ensure the safe operation of the battery. In the temperature priority determination process, battery temperature control has a higher priority because the battery temperature is directly related to the safety performance of the vehicle. Based on the collected temperature data and system working requirements, the energy exchange controller accurately controls the temperature difference through the PID control algorithm. Specifically, when the system is in battery cooling mode, the difference between the battery target temperature and the actual temperature is used as the input of the PID control; when the system is in cabin air conditioning mode, the difference between the target evaporation temperature and the actual evaporation temperature is used as the input. The PID controller achieves precise regulation of the compressor speed through the synergy of proportional, integral and differential terms. In this process, the minimum operating time parameter of the compressor also needs to be considered, which is usually set to no less than 3 minutes. This parameter is set to ensure the lubrication effect and service life of the compressor.

[0030] The control of the electronic expansion valve is a key link in the entire system. The controller calculates the reference opening value of the valve according to the working status of the compressor and the system superheat data. The system superheat is the difference between the actual temperature of the refrigerant when it leaves the evaporator and the saturation temperature at that pressure, which is usually controlled within the range of 5-15K. The high and low pressure sensor data is used to compensate the valve opening in real time. When the high pressure of the system is too high or the low pressure is too low, the controller will adjust the opening of the electronic expansion valve accordingly to ensure the safe operation of the system. The control of the water system is equally important. The controller monitors whether there is a lack of liquid in the water system through the liquid level sensor, and judges whether the water pump is operating normally through the working status signal of the water pump. Combined with the working status of the system and the operating parameters of the compressor, the controller generates the optimal speed value of the water pump and calculates the power control command of the PTC (positive temperature coefficient heater). These control commands are sent to the vehicle controller through the CAN bus to achieve coordinated control with the vehicle system.

[0031] In order to ensure the reliable operation of the compressor, the controller also implements the oil return control function. By monitoring the operating current value of the compressor, combined with parameters such as the compressor's operating time and valve opening, it is determined whether the system needs to perform an oil return operation. When it is determined that oil return is required, the controller will appropriately increase the compressor speed and adjust the electronic expansion valve opening to promote the return of lubricating oil to the compressor. Finally, the controller also has sensor fault diagnosis and processing functions. When a sensor failure is detected, the parameters will be estimated through the data of other normal sensors to ensure that the system can maintain basic functions. At the same time, the controller will make corresponding adjustments to various control instructions, and upload the fault information to the vehicle system through the CAN bus to remind the driver to perform maintenance in time.

[0032] For example: During the operation of an electric bus, when the ambient temperature is 35°C, the target temperature sent by the battery management system is 25°C, while the actual battery temperature is 30°C. At this time, the controller inputs the battery temperature deviation of 5°C into the PID controller. According to the PID parameter settings (proportional coefficient 100, integral time 60s, differential time 15s), the initial speed of the compressor is calculated to be 3000rpm. At the same time, the system detects that the overheat is 18K, which is higher than the target range (5-15K). The controller increases the opening of the electronic expansion valve from the initial 50% to 65%. In addition, the working current of the water pump is 4.5A. Within the rated range (3-6A), the controller keeps the water pump speed unchanged. After about 10 minutes of operation, the battery temperature dropped to 26°C, and the system overheat was stabilized at 8K, achieving precise temperature control.

[0033] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0034] (1) Performing differential calculation on the inlet and outlet temperatures of the battery pack through the data acquisition unit to obtain characteristic data of battery temperature changes;

[0035] (2) Based on the battery temperature change characteristic data, the temperature gradient of the water inlet and outlet of the heating system is analyzed to generate the temperature status data of the heating system;

[0036] (3) Comparing the evaporator temperature with the preset evaporation temperature threshold, and combining it with the ambient temperature data, outputting the evaporator working status judgment result;

[0037] (4) Calculate the temperature difference between the user set temperature sent by the air conditioning controller and the current ambient temperature to obtain the cabin temperature demand characteristic value;

[0038] (5) Compare the difference between the target temperature requirement issued by the battery management system and the battery temperature change characteristic data to generate a battery cooling requirement characteristic value;

[0039] (6) Prioritize the cabin temperature requirement characteristic value and the battery cooling requirement characteristic value through a priority sorting algorithm, and output temperature requirement priority data;

[0040] (7) Combining the temperature demand priority data and the evaporator working state judgment result, a threshold judgment method is used to screen the working mode to obtain the initial working mode data;

[0041] (8) Using a state matrix algorithm to comprehensively process the battery temperature change characteristic data, the heating system temperature state data, and the initial working mode data to generate a system working state characteristic value;

[0042] (9) Based on the system working state characteristic value, the initial working mode data is corrected and calculated through the decision tree algorithm, and the system working mode signal is output;

[0043] (10) The system working state characteristic value and the system working mode signal are combined and packaged, and sent to the compressor control unit through the CAN bus.

[0044] Specifically, the temperatures of the water inlet and outlet of the battery pack are processed by the data acquisition unit. The data acquisition unit collects temperature data from the water inlet and outlet of the battery pack and calculates the temperature difference between the two, which reflects the heat dissipation of the battery pack. When the outlet temperature is higher than the inlet temperature, it means that the battery is in a heating state and needs to be cooled; otherwise, it means that the battery is in a cooling state. Based on the obtained battery temperature change characteristic data, the controller continues to analyze the water inlet and outlet temperatures of the warm air system. By comparing the temperature data at different time points, the temperature change rate of the warm air system is calculated. This change rate reflects the actual heating or cooling capacity of the warm air system, which is of great guiding significance for subsequent system control strategies.

[0045] Evaporator temperature control is a key link in the entire system. The controller compares the real-time collected evaporator temperature with the pre-set temperature threshold. This threshold is not fixed, but will be dynamically adjusted according to the ambient temperature. For example, in high temperature environments in summer, the evaporator temperature is allowed to fluctuate within a relatively high range; in mild or cold environments, the control range of the evaporator temperature will be reduced accordingly to ensure the cooling effect. The cabin temperature control demand is determined by comparing the user-set temperature with the current ambient temperature. This temperature difference directly reflects the actual cooling or heating demand of the cabin. For example, when the ambient temperature is much higher than the user-set temperature, the system needs to provide a larger cooling capacity; otherwise, it needs to provide heating.

[0046] The battery cooling requirement is determined by analyzing the difference between the target temperature issued by the battery management system and the actual temperature of the current battery. The larger the difference, the more urgent the battery cooling requirement. The controller will adjust the system's working strategy based on this difference. After obtaining the cabin temperature requirement and battery cooling requirement, the controller analyzes them through a priority sorting algorithm. The algorithm assigns different weights to the two requirements, and usually battery cooling has a higher weight because battery temperature is directly related to vehicle safety. The system's working priority is determined by calculating the weighted score.

[0047] Combining the temperature demand priority data and the evaporator working status, the controller uses a threshold judgment method to select the appropriate working mode. When the temperature deviation exceeds a certain threshold, the system will switch to the corresponding working mode, such as single battery cooling mode or mixed cooling mode. The state matrix algorithm establishes a multi-dimensional state space to comprehensively analyze various temperature data and working mode data. This analysis method can comprehensively consider the working status of each part of the system and provide a basis for subsequent control decisions.

[0048] The decision tree algorithm modifies the initially selected working mode through a series of conditional judgments. Factors considered include the size of the temperature difference, system load status, environmental conditions, etc., and the optimal working mode is finally determined through layer-by-layer screening. Finally, the controller encapsulates all processing results into data. These data include the system's working status characteristic values ​​and working mode signals, which are sent to the compressor control unit using the standard CAN communication protocol to achieve coordinated control of the entire system.

[0049] For example: During a typical operation, the controller detects that the water inlet temperature of the battery pack is 25°C, the water outlet temperature is 30°C, and the temperature difference is 5°C, indicating that the battery is in a state of high heat generation. At the same time, the temperature of the heating system rises by 1.5°C within 10 seconds, the evaporator temperature is maintained at 4°C, and the ambient temperature is 32°C. The user sets the cabin temperature to 24°C, while the battery management system requires the battery temperature to be maintained below 25°C. The controller determines through a priority sorting algorithm that the battery cooling demand is more urgent, so it chooses to enter the battery-priority hybrid cooling mode and sends corresponding control instructions to the compressor control unit through the CAN bus. This control strategy successfully reduces the battery temperature to a safe range while maintaining moderate cooling of the cabin, achieving optimal operation of the system.

[0050] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0051] (1) extracting the actual temperature data of the battery and the actual temperature data of the evaporator from the characteristic value of the system working state, performing difference calculation between the target temperature of the battery and the actual temperature data of the battery through the temperature difference operator to obtain the battery temperature error value, and performing difference calculation between the target evaporation temperature and the actual temperature data of the evaporator to obtain the evaporation temperature error value;

[0052] (2) selecting a battery temperature error value or an evaporation temperature error value according to a system operating mode signal, performing temperature deviation compensation calculation through a PID control algorithm, and generating an initial compressor speed control value;

[0053] (3) Comparing the initial compressor speed control amount with the compressor speed upper limit and lower limit to generate a compressor speed limit value, and calculating the change rate of the compressor speed limit value and historical speed data to output a compressor reference speed value;

[0054] (4) performing time constraint processing on the compressor reference speed value and the compressor minimum operating time parameter to obtain the compressor protection control parameter;

[0055] (5) performing a priority judgment on the compressor reference speed value and the compressor protection control parameter through a comparison operator to generate compressor operation timing data;

[0056] (6) Generate a compressor operation control instruction based on the compressor operation timing data and the compressor reference speed value, and send the compressor operation control instruction to the compressor drive unit through the CAN bus.

[0057] Specifically, the controller extracts the actual battery temperature data and the actual evaporator temperature data from the system operating state characteristic value. These two data reflect the real-time operating state of the battery pack and the air conditioning system respectively. The temperature difference operator calculates the battery temperature error value by comparing the battery target temperature with the actual temperature, and calculates the difference between the target evaporation temperature and the actual evaporation temperature to obtain the evaporation temperature error value.

[0058] In the temperature deviation compensation calculation link, the following mathematical model is used:

[0059]

[0060] Where: R(t) is the compensated output value, λ1 is the proportional adjustment coefficient, λ2 is the integral time constant, λ3 is the differential time constant, E(t) is the temperature error input value, τ is the integral time variable, γ is the nonlinear compensation factor, and η is the exponential adjustment coefficient.

[0061] Based on this model, the controller selects the corresponding temperature error value according to the system working mode signal to enter the PID control algorithm for processing. The PID control algorithm is calculated by the above formula, in which the proportional term is used to quickly respond to temperature changes, the integral term eliminates steady-state errors, the differential term provides advanced control, and the nonlinear term enhances the algorithm's ability to correct large temperature deviations. After calculation, the initial compressor speed control amount is output. The controller then limits the initial compressor speed control amount, compares it with the preset speed upper limit (usually 6000rpm) and lower limit (usually 1800rpm), and generates the compressor limit speed value. This limiting process ensures that the compressor operates within a safe speed range. At the same time, the controller calculates the rate of change between the limit speed value and the historical speed data to avoid excessive speed changes, thereby outputting the compressor reference speed value.

[0062] Next, the compressor reference speed value and the compressor minimum operating time parameter are subjected to time constraint processing. The minimum operating time parameter is usually set to 180 seconds, which is to ensure that the compressor is fully lubricated and avoid frequent start and stop. Through this process, the controller obtains the compressor protection control parameters.

[0063] The comparison operator then makes a priority judgment on the compressor reference speed value and the protection control parameter. During the judgment process, the protection control parameter has a higher priority, and protection control is executed first when a conflict occurs. Through this judgment process, the controller generates compressor operation sequence data containing information such as startup sequence and operation time.

[0064] Finally, the controller generates a complete compressor operation control instruction based on the compressor operation timing data and the compressor reference speed value. This instruction contains information such as speed setting value, operation status, protection parameters, etc., and is packaged in the standard CAN communication protocol format and sent to the compressor drive unit.

[0065] For example, during the operation of an electric bus air conditioning system, the controller detects that the actual battery temperature is 32°C, while the target temperature is 25°C, and the calculated battery temperature error is 7°C; at the same time, the actual evaporator temperature is 8°C, the target temperature is 5°C, and the evaporation temperature error is 3°C. Since the battery temperature deviation is large and it is in the battery cooling priority mode, the controller selects the battery temperature error value to input into the PID controller. According to the above temperature deviation compensation formula, set λ1=100, λ2=50, λ3=25, γ=10, η=5, and calculate the initial compressor speed control amount to be 4500rpm. After limiting processing (within the range of 1800-6000rpm) and rate of change limitation (maximum change of 200rpm per second), the compressor reference speed value is finally determined to be 4200rpm. Combined with the minimum operating time parameter (180 seconds), the operating sequence is generated, and the complete control instruction is finally sent to the compressor drive unit through the CAN bus, realizing efficient control of the battery temperature.

[0066] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0067] (1) performing interpolation calculation on the reference speed value of the compressor and the speed correction curve, and performing analytical calculation on the operating state parameters of the compressor operation control instruction to generate a basic valve opening coefficient;

[0068] (2) obtaining system superheat data through a temperature acquisition unit, performing interval determination on the system superheat data, and generating a superheat correction coefficient;

[0069] (3) Perform weighted fusion calculation on the basic valve opening coefficient and the superheat correction coefficient to output the valve reference opening value;

[0070] (4) Collecting high and low pressure sensor data, performing signal filtering processing through the pressure sensor signal conditioning circuit to obtain the system high pressure value and the system low pressure value, and calculating the pressure ratio of the system high pressure value and the system low pressure value, and outputting the system pressure correction parameter;

[0071] (5) performing linear compensation calculation on the valve reference opening value according to the system pressure correction parameter to generate a compensated valve opening value;

[0072] (6) performing an opening distribution calculation on the compensated valve opening value according to the evaporator load and the battery cooling load through a flow distribution algorithm, and generating an evaporator electronic expansion valve opening control signal and an electronic expansion valve opening control signal respectively;

[0073] (7) performing slope limiting processing on the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal to obtain electronic expansion valve control data with limited opening change rate;

[0074] (8) The electronic expansion valve control data with limited opening rate is converted into valve step control pulses through the valve drive circuit and output to the corresponding electronic expansion valve actuator.

[0075] Specifically, the controller processes the reference speed value of the compressor, searches the pre-calibrated speed correction curve data table, and uses the cubic spline interpolation method to calculate the corresponding correction coefficient. At the same time, the operating time, load status and other parameters contained in the compressor operation control instruction are analyzed, and the correction coefficient is adjusted according to these parameters, and finally the basic valve opening coefficient is calculated. The temperature acquisition unit collects the actual temperature of the refrigerant flowing out of the evaporator outlet and compares it with the corresponding saturation temperature under the pressure to calculate the system superheat data. Generally speaking, the superheat needs to be controlled within the range of 5-15K. According to the interval of the superheat data, the controller generates the corresponding superheat correction coefficient. When the superheat is lower than 5K, the correction coefficient is less than 1, and the opening is reduced to increase the superheat; when the superheat is higher than 15K, the correction coefficient is greater than 1, and the opening is increased to reduce the superheat.

[0076] The basic valve opening coefficient and superheat correction coefficient are weighted to generate the valve reference opening value. When weighted calculation is performed, the weight of the basic opening coefficient is 0.7, and the weight of the superheat correction coefficient is 0.3, which not only ensures the output of basic cooling capacity, but also effectively adjusts the superheat. The collection and processing of high and low pressure sensor data are crucial for the safe operation of the system. The pressure sensor signal conditioning circuit uses a Butterworth low-pass filter to filter the collected pressure signal, and the cut-off frequency is set to 10Hz to eliminate high-frequency interference. After filtering, accurate system high and low pressure values ​​are obtained. The pressure ratio is the system high pressure value divided by the low pressure value. This ratio reflects the compression ratio of the system, which in turn affects the opening control of the electronic expansion valve.

[0077] The system pressure correction parameter is calculated through the pressure ratio. When the pressure ratio is too high (usually greater than 4.5), it indicates that the system pressure difference is too large and the electronic expansion valve opening needs to be appropriately increased; when the pressure ratio is too low (usually less than 2.5), it indicates that the system pressure difference is too small and the electronic expansion valve opening needs to be appropriately reduced. This correction parameter is linearly compensated with the valve reference opening value to obtain the compensated valve opening value. The flow distribution algorithm is an important part of the entire control process. The algorithm distributes the compensated valve opening value according to the ratio of the evaporator load and the battery cooling load. The load ratio is calculated by the temperature demand and the target temperature deviation to determine the opening control signal of each electronic expansion valve.

[0078] In order to prevent the opening of the electronic expansion valve from changing too dramatically, the controller limits the opening change rate. Usually, the opening change rate is limited to no more than 2% of the total stroke per second, which can prevent sudden changes in the system cooling capacity and protect the electronic expansion valve itself. After the slope limit processing, smooth electronic expansion valve control data is obtained. Finally, the control data is converted into valve step control pulses. The electronic expansion valve is usually driven by a stepper motor. The controller generates a corresponding pulse sequence through the valve drive circuit to drive the stepper motor to rotate, thereby achieving precise control of the valve opening.

[0079] For example: During the operation of an electric bus, when the compressor base speed is 3600rpm, the basic valve opening coefficient is calculated to be 0.85 through the interpolation of the speed correction curve. The temperature acquisition unit measures the system superheat to be 12K, which is within the normal range, and the superheat correction coefficient is calculated to be 1.05. After weighted fusion (0.7×0.85+0.3×1.05), the valve base opening value is calculated to be 0.91. After signal conditioning, the high and low pressure sensors obtain the system high pressure value of 2.2MPa, the low pressure value of 0.6MPa, and the pressure ratio of 3.67, from which the pressure correction parameter is calculated to be 1.02. The valve opening value after compensation is 0.93. Since the evaporator load accounts for 60% and the battery cooling load accounts for 40% at this time, the flow distribution algorithm distributes the opening value of 0.93 as follows: the evaporator electronic expansion valve opening is 0.56 (0.93×0.6), and the battery side electronic expansion valve opening is 0.37 (0.93×0.4). Finally, after slope limitation and drive circuit conversion, the corresponding step control pulse is output to achieve precise control of the electronic expansion valve.

[0080] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0081] (1) Compare and calculate the liquid level sensor signal with the liquid level threshold, and perform current sampling and analysis on the water pump working status signal to generate water system fault feature data;

[0082] (2) The temperature data in the system working state characteristic value is calculated over time through an integral operator, and a temperature change trend characteristic value is output;

[0083] (3) Combined with the fault characteristic data of the water system and the characteristic value of the temperature change trend, the safety limit calculation of the compressor reference speed value is performed to obtain the safe operation parameters of the compressor;

[0084] (4) Based on the safe operating parameters of the compressor, the rated speed of the water pump is dynamically adjusted and calculated through the frequency conversion control algorithm to generate the optimized value of the water pump speed;

[0085] (5) Correlation analysis is performed on the valve reference opening value and the temperature change trend characteristic value, the PTC heating power demand is calculated through the power control algorithm, and the PTC power control instruction is output;

[0086] (6) Perform data format conversion on the water pump speed optimization value and the PTC power control command, generate a CAN communication data packet, and send the CAN communication data packet to the vehicle controller according to the communication protocol;

[0087] (7) Verify and calculate the response signal of the vehicle controller through the feedback verification algorithm to generate control instruction execution status data;

[0088] (8) Analyze the deviation between the control instruction execution status data and the actual operating parameters, and make real-time corrections to the pump speed optimization value and PTC power control instruction.

[0089] Specifically, the liquid level sensor monitors the liquid level status of the water system in real time, and determines whether the water system is in a state of lack of liquid by comparing the detected liquid level signal with the preset liquid level threshold (usually 20% of the water tank capacity). At the same time, the controller monitors the working status of the water pump and collects the operating current value of the water pump through the current sampling circuit. The normal working current range is 3-6A. If it exceeds this range, it is determined that the water pump is working abnormally. Based on the analysis results of the liquid level status and the working status of the water pump, the fault characteristic data of the water system containing information such as the fault type and fault level are generated. The integral processing of temperature data is an important means to judge the operating trend of the system. The integral operator continuously samples the temperature data in the characteristic value of the system working status, with a sampling interval of 100ms, and obtains the cumulative value of temperature change within a certain period of time (usually 10 minutes) by cumulative calculation. This cumulative value reflects the trend of temperature change, thereby predicting the operating trend of the system. For example, when the temperature continues to rise, the cumulative value is positive and gradually increases, indicating that the system's heat dissipation capacity is insufficient; when the temperature tends to be stable, the cumulative value is close to zero.

[0090] In order to ensure the safe operation of the system, the controller conducts a comprehensive analysis of the water circuit fault characteristic data and the temperature change trend characteristic value. When a water circuit fault or an abnormal temperature change trend is detected, the compressor reference speed value needs to be limited. The restriction strategy includes: when a minor fault is detected, the compressor speed is limited to less than 80% of the reference speed; when a serious fault is detected, the speed is reduced to the minimum operating speed, and the machine is shut down for protection when necessary. The optimized control of the water pump speed is achieved through the frequency conversion algorithm. The frequency conversion control algorithm dynamically calculates the required flow demand based on the safe operation parameters of the compressor, and then determines the water pump speed. The speed adjustment range is 1000-3000rpm, and the specific adjustment strategy is: when the compressor load is low, the water pump operates in the low speed range; when the compressor load increases, the water pump speed increases accordingly to ensure sufficient cooling water flow.

[0091] PTC power control is calculated based on the valve reference opening value and the temperature change trend characteristic value. When the valve opening is small and the temperature change trend indicates that the cooling capacity is insufficient, the PTC power output is increased; otherwise, the power output is reduced. The PTC power adjustment range is 0-6kW, and a segmented control method is adopted, with each segment increment of 0.5kW. In terms of data communication, the controller needs to convert the water pump speed optimization value and the PTC power control instruction into a standard CAN communication format. The CAN data packet contains: data identifier (used to distinguish different types of control instructions), data length (usually 8 bytes), and specific data content (including control value, status flag, etc.). The data packet is encapsulated and sent according to the standard CAN2.0B protocol.

[0092] The feedback verification algorithm uses a cyclic redundancy check (CRC) method to verify the response signal returned by the vehicle controller. The verification content includes: data packet integrity, data value validity, timing correctness, etc. Through verification calculation, the control instruction execution status data containing information such as execution results and execution time is generated. Finally, the execution effect of the control instruction is evaluated. The control instruction execution status data is compared with the actual operating parameters (including the actual speed of the water pump, the actual power of the PTC, etc.) to calculate the control deviation. When the deviation exceeds the allowable range, the water pump speed optimization value and the PTC power control instruction are corrected to ensure control accuracy.

[0093] For example, during the operation of an electric bus, the liquid level sensor detected that the water tank level dropped to 18%, which was lower than the warning threshold of 20%. At the same time, the working current of the water pump was 5.8A, close to the upper limit of 6A. Based on these two abnormal indicators, the fault characteristic data of the water system is generated and marked as "mild fault". The temperature integral operation shows that the system temperature has accumulated an increase of 3.5℃ in the last 10 minutes, indicating that the heat dissipation capacity has decreased. Based on this, the controller reduces the compressor base speed from 4000rpm to 3200rpm (a decrease of 20%), and increases the water pump speed from the original 2400rpm to 2800rpm to increase the circulating water flow. In terms of PTC power control, since the valve opening has dropped to 45% and the temperature is on the rise, the controller adjusts the PTC power from 3kW to 4kW. These control instructions are sent to the vehicle controller via the CAN bus (using a baud rate of 250kbps), and the response signal is received within 50ms. The CRC check confirmed that the instructions had been executed correctly, and the deviations between the actual operating parameters and the control instructions were within 5%, without the need for correction, thus achieving safe and stable operation of the system.

[0094] In a specific embodiment, the process of executing step S105 may specifically include the following steps:

[0095] (1) performing a product operation on the operation time data in the compressor operation control instruction and the compressor reference speed value to generate the compressor cumulative operation amount data;

[0096] (2) The compressor operating current value is collected in real time through the current sampling circuit, and the current characteristic curve is compared with the compressor reference speed value to output the compressor load characteristic value;

[0097] (3) Based on the accumulated operating volume data of the compressor and the reference valve opening value, a threshold judgment algorithm is used to calculate the oil return time window and generate an oil return trigger signal;

[0098] (4) performing weighted processing on the oil return trigger signal according to the compressor load characteristic value to obtain the oil return demand calculation result;

[0099] (5) When the calculated result of the oil return demand exceeds the threshold, the compressor reference speed value is increased and calculated through the speed compensation algorithm to obtain the compressor oil return speed value;

[0100] (6) Based on the compressor oil return speed value, the valve reference opening value is corrected and calculated, and the electronic expansion valve oil return opening value is output.

[0101] Specifically, during the long-term operation of the compressor, the lubricating oil will be distributed in various components of the system along with the refrigerant circulation. A specific oil return control strategy is required to ensure that the lubricating oil returns to the compressor in time. The controller first multiplies the operating time data (in seconds) in the compressor operation control instruction with the compressor reference speed value to obtain the cumulative operating volume data reflecting the actual workload of the compressor. For example, when the compressor runs continuously for 1800 seconds at a speed of 3000rpm, the cumulative operating volume data is 5.4×106. The current sampling circuit samples the compressor operating current through the Hall sensor with a sampling frequency of 10Hz. The sampled current value is compared with the pre-calibrated compressor current characteristic curve. The current characteristic curve describes the standard operating current value of the compressor at different speeds. Any deviation from this standard value indicates that the compressor load state has changed. By comparing the deviation between the actual current value and the standard value, the compressor load characteristic value is calculated. Under the standard working state, the load characteristic value is 1; when the actual current is higher than the standard value, the load characteristic value is greater than 1, indicating that the compressor load is too heavy; otherwise, it indicates that the load is light.

[0102] The cumulative running volume data of the compressor and the reference opening value of the valve are important bases for judging whether oil return is needed. The threshold judgment algorithm calculates the oil return time window based on these two parameters. When the cumulative running volume exceeds 4×106 and the valve opening is less than 50%, the first-level oil return is triggered; when the cumulative running volume exceeds 8×106, the forced oil return will be triggered regardless of the valve opening. The oil return time window is usually set to 180-300 seconds, during which the system implements a specific oil return control strategy. The compressor load characteristic value plays a regulating role in oil return control. The controller adopts a weighted processing method. When the load characteristic value is large, the weight of the oil return demand is increased; when the load characteristic value is small, the weight is reduced. This weighted processing enables the oil return control to better adapt to the actual working state of the compressor. The specific weighting coefficient changes linearly with the load characteristic value. For every 0.1 increase in the load characteristic value, the weighting coefficient increases by 0.05.

[0103] When the calculated result of the weighted oil return demand exceeds the preset threshold (usually 1.2), the controller starts the oil return control program. The speed compensation algorithm increases the compressor base speed by 20-30% to increase the refrigerant flow rate and promote the return of lubricating oil. However, the increased speed must not exceed the maximum allowable speed of the compressor (usually 6000rpm). At the same time, in order to avoid sudden changes causing shocks to the system, the speed increase adopts a ramp function to gradually reach the target value within 5 seconds. The opening control of the electronic expansion valve also needs to cooperate with the oil return operation. The controller corrects the valve base opening value according to the compressor oil return speed value. The basic principle of correction is: under the premise of ensuring the system superheat, appropriately increase the opening to increase the refrigerant flow rate. Generally, the valve opening is increased by 15-25%, and the system superheat is closely monitored to ensure that it is maintained within the safe range of 5-15K.

[0104] For example, during the operation of an electric bus air conditioning system, the compressor ran continuously at 3500rpm for 2400 seconds, and the cumulative running data was calculated to be 8.4×106, which exceeded the oil return trigger threshold. The current sampling circuit measured the actual working current of the compressor to be 15A, while the standard working current at this speed was 12A, and the load characteristic value was calculated to be 1.25. Due to the high load characteristic value, the weighted coefficient of the oil return demand increased to 1.3, and the calculated oil return demand value reached 1.35, exceeding the preset threshold of 1.2. The controller immediately started the oil return program, increasing the compressor speed from 3500rpm to 4550rpm (an increase of 30%), and at the same time increasing the opening of the electronic expansion valve from the original 60% to 75%. This oil return process lasted for 240 seconds, during which the compressor current gradually dropped to 13A, indicating that the lubrication condition was improved. After the oil return was completed, the system restored the normal operating parameters to ensure the reliable operation of the compressor.

[0105] In a specific embodiment, the process of executing step S106 may specifically include the following steps:

[0106] (1) Perform effective range verification on the temperature sensor signal and pressure sensor signal in the system working state characteristic value, identify abnormal data through the signal mutation detection algorithm, and generate a sensor fault flag;

[0107] (2) Perform time series analysis on the sensor fault flag and sensor historical data to determine the sensor failure type and output sensor failure feature data;

[0108] (3) Select normal sensor signals based on sensor failure characteristic data, perform state estimation on missing data through Kalman filter algorithm, and obtain sensor compensation data;

[0109] (4) Reconstructing the system working state characteristic value using the sensor compensation data to generate a corrected system working state characteristic value;

[0110] (5) Based on the correction system working state characteristic value, the compressor speed correction value, the electronic expansion valve opening correction value, the water pump speed correction value and the PTC power correction value are calculated respectively through the compensation control algorithm;

[0111] (6) performing correction calculation on the compressor operation control command, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control command, and outputting the corrected control command;

[0112] (7) The sensor failure characteristic data and the corrected control instructions are packaged into a fault information data packet and uploaded to the vehicle system via the CAN bus.

[0113] Specifically, the controller first performs an effective range check on the signals of the temperature sensor and the pressure sensor. The effective range of the temperature sensor is set to -40℃ to 120℃, and the effective range of the pressure sensor is 0-4.5MPa. When the sensor signal exceeds these ranges, it is marked as abnormal data. At the same time, the signal mutation detection algorithm identifies abnormal data by calculating the change rate of adjacent sampling points. When the change rate of the temperature sensor exceeds 5℃ / s or the change rate of the pressure sensor exceeds 0.5MPa / s, it is determined to be a signal mutation. Based on these judgment results, a sensor fault flag containing information such as the fault location and fault type is generated. Time series analysis of sensor historical data is crucial for fault diagnosis. The controller stores the sensor data within the last 10 minutes in the cache area and determines the fault type by analyzing the data change trend. For example, when the output value of a sensor continues to remain at the upper or lower limit of the range, it indicates that the sensor has a range saturation fault; when the output value shows random jumps, it is determined to be a signal interference fault; when the output is zero or a fixed value, it is determined to be a sensor open circuit or short circuit fault. These fault type information are packaged into sensor failure feature data.

[0114] For failed sensor data, the controller uses the Kalman filter algorithm for state estimation. The algorithm predicts the theoretical value of the failed sensor based on other normally working sensor data and the system dynamic characteristics. For example, when the evaporator outlet temperature sensor fails, the temperature value of the point can be estimated based on the system pressure and the data of other temperature sensors. The Kalman filter algorithm continuously optimizes the estimation results through two steps of prediction and correction to obtain reliable sensor compensation data. During the reconstruction of the system working state characteristic value, the sensor compensation data replaces the original data of the failed sensor. During reconstruction, the correlation between parameters needs to be considered to ensure that the reconstructed data conforms to the laws of thermodynamics. For example, the temperature and pressure data of the evaporator must meet the requirements of the saturation characteristic curve of the refrigerant. After the reconstruction is completed, the corrected system working state characteristic value is obtained.

[0115] The compensation control algorithm calculates the correction amount of each actuator according to the corrected system state characteristic value. The compressor speed correction mainly considers the system cooling capacity demand, and the correction range is usually within ±20%; the electronic expansion valve opening correction is based on the system superheat control demand, and the correction range is within ±15%; the water pump speed correction is determined according to the flow demand, and the correction range is within ±30%; the PTC power correction is based on the heating demand, and the correction range is within ±25%. The controller applies these correction amounts to the original control instructions and generates new execution instructions. The correction process adopts a progressive adjustment strategy to avoid the impact of sudden changes in the control amount on the system. The corrected control instructions are sent to the corresponding actuators through their respective output channels.

[0116] Finally, the controller packages the sensor failure information and the corrected control strategy information into a fault diagnosis data packet. The data packet uses the standard CAN protocol format and contains information such as fault code, fault level, and correction strategy. It is sent to the vehicle controller through the CAN bus for fault tracing and maintenance.

[0117] For example, during the operation of an electric bus, the output value of the evaporator outlet temperature sensor suddenly jumped from the normal 8°C to -45°C, exceeding the effective range of the sensor (-40°C to 120°C). At the same time, the rate of change of this data point reached 26°C / s, far exceeding the normal threshold of 5°C / s. The controller immediately marked this sensor as a fault state. Analysis of the historical data of the last 10 minutes found that the sensor worked normally before the fault, and the output value changed steadily between 6-10°C. Combined with the mutation characteristics, it was determined to be a sensor short circuit fault. The controller then started the Kalman filter algorithm and estimated that the evaporator outlet temperature should be 7.5°C based on the normal working pressure sensor (showing an evaporation pressure of 0.6MPa) and other temperature sensor data. Use this compensation data to reconstruct the system working state and modify the control parameters accordingly: the compressor speed is adjusted from the original 3600rpm to 3100rpm (a decrease of 14%), the electronic expansion valve opening is adjusted from 65% to 58% (a decrease of 11%), and the water pump speed and PTC power remain unchanged. Finally, the controller generates a CAN data packet containing the fault code "P0532" (temperature sensor short circuit) and uploads it to the vehicle controller, achieving reliable degraded operation of the system.

[0118] The step division of the above methods is only for the purpose of clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this patent.

[0119] Second embodiment

[0120] The above describes the vehicle thermal management unit control method of the cabin air conditioning system in the embodiment of the present application. The following describes the vehicle thermal management unit control system of the cabin air conditioning system in the embodiment of the present application. Figure 2 , an embodiment of a vehicle thermal management unit control system of a cabin air conditioning system in an embodiment of the present application includes:

[0121] The acquisition module is used to combine the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and perform determination and calculation according to the preset temperature priority to obtain the system working state characteristic value and the system working mode signal;

[0122] a calculation module, for calculating the difference between the target battery temperature and the actual battery temperature or the difference between the target evaporation temperature and the actual evaporation temperature based on the system working mode signal and the system working state characteristic value by using a PID control algorithm, and generating a compressor reference speed value and a compressor operation control instruction in combination with a compressor minimum operation time parameter;

[0123] A compensation module, used to calculate a valve reference opening value through a preset opening algorithm according to the compressor reference speed value, the compressor operation control instruction and the system superheat data, and to perform compensation operation on the valve reference opening value according to the high and low pressure sensor data, and output an evaporator electronic expansion valve opening control signal and an electronic expansion valve opening control signal;

[0124] A control module is used to obtain the working state signals of the liquid level sensor and the water pump, perform safety determination calculations in combination with the system working state characteristic value, the compressor reference speed value and the valve reference opening value, generate a water pump speed optimization value and a PTC power control instruction, and send the water pump speed optimization value and the PTC power control instruction to the vehicle controller via the CAN bus;

[0125] an acquisition module, configured to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, calculate the oil return demand according to a preset determination threshold, and output the compressor oil return speed value and the electronic expansion valve oil return opening value when the oil return demand calculation result exceeds the threshold;

[0126] A correction module is used to judge the validity of each sensor signal in the system working state characteristic value. When a sensor failure is detected, normal sensor data is used to perform parameter interpolation calculation to generate a corrected system working state characteristic value, and based on the corrected system working state characteristic value, the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction are adjusted, and fault information is recorded and uploaded to the vehicle system through the CAN bus.

[0127] Through the cooperation of the above components, through the comprehensive analysis of the inlet and outlet temperature of the battery pack, the inlet and outlet temperature of the heating system, the evaporator temperature and the ambient temperature data, the accurate judgment of the system working state and the mode switching control are realized, and the stability and reliability of the system operation are improved. The PID control algorithm is used to accurately control the temperature difference, and combined with the setting of the minimum operating time parameter of the compressor, the frequent start and stop of the compressor is effectively avoided, and the service life of the compressor is extended. The electronic expansion valve is accurately controlled by the preset opening algorithm and pressure compensation operation, ensuring that the system can maintain an appropriate superheat under different working conditions, thereby improving the refrigeration efficiency of the system. At the same time, based on the real-time monitoring of the working status of the liquid level sensor and the water pump, combined with the safety judgment operation, the reliable operation of the water system is realized, and the dry burning and other faults of the water system are effectively prevented. In addition, the method also includes a complete oil return control strategy. Through the continuous monitoring and analysis of the operating status of the compressor, the oil return control is carried out in time to ensure the lubrication effect of the compressor. In terms of sensor fault handling, the parameter interpolation calculation and system state characteristic value correction are adopted to enable the system to maintain basic functions in the case of sensor failure, thereby improving the fault tolerance of the system. The entire control process communicates with the vehicle system through the CAN bus, realizing real-time transmission of control information and timely reporting of fault information, which facilitates system maintenance and fault diagnosis. This control method realizes efficient integration of battery temperature control and cabin air conditioning through multiple protection strategies and precise control algorithms, improving energy efficiency while ensuring system reliability.

[0128] It is not difficult to find that this embodiment is a system embodiment corresponding to the first embodiment, and this embodiment can be implemented in conjunction with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and in order to reduce repetition, they are not repeated here. Accordingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

[0129] It is worth mentioning that all modules involved in this embodiment are logic modules. In practical applications, a logic unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed by this application, but this does not mean that there are no other units in this embodiment.

[0130] In addition, some embodiments of the present application also provide an electronic device. The electronic device may be a digital computer in various forms, such as a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, etc. The electronic device may also be a mobile device in various forms, such as a personal digital processing, a cellular phone, a smart phone, a wearable device, and other similar computing devices.

[0131] Figure 3 An exemplary structural diagram of the electronic device is disclosed. Figure 3 As shown, the electronic device includes: one or more processors 1101, memory 1102, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Among them, the components shown in this article, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0132] The electronic device may further include: an input device 1103 and an output device 1104. The processor 1101, the memory 1102, the input device 1103 and the output device 1104 may be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0133] The input device 1103 can receive input digital or character information, and generate key signal input related to the user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 1104 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display and a plasma display. In some embodiments, the display device may be a touch screen.

[0134] To provide interaction with a user, the electronic device may be a computer. The computer has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0135] In the embodiments of the present application, a computer program / instruction is stored on a computer-readable medium, and when the computer program / instruction is executed by a processor, the steps of the method provided by any one or more of the above embodiments are implemented. The computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0136] The memory 1102 can be used as a non-transient computer-readable storage medium, which can be used to store non-transient software programs, non-transient computer executable programs and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided by any one or more embodiments in the embodiments of the present application.

[0137] The memory 1102 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 1102 may optionally include a memory remotely arranged relative to the processor 1101, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0138] It should be noted that the computer-readable medium described in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0139] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0140] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet).

[0141] In the above-described embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. For example, it can be implemented by using an application specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In certain embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program of the present application (including relevant data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and similar devices. In addition, some steps or functions of the present application can be implemented by hardware, for example, as a circuit that cooperates with a processor to perform each step or function.

[0142] The computer program product provided in the embodiment of the present application includes one or more computer programs / instructions, and when the computer program / instructions are executed by the processor, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive so lid state di sk (SSD)), etc.

[0143] The flow chart or block diagram in the accompanying drawings shows the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] The scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim may also be implemented by one unit or device through software or hardware. The words "first", "second", etc. are only used to distinguish the description, and do not indicate any particular order, nor can they be understood as indicating or implying relative importance.

[0145] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily mention changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-restrictive.

Claims

1. A method for controlling a thermal management unit of a cabin air conditioning system, characterized in that: The method comprises: The battery pack water inlet and outlet temperatures, the heating system water inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller are combined with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and the system working state characteristic value and system working mode signal are obtained according to the preset temperature priority. Based on the system working mode signal and the system working state characteristic value, a PID control algorithm is used to calculate the difference between the battery target temperature and the actual temperature or the difference between the target evaporation temperature and the actual evaporation temperature, and a compressor reference speed value and a compressor operation control instruction are generated in combination with a compressor minimum operation time parameter; According to the compressor reference speed value, the compressor operation control instruction and the system superheat data, the valve reference opening value is calculated by a preset opening algorithm, and the valve reference opening value is compensated according to the high and low pressure sensor data, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are output; Acquire the working state signals of the liquid level sensor and the water pump, perform safety determination calculations in combination with the system working state characteristic value, the compressor reference speed value and the valve reference opening value, generate the water pump speed optimization value and the PTC power control instruction, and send the water pump speed optimization value and the PTC power control instruction to the vehicle controller through the CAN bus; Based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, the compressor operation current value is obtained, and the oil return demand is calculated according to a preset judgment threshold value, and when the oil return demand calculation result exceeds the threshold value, the compressor oil return speed value and the electronic expansion valve oil return opening value are output; The validity of each sensor signal in the system working state characteristic value is judged. When a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system working state characteristic value, and the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction are adjusted based on the corrected system working state characteristic value. At the same time, fault information is recorded and uploaded to the vehicle system through the CAN bus.

2. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 1, characterized in that: The battery pack water inlet and outlet temperatures, the heating system water inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller are combined with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and the system working state characteristic value and the system working mode signal are obtained according to the preset temperature priority, including: Performing a difference calculation on the inlet and outlet temperatures of the battery pack through a data acquisition unit to obtain battery temperature change characteristic data; Based on the battery temperature variation characteristic data, a temperature gradient analysis is performed on the water inlet and outlet temperatures of the heating system to generate temperature status data of the heating system; Comparing the evaporator temperature with a preset evaporation temperature threshold, and combining the ambient temperature data, outputting a result of judging the working state of the evaporator; Calculating the temperature difference between the user set temperature sent by the air conditioning controller and the current ambient temperature to obtain a cabin temperature demand characteristic value; Compare the target temperature requirement issued by the battery management system with the battery temperature change characteristic data to generate a battery cooling requirement characteristic value; Prioritize the cabin temperature requirement characteristic value and the battery cooling requirement characteristic value by using a priority sorting algorithm, and output temperature requirement priority data; Combining the temperature demand priority data and the evaporator working state judgment result, a threshold judgment method is used to screen the working mode to obtain initial working mode data; Using a state matrix algorithm to comprehensively process the battery temperature change characteristic data, the heating system temperature state data and the initial working mode data to generate the system working state characteristic value; Based on the system working state characteristic value, the initial working mode data is corrected and calculated by a decision tree algorithm, and the system working mode signal is output; The system working state characteristic value and the system working mode signal are combined and packaged, and sent to the compressor control unit through the CAN bus.

3. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 1, characterized in that: Based on the system working mode signal and the system working state characteristic value, the difference between the battery target temperature and the actual temperature or the difference between the target evaporation temperature and the actual evaporation temperature is processed by using a PID control algorithm, and combined with the compressor minimum operating time parameter, a compressor reference speed value and a compressor operation control instruction are generated, including: Extracting the actual temperature data of the battery and the actual temperature data of the evaporator from the characteristic value of the system working state, performing a difference calculation between the target battery temperature and the actual battery temperature data through a temperature difference operator to obtain a battery temperature error value, and performing a difference calculation between the target evaporation temperature and the actual evaporator temperature data to obtain an evaporation temperature error value; Selecting the battery temperature error value or the evaporation temperature error value according to the system working mode signal, performing temperature deviation compensation calculation through a PID control algorithm, and generating an initial compressor speed control amount; Comparing the initial compressor speed control amount with the compressor speed upper limit and lower limit to generate a compressor speed limit value, and calculating the change rate of the compressor speed limit value and historical speed data to output the compressor reference speed value; Performing time constraint processing on the compressor reference speed value and the compressor minimum operating time parameter to obtain a compressor protection control parameter; A comparison operator is used to determine the priority of the compressor reference speed value and the compressor protection control parameter to generate compressor operation timing data; The compressor operation control instruction is generated according to the compressor operation timing data and the compressor reference speed value, and the compressor operation control instruction is sent to the compressor drive unit through the CAN bus.

4. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 1, characterized in that: The valve reference opening value is calculated by a preset opening algorithm according to the compressor reference speed value, the compressor operation control instruction and the system superheat data, and the valve reference opening value is compensated according to the high and low pressure sensor data, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are output, including: An interpolation operation is performed on the reference speed value of the compressor and the speed correction curve, and an analytical operation is performed on the operating state parameters of the compressor operating control instruction to generate a basic valve opening coefficient; Acquiring the system superheat data through a temperature acquisition unit, performing interval determination on the system superheat data, and generating a superheat correction coefficient; Performing weighted fusion calculation on the basic valve opening coefficient and the superheat correction coefficient, and outputting the valve reference opening value; Collect the data of the high and low pressure sensors, perform signal filtering processing through the pressure sensor signal conditioning circuit, obtain the system high pressure value and the system low pressure value, calculate the pressure ratio of the system high pressure value and the system low pressure value, and output the system pressure correction parameter; Performing a linear compensation operation on the valve reference opening value according to the system pressure correction parameter to generate a compensated valve opening value; The compensated valve opening value is calculated according to the evaporator load and the battery cooling load by a flow distribution algorithm to generate the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal respectively; Performing slope limiting processing on the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal to obtain electronic expansion valve control data with limited opening change rate; The electronic expansion valve control data with limited opening change rate is converted into valve step control pulses through a valve drive circuit and output to a corresponding electronic expansion valve actuator.

5. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 1, characterized in that: The method of acquiring the working state signal of the liquid level sensor and the water pump, combining the system working state characteristic value, the compressor reference speed value and the valve reference opening value, performing safety determination operation, generating a water pump speed optimization value and a PTC power control instruction, and sending the water pump speed optimization value and the PTC power control instruction to the vehicle controller through the CAN bus includes: Compare and calculate the liquid level sensor signal with the liquid level threshold, and perform current sampling and analysis on the water pump working status signal to generate water system fault feature data; The temperature data in the system working state characteristic value is calculated by time accumulation through an integral operator, and a temperature change trend characteristic value is output; Combining the water system fault characteristic data and the temperature change trend characteristic value, a safety limit calculation is performed on the compressor reference speed value to obtain a safe operation parameter of the compressor; Based on the safe operation parameters of the compressor, the rated speed of the water pump is dynamically adjusted and calculated by a variable frequency control algorithm to generate an optimized value of the water pump speed; Perform correlation analysis on the valve reference opening value and the temperature change trend characteristic value, calculate the PTC heating power demand through a power control algorithm, and output the PTC power control instruction; Performing data format conversion on the water pump speed optimization value and the PTC power control instruction to generate a CAN communication data packet, and sending the CAN communication data packet to the vehicle controller according to the communication protocol; The response signal of the vehicle controller is verified and calculated through the feedback verification algorithm to generate the control instruction execution status data; The control instruction execution state data and the actual operating parameters are analyzed for deviations, and the water pump speed optimization value and the PTC power control instruction are corrected in real time.

6. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 1, characterized in that: The method of obtaining the compressor operating current value based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, performing oil return demand calculation according to a preset determination threshold, and outputting the compressor oil return speed value and the electronic expansion valve oil return opening value when the oil return demand calculation result exceeds the threshold, includes: Performing a product operation on the operation time data in the compressor operation control instruction and the compressor reference speed value to generate compressor cumulative operation amount data; The operating current value of the compressor is collected in real time by a current sampling circuit, and a current characteristic curve is compared with the reference speed value of the compressor to output a compressor load characteristic value; Based on the accumulated running volume data of the compressor and the reference valve opening value, a threshold judgment algorithm is used to calculate the oil return time window and generate an oil return trigger signal; Performing weighted processing on the oil return trigger signal according to the compressor load characteristic value to obtain an oil return demand calculation result; When the oil return demand calculation result exceeds a threshold value, the compressor reference speed value is increased and calculated by a speed compensation algorithm to obtain the compressor oil return speed value; Based on the compressor oil return speed value, the valve reference opening value is corrected and calculated, and the electronic expansion valve oil return opening value is output.

7. The vehicle thermal management unit control method of the cabin air conditioning system according to claim 6, characterized in that: The validity of each sensor signal in the system working state characteristic value is judged, and when a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system working state characteristic value, and the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction are adjusted based on the corrected system working state characteristic value, and the fault information is recorded and uploaded to the vehicle system through the CAN bus, including: Performing effective range verification on the temperature sensor signal and the pressure sensor signal in the system working state characteristic value, identifying abnormal data through a signal mutation detection algorithm, and generating a sensor fault flag; Perform time series analysis on the sensor fault flag and sensor historical data to determine the sensor failure type and output sensor failure feature data; Selecting a normal sensor signal according to the sensor failure characteristic data, performing state estimation on the missing data through a Kalman filter algorithm, and obtaining sensor compensation data; Reconstructing the system working state characteristic value by using the sensor compensation data to generate the corrected system working state characteristic value; Based on the working state characteristic value of the correction system, the compressor speed correction amount, the electronic expansion valve opening correction amount, the water pump speed correction amount and the PTC power correction amount are calculated respectively through the compensation control algorithm; Perform correction calculation on the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction, and output the corrected control instruction; The sensor failure characteristic data and the corrected control instructions are packaged into a fault information data packet and uploaded to the vehicle system via the CAN bus.

8. A vehicle thermal management unit control system for a cabin air conditioning system, used to implement the vehicle thermal management unit control method for a cabin air conditioning system according to any one of claims 1 to 7, characterized in that: The vehicle thermal management unit control system of the cabin air conditioning system includes: The acquisition module is used to combine the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature and the ambient temperature data collected by the energy exchange controller with the user set temperature issued by the air conditioning controller and the target temperature requirement issued by the battery management system, and perform determination and calculation according to the preset temperature priority to obtain the system working state characteristic value and the system working mode signal; a calculation module, for calculating the difference between the target battery temperature and the actual battery temperature or the difference between the target evaporation temperature and the actual evaporation temperature based on the system working mode signal and the system working state characteristic value by using a PID control algorithm, and generating a compressor reference speed value and a compressor operation control instruction in combination with a compressor minimum operation time parameter; A compensation module, used to calculate a valve reference opening value through a preset opening algorithm according to the compressor reference speed value, the compressor operation control instruction and the system superheat data, and to perform compensation operation on the valve reference opening value according to the high and low pressure sensor data, and output an evaporator electronic expansion valve opening control signal and an electronic expansion valve opening control signal; A control module is used to obtain the working state signals of the liquid level sensor and the water pump, perform safety determination calculations in combination with the system working state characteristic value, the compressor reference speed value and the valve reference opening value, generate a water pump speed optimization value and a PTC power control instruction, and send the water pump speed optimization value and the PTC power control instruction to the vehicle controller via the CAN bus; an acquisition module, configured to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control instruction and the valve reference opening value, calculate the oil return demand according to a preset determination threshold, and output the compressor oil return speed value and the electronic expansion valve oil return opening value when the oil return demand calculation result exceeds the threshold; A correction module is used to judge the validity of each sensor signal in the system working state characteristic value. When a sensor failure is detected, normal sensor data is used to perform parameter interpolation calculation to generate a corrected system working state characteristic value, and based on the corrected system working state characteristic value, the compressor operation control instruction, the evaporator electronic expansion valve opening control signal, the electronic expansion valve opening control signal, the water pump speed optimization value and the PTC power control instruction are adjusted, and fault information is recorded and uploaded to the vehicle system through the CAN bus.

9. An electronic device, characterized in that: The electronic device comprises: one or more processors; and A memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

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