Control methods, systems and equipment for automotive thermal management units in cabin air conditioning systems

Abstract

This application relates to the field of thermal management control technology, and discloses a control method, system, and equipment for a vehicle thermal management unit in a cabin air conditioning system. The method includes: collecting temperature data from the battery pack, heating system, evaporator, and ambient temperature; combining this with the user-set temperature and the target battery temperature to perform temperature priority calculations, obtaining operating state characteristic values ​​and mode signals; calculating the temperature difference using a PID algorithm based on these signals and characteristic values, and generating compressor control commands; calculating valve opening based on compressor parameters and superheat data, and outputting electronic expansion valve control signals; acquiring liquid level and water pump status for safety assessment, and generating water pump and PTC control commands; monitoring compressor operating parameters and executing oil return control; and judging the effectiveness of sensors, correcting parameters and reporting faults when they fail. This application achieves reasonable distribution and precise control of cooling capacity in a two-in-one system where battery cooling and cabin air conditioning share a single compressor.

Description

Technical Field

[0001] This application relates to the field of thermal management control technology, and in particular to a method, system and equipment for controlling automotive thermal management units in a cabin air conditioning system. Background Technology

[0002] The cabin air conditioning and battery thermal management system are key components for ensuring safe vehicle operation and passenger comfort in electric vehicles. Currently, mainstream electric vehicle thermal management solutions typically employ a separate design for the battery cooling system and the cabin air conditioning system, using independent cooling circuits to provide cooling for the battery pack and cabin respectively. While this design has simple control logic, it requires two separate compressors, condensers, and other core components, increasing system cost and weight, and reducing overall vehicle space utilization. In recent years, some vehicle manufacturers have begun to explore integrated systems that combine battery cooling and cabin air conditioning functions into a single system. Through system architecture integration, battery cooling and cabin air conditioning share a single compressor, aiming to reduce costs and improve system efficiency.

[0003] However, existing dual-function thermal management systems still face some technical challenges in practical applications: Because the system needs to simultaneously meet the temperature requirements of both the cabin and the battery, the control of the refrigerant system becomes significantly more difficult. In particular, existing control strategies often struggle to achieve precise control in areas such as system oil return, low-temperature refrigerant migration, cooling capacity distribution calibration, and valve control. For example, when cooling the battery in low-temperature environments, refrigerant tends to accumulate in the evaporator, leading to a decrease in system cooling performance; when cabin air conditioning and battery cooling operate simultaneously, improper cooling capacity distribution may affect passenger comfort or battery temperature control; furthermore, improper system oil return control can lead to poor compressor lubrication, affecting system reliability and lifespan. Summary of the Invention

[0004] One objective of this 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 where battery cooling and cabin air conditioning share a single compressor, while solving key technical problems such as system oil return and low-temperature refrigerant migration, and ensuring that the system can operate stably and reliably under various operating conditions.

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

[0006] In a first aspect, this application provides a method for controlling a vehicle thermal management unit in a cabin air conditioning system. The method includes: collecting data from the energy exchange controller regarding the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature; combining this data with the user-set temperature from the air conditioning controller and the target temperature requirement from the battery management system; and performing a judgment calculation according to a preset temperature priority to obtain system operating state characteristic values ​​and system operating mode signals; based on the system operating mode signals and system operating state characteristic values, using P... The ID control algorithm calculates the difference between the target battery temperature and the actual temperature, or the difference between the target evaporation temperature and the actual evaporation temperature, and, combined with the compressor's minimum operating time parameter, generates a compressor reference speed value and compressor operation control command. Based on the compressor reference speed value, compressor operation control command, and system superheat data, it calculates the valve reference opening value using a preset opening algorithm. Simultaneously, it performs compensation calculations on the valve reference opening value based on high and low pressure sensor data, outputting evaporator electronic expansion valve opening control signals and electronic expansion valve opening control signals. It acquires liquid level sensor and water pump operating status signals, and, combined with system operating status characteristic values, compressor reference speed value, and valve reference opening value, performs safety judgment calculations to generate an optimized water pump speed value and PTC power control command. The optimized water pump speed value and PTC power control command are then applied to the system. The control command is sent to the vehicle controller via the CAN bus; based on the compressor reference speed value, compressor operation control command, and valve reference opening value, the compressor operating 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 electronic expansion valve oil return opening value are output; the validity of each sensor signal in the system operating status characteristic value is judged. When a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system operating status characteristic value. Based on the corrected system operating status characteristic value, the compressor operation control command, evaporator electronic expansion valve opening control signal, electronic expansion valve opening control signal, water pump speed optimization value, and PTC power control command are adjusted. At the same time, fault information is recorded and uploaded to the vehicle system via the CAN bus.

[0007] Secondly, this application provides a vehicle thermal management unit control system for a cabin air conditioning system, the system comprising:

[0008] The data acquisition module is used to collect data on the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature from the energy exchange controller. It combines these data with the user-set temperature from the air conditioning controller and the target temperature requirements from the battery management system. The module performs calculations based on preset temperature priorities to obtain system operating status characteristic values ​​and system operating mode signals.

[0009] The calculation module is used to calculate the difference between the target battery temperature and the actual 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, using a PID control algorithm, and combined with the compressor minimum running time parameter to generate the compressor reference speed value and compressor operation control command.

[0010] The compensation module is used to calculate the valve reference opening value based on the compressor reference speed value, the compressor operation control command and the system superheat data through a preset opening algorithm, and to perform compensation calculation on the valve reference opening value based on the high and low pressure sensor data, and output the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal.

[0011] The control module is used to acquire the operating status signals of the liquid level sensor and the water pump, combine the system operating status characteristic value, the compressor reference speed value and the valve reference opening value, perform safety judgment calculation, generate the water pump speed optimization value and PTC power control command, and send the water pump speed optimization value and PTC power control command to the vehicle controller through the CAN bus;

[0012] The acquisition module is used to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control command and the valve reference opening value, calculate the oil return demand according to the preset judgment 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] The correction module is used to determine the validity of each sensor signal in the system operating state characteristic value. When a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system operating state characteristic value. Based on the corrected system operating state characteristic value, 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. At the same time, fault information is recorded and uploaded to the vehicle system via the CAN bus.

[0014] Thirdly, some embodiments of this application also provide an electronic device, the electronic device comprising: one or more processors; and a memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method described above.

[0015] The technical solution provided in this application achieves precise judgment of system operating status and mode switching control through comprehensive analysis of data from the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature, thereby improving the stability and reliability of system operation. The PID control algorithm is used to precisely control the temperature difference, and combined with the setting of the compressor's minimum operating time parameter, it effectively avoids frequent compressor start-stops and extends the compressor's service life. Precise control of the electronic expansion valve through a preset opening degree algorithm and pressure compensation calculation ensures that the system maintains appropriate superheat under different operating conditions, improving the system's cooling efficiency. Simultaneously, based on real-time monitoring of the liquid level sensor and water pump operating status, combined with safety judgment calculations, reliable operation of the water circuit system is achieved, effectively preventing faults such as dry burning. Furthermore, this method includes a complete oil return control strategy. Through continuous monitoring and analysis of the compressor's operating status, timely oil return control is performed to ensure the compressor's lubrication effect. Regarding sensor fault handling, parameter interpolation calculation and system state characteristic value correction are used to enable the system to maintain basic functions even in the event of sensor failure, improving the system's fault tolerance. The entire control process communicates with the vehicle system via the CAN bus, enabling real-time transmission of control information and timely reporting of fault information, thus facilitating system maintenance and fault diagnosis. This application achieves 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. Attached Figure Description

[0016] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0017] Figure 1 This is a schematic diagram of an embodiment of the vehicle thermal management unit control method for the cabin air conditioning system in this application.

[0018] Figure 2 This is a schematic diagram of an embodiment of the vehicle thermal management unit control system for the cabin air conditioning system in this application.

[0019] Figure 3 This is a schematic diagram of the electronic device structure provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the vehicle thermal management unit control method for the cabin air conditioning system in this application includes:

[0022] Step S101: The system working status characteristic value and system working mode signal are obtained by combining the battery pack inlet and outlet water temperature, heating system inlet and outlet water temperature, evaporator temperature and 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 according to the preset temperature priority.

[0023] Step S102: Based on the system working mode signal and system working state characteristic value, use PID control algorithm 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 combine the compressor minimum running time parameter to generate the compressor reference speed value and compressor running control command.

[0024] Step S103: Based on the compressor reference speed value, compressor operation control command and system superheat data, calculate the valve reference opening value through a preset opening algorithm. At the same time, perform compensation calculation on the valve reference opening value based on the high and low pressure sensor data, and output the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal.

[0025] Step S104: Obtain the liquid level sensor and water pump operating status signals, combine the system operating status characteristic value, compressor reference speed value and valve reference opening value, perform safety judgment calculation, generate water pump speed optimization value and PTC power control command, and send the water pump speed optimization value and PTC power control command to the vehicle controller through CAN bus;

[0026] Step S105: Based on the compressor reference speed value, compressor operation control command and valve reference opening value, obtain the compressor operating current value, calculate the oil return demand according to the preset judgment threshold, and when the oil return demand calculation result exceeds the threshold, output the compressor oil return speed value and the electronic expansion valve oil return opening value.

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

[0028] It is understood that the executing entity of this application can be the vehicle thermal management unit control system of the cabin air conditioning system, or it can be a terminal or a server; no specific limitation is made here. This application's embodiment uses a server as an example for illustration.

[0029] Specifically, the energy exchange controller collects various key temperature parameters. The battery pack inlet and outlet temperatures monitor battery cooling efficiency; calculating the temperature difference between the inlet and outlet water reveals the current battery heat dissipation status. The heating system inlet and outlet temperatures reflect the cabin heating system's operating status. The evaporator temperature is a crucial indicator of the air conditioning system's cooling performance. Ambient temperature serves as a reference benchmark for the entire system. Simultaneously, the control method receives user-set temperatures from the air conditioning controller, representing passengers' desired cabin temperature, and target temperature requirements from the battery management system—the range ensuring safe battery operation. In the temperature priority determination process, battery temperature control has higher priority because it directly affects vehicle safety. Based on the collected temperature data and system operating requirements, the energy exchange controller uses a PID control algorithm to precisely control the temperature difference. Specifically, when the system is in battery cooling mode, the difference between the target battery temperature and the actual temperature is used as the input for 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. A PID controller achieves precise regulation of compressor speed through the coordinated action of its proportional, integral, and derivative terms. In this process, the minimum operating time parameter of the compressor also needs to be considered, typically set to no less than 3 minutes. This parameter is set to ensure effective lubrication and extend the compressor's lifespan.

[0030] The control of the electronic expansion valve is a crucial component of the entire system. The controller calculates the valve's baseline opening value based on the compressor's operating status and system superheat data. System superheat is the difference between the actual temperature of the refrigerant leaving the evaporator and its saturation temperature at that pressure, typically controlled within the range of 5-15K. High and low pressure sensor data are used for real-time compensation of the valve opening. When the system pressure is too high or the low pressure is too low, the controller adjusts the electronic expansion valve opening accordingly to ensure safe system operation. The control of the water system is equally important. The controller monitors for liquid shortages in the water system using a level sensor and determines the water pump's normal operation based on its operating status signal. Combining the system's operating status and the compressor's operating parameters, the controller generates the optimal water pump speed and calculates the power control commands for the PTC (Positive Temperature Coefficient) heater. These control commands are sent to the vehicle controller via the CAN bus, enabling coordinated control with the entire vehicle system.

[0031] To ensure reliable compressor operation, the controller also implements an oil return control function. By monitoring the compressor's operating current and combining it with parameters such as compressor operating time and valve opening, it determines whether the system needs to perform an oil return operation. When oil return is determined to be necessary, the controller appropriately increases the compressor speed and adjusts the electronic expansion valve opening to promote lubricating oil return to the compressor. Finally, the controller also has sensor fault diagnosis and handling functions. When a sensor failure is detected, it estimates parameters using data from other normal sensors to ensure the system can maintain basic functions. Simultaneously, the controller adjusts various control commands accordingly and uploads fault information to the vehicle system via the CAN bus, reminding the driver to perform timely maintenance.

[0032] For example, during the operation of an electric bus, when the ambient temperature is 35℃, the target temperature issued by the battery management system is 25℃, while the actual battery temperature is 30℃. At this time, the controller inputs a battery temperature deviation of 5℃ into the PID controller. Based on the PID parameter settings (proportional coefficient 100, integral time 60s, derivative time 15s), the initial compressor speed is calculated to be 3000rpm. Simultaneously, the system detects a superheat of 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 water pump operating current is 4.5A, within the rated range (3-6A), and the controller maintains the water pump speed constant. After about 10 minutes of operation, the battery temperature drops to 26℃, and the system superheat stabilizes at 8K, achieving precise temperature control.

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

[0034] (1) The temperature difference between the inlet and outlet of the battery pack is calculated by the data acquisition unit to obtain characteristic data of battery temperature change;

[0035] (2) Based on the battery temperature change characteristic data, perform temperature gradient analysis on the inlet and outlet temperatures of the heating system to generate heating system temperature status data.

[0036] (3) Compare the evaporator temperature with the preset evaporation temperature threshold, and output the evaporator working status judgment result based on the ambient temperature data.

[0037] (4) Calculate the temperature difference between the user-set temperature issued by the air conditioning controller and the current ambient temperature to obtain the cabin temperature requirement 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 the battery cooling requirement characteristic value.

[0039] (6) Priority allocation is performed on the cabin temperature demand characteristic value and the battery cooling demand characteristic value through a priority sorting algorithm, and temperature demand priority data is output.

[0040] (7) Combining the temperature demand priority data and the evaporator working status judgment results, the threshold judgment method is used to screen the working mode and obtain the initial working mode data.

[0041] (8) Use the 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 system working state characteristic values;

[0042] (9) Based on the system working state feature values, the initial working mode data is corrected and calculated using the decision tree algorithm, and the system working mode signal is output.

[0043] (10) Combine and encapsulate the system operating status characteristic value and the system operating mode signal, and send them to the compressor control unit via CAN bus.

[0044] Specifically, the data acquisition unit processes the inlet and outlet temperatures of the battery pack. The unit collects temperature data from the inlet and outlet of the battery pack and calculates the temperature difference between them, which reflects the heat dissipation of the battery pack. When the outlet temperature is higher than the inlet temperature, it indicates that the battery is overheating and needs cooling; conversely, it indicates that the battery is cooling down. Based on the obtained battery temperature change characteristic data, the controller further analyzes the inlet and outlet temperatures of the heating system. By comparing temperature data at different time points, the rate of temperature change of the heating system is calculated. This rate of change reflects the actual heating or cooling capacity of the heating system and has important guiding significance for subsequent system control strategies.

[0045] Evaporator temperature control is a crucial component of the entire system. The controller compares the real-time evaporator temperature with a pre-set temperature threshold. This threshold is not fixed but dynamically adjusted based on the ambient temperature. For example, in high-temperature summer environments, the evaporator temperature is allowed to fluctuate within a relatively high range; while in mild or cold environments, the control range for the evaporator temperature will be correspondingly reduced to ensure cooling efficiency. Cabin temperature control requirements are determined by comparing the user-set temperature with the current ambient temperature. This temperature difference directly reflects the actual cooling or heating needs of the cabin. For instance, when the ambient temperature is significantly higher than the user-set temperature, the system needs to provide a larger cooling capacity; conversely, it needs to provide heating capacity.

[0046] Battery cooling requirements are determined by analyzing the difference between the target temperature issued by the battery management system and the current actual battery temperature. The larger this difference, the more urgent the battery cooling requirement. The controller adjusts the system's operating strategy based on this difference. After obtaining the cabin temperature and battery cooling requirements, the controller analyzes them using a priority ranking algorithm. This algorithm assigns different weights to the two requirements, typically giving higher weight to battery cooling because battery temperature is directly related to vehicle safety. The system's operating priority is determined by calculating a weighted score.

[0047] By combining temperature demand priority data and evaporator operating status, the controller uses a threshold-based method to select the appropriate operating mode. When the temperature deviation exceeds a specific threshold, the system switches to the corresponding operating mode, such as a single battery cooling mode or a hybrid cooling mode. The state matrix algorithm establishes a multi-dimensional state space and comprehensively analyzes various temperature and operating mode data. This analysis method can comprehensively consider the operating status of each part of the system, providing a basis for subsequent control decisions.

[0048] The decision tree algorithm then refines the initially selected operating mode through a series of conditional judgments. Factors considered include the magnitude of the temperature difference, system load status, and environmental conditions, ultimately determining the optimal operating mode through a multi-layered selection process. Finally, the controller encapsulates all processing results. This data, including system operating status characteristic values ​​and operating mode signals, is transmitted to the compressor control unit using the standard CAN communication protocol, achieving coordinated control of the entire system.

[0049] For example, during a typical operation, the controller detected a battery pack inlet temperature of 25°C and an outlet temperature of 30°C, a temperature difference of 5°C, indicating that the battery was generating significant heat. Simultaneously, the heating system temperature rose by 1.5°C within 10 seconds, the evaporator temperature remained at 4°C, and the ambient temperature was 32°C. The user set the cabin temperature to 24°C, while the battery management system required the battery temperature to be maintained below 25°C. The controller, using a priority ranking algorithm, determined that the battery cooling requirement was more urgent and therefore selected a battery-priority hybrid cooling mode, sending corresponding control commands to the compressor control unit via the CAN bus. This control strategy successfully reduced the battery temperature to a safe range while maintaining adequate cabin cooling, achieving optimal system operation.

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

[0051] (1) Extract the actual battery temperature data and the actual evaporator temperature data from the system working state characteristic values. Calculate the difference between the target battery temperature and the actual battery temperature data using a temperature difference calculator to obtain the battery temperature error value. At the same time, calculate the difference between the target evaporation temperature and the actual evaporator temperature data to obtain the evaporation temperature error value.

[0052] (2) Select the battery temperature error value or evaporation temperature error value according to the system working mode signal, perform temperature deviation compensation calculation through PID control algorithm, and generate the initial compressor speed control quantity;

[0053] (3) Compare the initial compressor speed control value with the upper and lower limits of the compressor speed to generate the compressor limit speed value. At the same time, calculate the rate of change between the compressor limit speed value and the historical speed data, and output the compressor reference speed value.

[0054] (4) Time constraint processing is performed on the compressor reference speed value and the compressor minimum running time parameter to obtain the compressor protection control parameters;

[0055] (5) The compressor reference speed value and compressor protection control parameters are prioritized by the comparison and calculation unit to generate compressor running sequence data;

[0056] (6) Generate compressor operation control commands based on compressor operation sequence data and compressor reference speed value, and send the compressor operation control commands to the compressor drive unit via CAN bus.

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

[0058] The following mathematical model is used in the temperature deviation compensation calculation:

[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 derivative 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 appropriate temperature error value according to the system operating mode signal and inputs it into the PID control algorithm for processing. The PID control algorithm is calculated using the above formula, where the proportional term is used for rapid response to temperature changes, the integral term eliminates steady-state errors, the derivative term provides anticipatory control, and the nonlinear term enhances the algorithm's ability to correct for large temperature deviations. After calculation, the initial compressor speed control value is output. The controller then limits the initial compressor speed control value, comparing it with preset upper and lower speed limits (usually 6000 rpm) to generate a limited compressor speed value. This limiting process ensures that the compressor operates within a safe speed range. Simultaneously, the controller calculates the rate of change between the limited speed value and historical speed data to avoid excessively drastic speed changes, thereby outputting a reference compressor speed value.

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

[0063] The comparator then prioritizes the compressor's reference speed and protection control parameters. During this process, the protection control parameters have higher priority, and in the event of a conflict, the protection control is executed first. Through this process, the controller generates compressor runtime sequence data containing information such as startup timing and running time.

[0064] Finally, based on the compressor's runtime sequence data and the compressor's reference speed value, the controller generates a complete compressor operation control command. This command includes information such as the speed setpoint, operating status, and protection parameters, and is packaged according to the standard CAN communication protocol format before being sent to the compressor drive unit.

[0065] For example, during the operation of an electric bus's air conditioning system, the controller detected an actual battery temperature of 32℃, while the target temperature was 25℃, resulting in a calculated battery temperature error of 7℃. Simultaneously, the actual evaporator temperature was 8℃, while the target temperature was 5℃, resulting in an evaporator temperature error of 3℃. Due to the significant battery temperature deviation and the battery cooling priority mode, the controller selected the battery temperature error value as input to the PID controller. Based on the aforementioned temperature deviation compensation formula, setting λ1 = 100, λ2 = 50, λ3 = 25, γ = 10, and η = 5, the initial compressor speed control value was calculated to be 4500 rpm. After amplitude limiting (within the range of 1800-6000 rpm) and rate-of-change limitation (maximum change of 200 rpm per second), the final compressor base speed value was determined to be 4200 rpm. Combining this with the minimum running time parameter (180 seconds) to generate the runtime sequence, the complete control command was finally sent to the compressor drive unit via the CAN bus, achieving efficient battery temperature control.

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

[0067] (1) Interpolation calculation is performed between the compressor reference speed value and the speed correction curve, and the operating status parameters of the compressor operation control command are analyzed to generate the basic valve opening coefficient.

[0068] (2) Obtain system superheat data through temperature acquisition unit, determine the range of system superheat data, and generate superheat correction coefficient;

[0069] (3) The basic valve opening coefficient and the superheat correction coefficient are weighted and fused together to output the valve reference opening value;

[0070] (4) Collect high and low pressure sensor data, perform signal filtering processing through pressure sensor signal conditioning circuit to obtain system high pressure value and system low pressure value, calculate the pressure ratio of system high pressure value and system low pressure value, and output system pressure correction parameters;

[0071] (5) Perform linear compensation calculation on the valve reference opening value based on the system pressure correction parameters to generate the compensated valve opening value;

[0072] (6) The compensated valve opening value is calculated according to the evaporator load and battery cooling load by using the flow distribution algorithm, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are generated respectively.

[0073] (7) The slope of the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal is limited to obtain electronic expansion valve control data with limited opening change rate.

[0074] (8) The control data of the electronic expansion valve with limited opening change 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 compressor's reference speed value, calculates the corresponding correction coefficient using cubic spline interpolation by consulting a pre-calibrated speed correction curve data table. Simultaneously, it analyzes parameters such as running time and load status included in the compressor's operation control commands, adjusts the correction coefficients based on these parameters, and finally calculates the basic valve opening coefficient. 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 at that pressure to calculate the system superheat data. Generally, the superheat needs to be controlled within the range of 5-15K. Based on the range of the superheat data, the controller generates a corresponding superheat correction coefficient. When the superheat is below 5K, the correction coefficient is less than 1, and the valve opening is reduced to increase the superheat; when the superheat is above 15K, the correction coefficient is greater than 1, and the valve opening is increased to decrease the superheat.

[0076] The baseline valve opening coefficient and superheat correction coefficient are weighted to generate the valve reference opening value. During the weighted calculation, the baseline opening coefficient has a weight of 0.7, and the superheat correction coefficient has a weight of 0.3. This ensures both the output of the basic cooling capacity and effective regulation of superheat. The acquisition 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 acquired pressure signal, with a cutoff frequency set to 10Hz to eliminate high-frequency interference. After filtering, accurate system high and low pressure values ​​are obtained. The pressure ratio, calculated by dividing the system high pressure value by the low pressure value, reflects the system's compression ratio and thus affects the opening control of the electronic expansion valve.

[0077] The system pressure correction parameter is calculated using the pressure ratio. When the pressure ratio is too high (typically greater than 4.5), it indicates an excessively large system pressure differential, requiring an appropriate increase in the electronic expansion valve opening. Conversely, when the pressure ratio is too low (typically less than 2.5), it indicates an excessively small system pressure differential, requiring an appropriate decrease in the electronic expansion valve opening. This correction parameter is linearly compensated against the valve's reference opening value to obtain the compensated valve opening value. The flow distribution algorithm is a crucial component of the entire control process. This algorithm distributes the compensated valve opening value based on the ratio of evaporator load to battery cooling load. The load ratio is calculated using temperature demand and target temperature deviation, thereby determining the opening control signal for each electronic expansion valve.

[0078] To prevent excessively drastic changes in the opening of the electronic expansion valve, the controller limits the rate of change. Typically, the rate of change is limited to no more than 2% of the total stroke per second. This prevents sudden changes in system cooling and protects the electronic expansion valve itself. After slope limiting, smooth electronic expansion valve control data is obtained. Finally, the control data is converted into valve step control pulses. Electronic expansion valves are usually driven by stepper motors. The controller generates a corresponding pulse sequence through the valve drive circuit, driving 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's base speed is 3600 rpm, the basic valve opening coefficient is calculated to be 0.85 through speed correction curve interpolation. The temperature acquisition unit measures the system superheat to be 12 K, which is within the normal range, and the calculated superheat correction coefficient is 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 a system high pressure value of 2.2 MPa, a low pressure value of 0.6 MPa, and a pressure ratio of 3.67, from which the pressure correction parameter is calculated to be 1.02. The compensated valve opening value 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 allocates the opening value of 0.93 as follows: evaporator electronic expansion valve opening 0.56 (0.93 × 0.6), battery-side electronic expansion valve opening 0.37 (0.93 × 0.4). Finally, after slope limiting and drive circuit conversion, the corresponding step control pulse is output, realizing the precise control of the electronic expansion valve.

[0080] In one 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 at the same time perform current sampling analysis on the water pump working status signal to generate water system fault characteristic data.

[0082] (2) The temperature data in the system's operating state characteristic values ​​are calculated over time by the integrator, and the temperature change trend characteristic value is output.

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

[0084] (4) Based on the compressor's safe operating parameters, the rated speed of the water pump is dynamically adjusted and calculated using a frequency conversion control algorithm to generate an optimized value for the water pump speed.

[0085] (5) Perform correlation analysis between the valve reference opening value and the temperature change trend characteristic value, calculate the PTC heating power demand through the power control algorithm, and output the PTC power control command;

[0086] (6) Convert the data format of the water pump speed optimization value and PTC power control command, generate CAN communication data packets, and send the CAN communication data packets to the vehicle controller in accordance with the communication protocol;

[0087] (7) The response signal of the vehicle controller is verified and calculated by the feedback verification algorithm to generate control command execution status data;

[0088] (8) Perform deviation analysis between the control command execution status data and the actual operating parameters, and make real-time corrections to the optimized value of the water pump speed and the PTC power control command.

[0089] Specifically, the liquid level sensor monitors the liquid level status of the water system in real time. By comparing the detected liquid level signal with a preset liquid level threshold (usually 20% of the tank capacity), it determines whether the water system is in a state of low liquid level. Simultaneously, the controller monitors the water pump's operating status, acquiring the pump's operating current value through a current sampling circuit. The normal operating current range is 3-6A; exceeding this range indicates a pump malfunction. Based on the analysis results of the liquid level status and the water pump's operating status, fault characteristic data of the water system, including fault type and fault level, is generated. Integral processing of temperature data is an important means of judging the system's operating trend. The integrator continuously samples the temperature data in the system's operating status characteristic values ​​at 100ms intervals, and calculates the cumulative temperature change over a certain time period (usually 10 minutes) through accumulation. This cumulative value reflects the temperature change trend, thereby predicting the system's operating trend. For example, when the temperature continues to rise, the cumulative value is positive and gradually increases, indicating insufficient system heat dissipation; when the temperature tends to stabilize, the cumulative value approaches zero.

[0090] To ensure safe system operation, the controller comprehensively analyzes water circuit fault characteristic data and temperature change trend characteristic values. When a water circuit fault or abnormal temperature change trend is detected, the compressor's reference speed needs to be limited. Limiting strategies include: when a minor fault is detected, limiting the compressor speed to within 80% of the reference speed; when a serious fault is detected, reducing the speed to the minimum operating speed, and shutting down for protection if necessary. Optimized control of the water pump speed is achieved through a variable frequency drive (VFD) algorithm. Based on the compressor's safe operating parameters, the VFD dynamically calculates the required flow rate and then determines the water pump speed. The speed adjustment range is 1000-3000 rpm, with the specific adjustment strategy as follows: 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 temperature change trend characteristics. When the valve opening is small and the temperature change trend indicates insufficient cooling capacity, the PTC power output is increased; conversely, the power output is decreased. The PTC power adjustment range is 0-6kW, using a segmented control method with each segment incrementing by 0.5kW. For data communication, the controller needs to convert the optimized pump speed value and PTC power control commands into the standard CAN communication format. The CAN data packet contains: a data identifier (used to distinguish different types of control commands), a data length (usually 8 bytes), and specific data content (including control values, status flags, etc.). The data packet is encapsulated and transmitted according to the standard CAN 2.0B protocol.

[0092] The feedback verification algorithm employs Cyclic Redundancy Check (CRC) to verify the response signal returned by the vehicle controller. Verification includes: data packet integrity, data value validity, and timing correctness. Through verification calculations, control command execution status data containing information such as execution results and execution time is generated. Finally, the execution effect of the control commands is evaluated. The control command execution status data is compared with actual operating parameters (including actual water pump speed and actual PTC power) to calculate the control deviation. When the deviation exceeds the allowable range, the optimized water pump speed value and PTC power control commands are corrected to ensure control accuracy.

[0093] For example, during the operation of an electric bus, the water level sensor detected that the water tank level had dropped to 18%, below the 20% warning threshold, while the water pump operating current was 5.8A, close to the upper limit of 6A. Based on these two abnormal indicators, fault characteristic data of the water system was generated and marked as "minor fault". Temperature integral calculation showed that the system temperature had cumulatively increased by 3.5℃ in the last 10 minutes, indicating a decrease in heat dissipation capacity. Accordingly, the controller reduced the compressor base speed from 4000rpm to 3200rpm (a 20% reduction) and increased the water pump speed from 2400rpm to 2800rpm, increasing the circulating water flow. Regarding PTC power control, since the valve opening had dropped to 45% and the temperature was trending upward, the controller adjusted the PTC power from 3kW to 4kW. These control commands were sent to the vehicle controller via the CAN bus (using a baud rate of 250kbps) and a response signal was received within 50ms. The CRC check confirmed that the command was executed correctly. The deviation between the actual operating parameters and the control command was within 5%, and no correction was required, thus achieving safe and stable operation of the system.

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

[0095] (1) Multiply the runtime data in the compressor operation control command with the compressor reference speed value to generate the compressor cumulative operation 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 compressor's cumulative operating data and the valve's reference opening value, a threshold judgment algorithm is used to calculate the oil return time window and generate an oil return trigger signal;

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

[0099] (5) When the calculated oil return demand exceeds the threshold, the compressor reference speed value is increased by the speed compensation algorithm to obtain the compressor oil return speed value.

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

[0101] Specifically, during prolonged compressor operation, lubricating oil circulates throughout the system components along with the refrigerant. A specific oil return control strategy is needed to ensure timely return of the lubricating oil to the compressor. The controller first multiplies the runtime data (in seconds) from the compressor's operating control command with the compressor's base speed value to obtain cumulative operating data reflecting the compressor's actual workload. For example, when the compressor runs continuously at 3000 rpm for 1800 seconds, the cumulative operating data is 5.4 × 10⁶. The current sampling circuit samples the compressor's operating current using a Hall sensor at a sampling frequency of 10 Hz. The sampled current value is compared with a 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 a change in the compressor's load condition. By comparing the deviation between the actual current value and the standard value, the compressor load characteristic value is calculated. Under standard operating conditions, 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 is overloaded; conversely, it indicates that the load is light.

[0102] The compressor's cumulative operating data and the valve's baseline opening value are crucial for determining whether oil return is needed. The threshold judgment algorithm calculates the oil return time window based on these two parameters. When the cumulative operating volume exceeds 4 × 10⁶ and the valve opening is below 50%, the first stage of oil return is triggered; when the cumulative operating volume exceeds 8 × 10⁶, forced oil return is triggered regardless of the valve opening. The oil return time window is typically set to 180-300 seconds, during which the system executes a specific oil return control strategy. The compressor load characteristic value plays a regulatory role in oil return control. The controller uses a weighted processing method: when the load characteristic value is large, the weight of oil return demand is increased; when the load characteristic value is small, the weight is decreased. This weighted processing allows oil return control to better adapt to the compressor's actual operating state. 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 weighted oil return demand calculation exceeds a preset threshold (usually 1.2), the controller initiates the oil return control program. The speed compensation algorithm increases the compressor's base speed by 20-30% to increase refrigerant flow and promote lubricant return. However, the increased speed must not exceed the compressor's maximum allowable speed (usually 6000 rpm). Simultaneously, to avoid sudden changes impacting the system, the speed increase uses a ramp function, gradually reaching the target value within 5 seconds. The electronic expansion valve's opening control also needs to coordinate with the oil return operation. The controller corrects the valve's base opening value based on the compressor's oil return speed. The basic principle of correction is to appropriately increase the opening to improve refrigerant flow while ensuring system superheat. Generally, the valve opening is increased by 15-25%, while closely monitoring the system superheat to ensure it remains within the safe range of 5-15K.

[0104] For example, during the operation of an electric bus's air conditioning system, the compressor ran continuously at 3500 rpm for 2400 seconds, resulting in a cumulative operating load of 8.4 × 10⁶, exceeding the oil return trigger threshold. The current sampling circuit measured the compressor's actual operating current at 15A, while the standard operating current at that speed is 12A, resulting in a calculated load characteristic value of 1.25. Due to the high load characteristic value, the weighting coefficient for 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 then initiated the oil return program, increasing the compressor speed from 3500 rpm to 4550 rpm (a 30% increase) and simultaneously increasing the electronic expansion valve opening from 60% to 75%. This oil return process lasted 240 seconds, during which the compressor current gradually decreased to 13A, indicating improved lubrication. After the oil return was completed, the system returned to normal operating parameters, ensuring reliable compressor operation.

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

[0106] (1) Verify the effective range of temperature sensor signals and pressure sensor signals in the characteristic values ​​of system working status, identify abnormal data through signal mutation detection algorithm, and generate sensor fault flag bits;

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

[0108] (3) Select normal sensor signals based on sensor failure characteristic data, and use Kalman filtering algorithm to estimate the state of missing data to obtain sensor compensation data;

[0109] (4) Use sensor compensation data to reconstruct the system operating state characteristic values ​​and generate corrected system operating state characteristic values;

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

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

[0112] (7) Pack the sensor failure characteristic data and the corrected control commands into a fault information data packet and upload it to the vehicle system via the CAN bus.

[0113] Specifically, the controller first verifies the effective range of the signals from the temperature and pressure sensors. 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. Simultaneously, a signal mutation detection algorithm identifies abnormal data by calculating the rate of change between adjacent sampling points. When the rate of change of the temperature sensor exceeds 5℃ / s or the rate of change of the pressure sensor exceeds 0.5MPa / s, it is determined to be a signal mutation. Based on these judgments, a sensor fault flag bit containing information such as fault location and fault type is generated. Time-series analysis of sensor historical data is crucial for fault diagnosis. The controller stores sensor data from the most recent 10 minutes in a buffer and determines the fault type by analyzing data change trends. For example, when the output value of a sensor remains consistently at the upper or lower limit of its range, it indicates a range saturation fault; when the output value exhibits random fluctuations, 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. This fault type information is packaged into sensor failure characteristic data.

[0114] For data from failed sensors, the controller employs a Kalman filter algorithm for state estimation. This algorithm predicts the theoretical values ​​of the failed sensor based on data from other normally functioning sensors and the system's dynamic characteristics. For example, when the evaporator outlet temperature sensor fails, the temperature value at that point can be estimated based on system pressure and data from other temperature sensors. The Kalman filter algorithm continuously optimizes the estimation results through prediction and correction steps, obtaining reliable sensor compensation data. During the reconstruction of the system's operating state characteristic values, the original data from the failed sensor is replaced with the sensor compensation data. Reconstruction must consider the correlation between parameters to ensure that the reconstructed data conforms to thermodynamic laws. For example, the evaporator's temperature and pressure data must meet the requirements of the refrigerant's saturation characteristic curve. After reconstruction, the corrected system operating state characteristic values ​​are obtained.

[0115] The compensation control algorithm calculates corrections for each actuator based on the corrected system state characteristic values. Compressor speed correction primarily considers the system's cooling capacity requirement, typically within ±20%; electronic expansion valve opening correction is based on the system's superheat control requirements, within ±15%; water pump speed correction is determined by flow rate requirements, within ±30%; and PTC power correction is based on heating requirements, within ±25%. The controller applies these corrections to the original control commands, generating new execution commands. The correction process employs a gradual adjustment strategy to avoid sudden changes in control values ​​that could impact the system. The corrected control commands 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 adopts the standard CAN protocol format and contains information such as fault code, fault level, and correction strategy. It is sent to the vehicle controller via 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℃ to -45℃, exceeding the sensor's effective range (-40℃ to 120℃). Simultaneously, the rate of change of this data point reached 26℃ / s, far exceeding the normal threshold of 5℃ / s. The controller immediately marked this sensor as faulty. Analysis of the historical data from the last 10 minutes revealed that the sensor was functioning normally before the fault, with the output value fluctuating steadily between 6-10℃. Based on this abrupt change, a short-circuit fault in the sensor was determined. The controller then activated the Kalman filter algorithm, estimating the evaporator outlet temperature to be 7.5℃ based on data from the normally functioning pressure sensor (displaying an evaporation pressure of 0.6MPa) and other temperature sensors. This compensated data was used to reconstruct the system's operating state, and the control parameters were adjusted accordingly: the compressor speed was adjusted from 3600rpm to 3100rpm (a 14% reduction), the electronic expansion valve opening was adjusted from 65% to 58% (an 11% reduction), while the water pump speed and PTC power remained 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, thus enabling reliable degraded operation of the system.

[0118] The steps of the various methods described above are only for clarity. In practice, they can be combined into one step or some steps can be split 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 or introducing insignificant designs to the algorithm or process, but without changing the core design of the algorithm and process, are also within the scope of protection of this patent.

[0119] Second Embodiment

[0120] The control method for the vehicle thermal management unit of the cabin air conditioning system in this application embodiment has been described above. The control system for the vehicle thermal management unit of the cabin air conditioning system in this application embodiment is described below. Please refer to [link / reference]. Figure 2 One embodiment of the vehicle thermal management unit control system for the cabin air conditioning system in this application includes:

[0121] The data acquisition module is used to collect data on the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature from the energy exchange controller. It combines these data with the user-set temperature from the air conditioning controller and the target temperature requirements from the battery management system. The module performs calculations based on preset temperature priorities to obtain system operating status characteristic values ​​and system operating mode signals.

[0122] The calculation module is used to calculate the difference between the target battery temperature and the actual 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, using a PID control algorithm, and combined with the compressor minimum running time parameter to generate the compressor reference speed value and compressor operation control command.

[0123] The compensation module is used to calculate the valve reference opening value based on the compressor reference speed value, the compressor operation control command and the system superheat data through a preset opening algorithm, and to perform compensation calculation on the valve reference opening value based on the high and low pressure sensor data, and output the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal.

[0124] The control module is used to acquire the operating status signals of the liquid level sensor and the water pump, combine the system operating status characteristic value, the compressor reference speed value and the valve reference opening value, perform safety judgment calculation, generate the water pump speed optimization value and PTC power control command, and send the water pump speed optimization value and PTC power control command to the vehicle controller through the CAN bus;

[0125] The acquisition module is used to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control command and the valve reference opening value, calculate the oil return demand according to the preset judgment 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] The correction module is used to determine the validity of each sensor signal in the system operating state characteristic value. When a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system operating state characteristic value. Based on the corrected system operating state characteristic value, 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. At the same time, fault information is recorded and uploaded to the vehicle system via the CAN bus.

[0127] Through the coordinated operation of the aforementioned components, and by comprehensively analyzing data on the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature, precise judgment of the system's operating status and mode switching control are achieved, improving the system's stability and reliability. A PID control algorithm is used to precisely control the temperature difference, combined with the setting of the compressor's minimum operating time parameter, effectively avoiding frequent compressor start-stops and extending the compressor's lifespan. Precise control of the electronic expansion valve through a preset opening algorithm and pressure compensation calculation ensures that the system maintains appropriate superheat under different operating conditions, improving the system's cooling efficiency. Simultaneously, based on real-time monitoring of the liquid level sensor and water pump operating status, combined with safety judgment calculations, reliable operation of the water circuit system is achieved, effectively preventing faults such as dry burning. Furthermore, this method includes a complete oil return control strategy; through continuous monitoring and analysis of the compressor's operating status, timely oil return control is performed to ensure the compressor's lubrication effect. Regarding sensor fault handling, parameter interpolation calculation and system state characteristic value correction are used, enabling the system to maintain basic functions even in the event of sensor failure, improving the system's fault tolerance. The entire control process communicates with the vehicle system via the CAN bus, enabling real-time transmission of control information and timely reporting of fault information, thus facilitating system maintenance and fault diagnosis. This control method, through multiple protection strategies and precise control algorithms, achieves efficient integration of battery temperature control and cabin air conditioning, improving energy efficiency while ensuring system reliability.

[0128] It is not difficult to see that this embodiment is a system implementation 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 will not be repeated here to reduce repetition. Accordingly, the relevant technical details mentioned in this embodiment can also be applied to the first embodiment.

[0129] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problem proposed in this application; however, this does not mean that other units are absent from this embodiment.

[0130] Furthermore, some embodiments of this application also provide an electronic device. The electronic device can be various forms of digital computer, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, etc. The electronic device can also be various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices.

[0131] Figure 3 An exemplary structural diagram of the electronic device is disclosed. For example... Figure 3 As shown, the electronic device includes one or more processors 1101, a memory 1102, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components are interconnected via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple electronic devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). The components, their connections and relationships, and their functions shown herein are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0132] The electronic device may further include an input device 1103 and an output device 1104. The processor 1101, memory 1102, input device 1103, and output device 1104 may be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0133] Input device 1103 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the electronic device, such as a touch screen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 1104 may include a display device, auxiliary lighting device (e.g., LED), and haptic feedback device (e.g., vibration motor). 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 the user, the electronic device can be a computer. The computer has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0135] In this embodiment, a computer-readable medium stores a computer program / instructions that, when executed by a processor, implement the steps of the methods provided in any one or more of the above embodiments. This computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into that device. The aforementioned computer-readable medium carries one or more computer-readable instructions.

[0136] The memory 1102 can serve as a non-transitory computer-readable storage medium, used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 1102, thereby implementing the program instructions / modules corresponding to the methods provided in any one or more of the embodiments described above in this application.

[0137] The memory 1102 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device. Furthermore, the memory 1102 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1102 may optionally include memory remotely located relative to the processor 1101, and these remote memories can be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

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

[0139] Computer-readable media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. 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 technologies, read-only optical disc (CD-ROM), digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0140] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltank, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can 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 can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0141] In the above embodiments, all or part of the implementation can be achieved through software, hardware, firmware, or any combination thereof. For example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In some embodiments, the software program of this application can be executed by a processor to implement the above steps or functions. Similarly, the software program of this application (including related data structures) can be stored in a computer-readable recording medium, such as RAM memory, magnetic or optical drives, floppy disks, and similar devices. In addition, some steps or functions of this application can be implemented in hardware, for example, as circuitry that cooperates with a processor to perform the various steps or functions.

[0142] The computer program product provided in this application includes one or more computer programs / instructions. When executed by a processor, these computer programs / instructions generate, in whole or in part, the processes or functions described in this application. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive (SSD)).

[0143] The flowcharts or block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-specific system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0144] The scope of this application is defined by the appended claims rather than the foregoing description, and is therefore intended to encompass all variations falling within the meaning and scope of equivalents of the claims. No reference numerals in the claims should be construed as limiting the scope of the claims. Furthermore, 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 recited in a device claim may also be implemented by a single unit or device in software or hardware. Terms such as "first," "second," etc., are used only for distinguishing descriptions and do not indicate any particular order, nor should they be construed as indicating or implying relative importance.

[0145] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily made by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims, and the above embodiments should be regarded as exemplary and non-limiting.

Claims

1. A control method for a vehicle thermal management unit in a cabin air conditioning system, characterized in that, The method includes: The system's operating status characteristic value and operating mode signal are obtained by combining the battery pack inlet and outlet water temperature, heating system inlet and outlet water temperature, evaporator temperature and 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 according to the preset temperature priority. Based on the system operating mode signal and the system operating state characteristic value, the PID control algorithm is used to calculate the difference between the target battery temperature and the actual temperature or the difference between the target evaporation temperature and the actual evaporation temperature. Combined with the compressor minimum running time parameter, the compressor reference speed value and compressor operation control command are generated. Based on the compressor reference speed value, the compressor operation control command, and the system superheat data, the valve reference opening value is calculated through a preset opening algorithm. At the same time, the valve reference opening value is compensated based on 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 system acquires the operating status signals of the liquid level sensor and the water pump, combines the system operating status characteristic value, the compressor reference speed value and the valve reference opening value to perform a safety judgment calculation, generates the water pump speed optimization value and PTC power control command, and sends the water pump speed optimization value and PTC power control command 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 operating 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's operating 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 operating state characteristic value. Based on the corrected system operating state characteristic value, 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. At the same time, fault information is recorded and uploaded to the vehicle system via the CAN bus.

2. The vehicle thermal management unit control method for the cabin air conditioning system according to claim 1, characterized in that, The system collects data on the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature from the energy exchange controller. This data is then combined with the user-set temperature from the air conditioning controller and the target temperature requirement from the battery management system. Based on a preset temperature priority, the system calculates and determines its operating status characteristic values ​​and operating mode signals, including: The battery temperature change characteristic data are obtained by performing a difference calculation on the inlet and outlet temperatures of the battery pack through the data acquisition unit. Based on the battery temperature change characteristic data, temperature gradient analysis is performed on the inlet and outlet temperatures of the heating system to generate heating system temperature status data. The evaporator temperature is compared with the preset evaporation temperature threshold, and the ambient temperature data is combined to output the evaporator working status judgment result. The temperature difference between the user-set temperature issued by the air conditioning controller and the current ambient temperature is calculated to obtain the cabin temperature requirement characteristic value. The target temperature requirement issued by the battery management system is compared with the battery temperature change characteristic data to generate a battery cooling requirement characteristic value. The cabin temperature requirement feature value and the battery cooling requirement feature value are prioritized using a priority sorting algorithm, and the temperature requirement priority data is output. Combining the temperature demand priority data and the evaporator operating status judgment results, a threshold judgment method is used to filter the operating modes to obtain initial operating mode data; The battery temperature change characteristic data, the heating system temperature state data, and the initial working mode data are comprehensively processed using a state matrix algorithm to generate the system working state characteristic value. Based on the system operating state feature values, the initial operating mode data is corrected and calculated using a decision tree algorithm, and the system operating mode signal is output. The system operating status characteristic value and the system operating mode signal are combined and encapsulated, and then sent to the compressor control unit via the CAN bus.

3. The vehicle thermal management unit control method for the cabin air conditioning system according to claim 1, characterized in that, Based on the system operating mode signal and the system operating state characteristic value, the PID control algorithm is used to calculate the difference between the target battery temperature and the actual temperature, or the difference between the target evaporation temperature and the actual evaporation temperature. Combined with the compressor minimum running time parameter, a compressor reference speed value and compressor operation control commands are generated, including: The actual battery temperature data and the actual evaporator temperature data are extracted from the system's operating state characteristic values. The difference between the target battery temperature and the actual battery temperature data is calculated by a temperature difference calculator to obtain the battery temperature error value. At the same time, the difference between the target evaporation temperature and the actual evaporator temperature data is calculated to obtain the evaporation temperature error value. Based on the system operating mode signal, the battery temperature error value or the evaporation temperature error value is selected, and the temperature deviation compensation calculation is performed by the PID control algorithm to generate the initial compressor speed control quantity. The initial compressor speed control value is compared with the upper and lower limits of the compressor speed to generate the compressor limit speed value. At the same time, the rate of change of the compressor limit speed value is calculated with historical speed data to output the compressor reference speed value. The compressor reference speed value and the compressor minimum operating time parameter are subjected to time constraint processing to obtain the compressor protection control parameters; The compressor reference speed value and the compressor protection control parameters are prioritized by a comparison arithmetic unit to generate compressor runtime sequence data. Based on the compressor's runtime sequence data and the compressor's reference speed value, the compressor's operation control command is generated and sent to the compressor drive unit via the CAN bus.

4. The vehicle thermal management unit control method for the cabin air conditioning system according to claim 1, characterized in that, The process involves calculating a valve reference opening value using a preset opening algorithm based on the compressor reference speed value, the compressor operation control command, and system superheat data. Simultaneously, compensation calculations are performed on the valve reference opening value based on high and low pressure sensor data. The process then outputs an evaporator electronic expansion valve opening control signal and an electronic expansion valve opening control signal, including: Interpolation calculations are performed between the compressor's reference speed value and the speed correction curve. Simultaneously, the operating status parameters of the compressor's operating control command are analyzed and calculated to generate the basic valve opening coefficient. The system superheat data is acquired through a temperature acquisition unit, and the system superheat data is range-determined to generate a superheat correction coefficient. The basic valve opening coefficient and the superheat correction coefficient are weighted and fused together to calculate the valve reference opening value. The high and low pressure sensor data are collected, and the signal is filtered through the pressure sensor signal conditioning circuit to obtain the system high pressure value and the system low pressure value. The pressure ratio of the system high pressure value and the system low pressure value is calculated, and the system pressure correction parameter is output. A linear compensation calculation is performed on the valve reference opening value based on the system pressure correction parameters to generate the compensated valve opening value. The compensated valve opening value is calculated according to the evaporator load and battery cooling load using a flow distribution algorithm, and the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal are generated respectively. The slope limitation processing is performed on the opening control signal of the evaporator electronic expansion valve and the electronic expansion valve opening control signal to obtain electronic expansion valve control data with limited opening change rate; The control data of the electronic expansion valve with limited opening change rate is converted into valve step control pulses through the valve drive circuit and output to the corresponding electronic expansion valve actuator.

5. The vehicle thermal management unit control method for the cabin air conditioning system according to claim 1, characterized in that, The process of acquiring the liquid level sensor and water pump operating status signals, combining them with the system operating status characteristic values, the compressor reference speed value, and the valve reference opening value, performing a safety judgment calculation, generating an optimized water pump speed value and a PTC power control command, and sending the optimized water pump speed value and the PTC power control command to the vehicle controller via the CAN bus includes: The liquid level sensor signal is compared and calculated with the liquid level threshold, and the water pump operating status signal is sampled and analyzed to generate water system fault characteristic data. The temperature data in the system's operating state characteristic values ​​are calculated over time by an integrator, and the temperature change trend characteristic value is output. By combining 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 compressor safe operating parameters; Based on the compressor's safe operating parameters, the rated speed of the water pump is dynamically adjusted and calculated using a frequency conversion control algorithm to generate the optimized water pump speed value. The valve reference opening value is correlated with the temperature change trend characteristic value, and the PTC heating power requirement is calculated through a power control algorithm, and the PTC power control command is output. The optimized water pump speed value and the PTC power control command are converted into data formats to generate CAN communication data packets, and the CAN communication data packets are sent to the vehicle controller according to the communication protocol. The response signal of the vehicle controller is verified and calculated using a feedback verification algorithm to generate control command execution status data. The deviation analysis between the control command execution status data and the actual operating parameters is performed to correct the optimized pump speed value and the PTC power control command in real time.

6. The vehicle thermal management unit control method for the cabin air conditioning system according to claim 1, characterized in that, The compressor operating current value is obtained based on the compressor reference speed value, the compressor operation control command, and the valve reference opening value. The oil return demand is calculated according to a preset threshold. When the calculated oil return demand exceeds the threshold, the compressor oil return speed value and the electronic expansion valve oil return opening value are output, including: The runtime data in the compressor operation control command is multiplied with the compressor reference speed value to generate the compressor cumulative operation data. The compressor operating current value is collected in real time by a current sampling circuit, and the current characteristic curve is compared with the compressor reference speed value to output the compressor load characteristic value. Based on the compressor's cumulative operating data and the valve's reference opening value, a threshold judgment algorithm is used to calculate the oil return time window and generate an oil return trigger signal. The oil return trigger signal is weighted according to the compressor load characteristic value to obtain the oil return demand calculation result. When the calculated oil return demand exceeds the threshold, the compressor reference speed value is increased 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 for the cabin air conditioning system according to claim 6, characterized in that, The system performs validity checks on the sensor signals in the system's operating state characteristic values. When a sensor failure is detected, parameter interpolation calculations are performed using normal sensor data to generate corrected system operating state characteristic values. Based on these corrected system operating state characteristic values, 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. Simultaneously, fault information is recorded and uploaded to the vehicle system via the CAN bus, including: The effective range of the temperature sensor signal and pressure sensor signal in the characteristic value of the system's working state is verified, and abnormal data is identified by the signal mutation detection algorithm to generate sensor fault flag bits. The sensor failure flag bit and the sensor historical data are analyzed over time to determine the sensor failure type and output sensor failure characteristic data. Based on the sensor failure characteristic data, normal sensor signals are selected, and the state of the missing data is estimated using the Kalman filter algorithm to obtain sensor compensation data. The sensor compensation data is used to reconstruct the system operating state characteristic values ​​to generate the corrected system operating state characteristic values. Based on the operating state characteristic values ​​of the correction system, the compressor speed correction, electronic expansion valve opening correction, water pump speed correction, and PTC power correction are calculated respectively through the compensation control algorithm. 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 corrected and the corrected control command is output. The sensor failure characteristic data and the corrected control commands 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 as described in any one of claims 1-7, characterized in that, The vehicle thermal management unit control system of the cabin air conditioning system includes: The data acquisition module is used to collect data on the battery pack inlet and outlet temperatures, the heating system inlet and outlet temperatures, the evaporator temperature, and the ambient temperature from the energy exchange controller. It combines these data with the user-set temperature from the air conditioning controller and the target temperature requirements from the battery management system. The module performs calculations based on preset temperature priorities to obtain system operating status characteristic values ​​and system operating mode signals. The calculation module is used to calculate the difference between the target battery temperature and the actual 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, using a PID control algorithm, and combined with the compressor minimum running time parameter to generate the compressor reference speed value and compressor operation control command. The compensation module is used to calculate the valve reference opening value based on the compressor reference speed value, the compressor operation control command and the system superheat data through a preset opening algorithm, and to perform compensation calculation on the valve reference opening value based on the high and low pressure sensor data, and output the evaporator electronic expansion valve opening control signal and the electronic expansion valve opening control signal. The control module is used to acquire the operating status signals of the liquid level sensor and the water pump, combine the system operating status characteristic value, the compressor reference speed value and the valve reference opening value, perform safety judgment calculation, generate the water pump speed optimization value and PTC power control command, and send the water pump speed optimization value and PTC power control command to the vehicle controller through the CAN bus; The acquisition module is used to acquire the compressor operating current value based on the compressor reference speed value, the compressor operation control command and the valve reference opening value, calculate the oil return demand according to the preset judgment 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. The correction module is used to determine the validity of each sensor signal in the system operating state characteristic value. When a sensor failure is detected, parameter interpolation calculation is performed using normal sensor data to generate a corrected system operating state characteristic value. Based on the corrected system operating state characteristic value, 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. At the same time, fault information is recorded and uploaded to the vehicle system via the CAN bus.

9. An electronic device, characterized in that, The electronic device includes: 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 described in any one of claims 1 to 7.

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