Control method, device, equipment, medium and product of heat pump air conditioning system

Abstract

The application provides a control method, device, equipment, medium and product of a heat pump air conditioning system, the method comprising: collecting a temperature measured value of a condenser outlet of a heat pump air conditioning system of a target vehicle; obtaining at least one operating state parameter of the heat pump air conditioning system; inputting the at least one operating state parameter into a temperature prediction module to output a temperature predicted value of the condenser outlet; obtaining a diagnosis result of whether a temperature sensor of the condenser outlet is faulty based on the temperature predicted value and the temperature measured value of the condenser outlet; and selecting the temperature predicted value or the temperature measured value to control the heat pump air conditioning system to work based on the diagnosis result, which can effectively avoid the risk of shutdown or loss of control of the heat pump air conditioning system caused by a single sensor fault, and improve the robustness and reliability of the heat pump air conditioning system.

Description

Technical Field

[0001] This application relates to the field of heat pump air conditioning system control technology for vehicles, specifically to a control method, device, equipment, medium, and product for a heat pump air conditioning system. Background Technology

[0002] In vehicle heat pump air conditioning systems, especially in the field of thermal management systems for new energy vehicles, ensuring the stable and reliable operation of the heat pump system under various operating conditions is a core requirement. Among these requirements, accurate sensing of the condenser outlet water temperature is the key basis for the system to achieve efficient cooling, heating, and battery thermal management control.

[0003] Currently, in related technologies, the control of heat pump air conditioning systems typically relies heavily on real-time measurement data provided by a condenser outlet water temperature sensor. The system adjusts key parameters such as compressor speed and loop flow rate based on feedback from this sensor to meet thermal management requirements. However, this approach uses the sensor's measured values ​​as the sole and direct data input source for the control system. When the sensor outputs abnormal data due to malfunction or interference, the control system loses reliable input, potentially leading to inaccurate control commands, affecting system functionality and energy efficiency, and even posing safety hazards.

[0004] Therefore, a prominent problem with existing technologies is that the system cannot maintain safe and stable control based on temperature feedback when the condenser outlet water temperature sensor malfunctions. With increasingly stringent requirements for functional safety and robustness in vehicle thermal management systems, ensuring continuous closed-loop operation of the control loop under sensor failure conditions has become a pressing technical problem. Summary of the Invention

[0005] In view of this, this application aims to provide a control method, device, equipment, medium and product for a heat pump air conditioning system, in order to solve the technical problem in traditional related technologies that the system cannot maintain safe and stable control based on temperature feedback when the condenser outlet water temperature sensor malfunctions.

[0006] The first aspect of this application provides a control method for a heat pump air conditioning system, comprising: The system collects the measured temperature value from the temperature sensor at the condenser outlet of the heat pump air conditioning system of the target vehicle; acquires at least one operating status parameter of the heat pump air conditioning system; inputs the at least one operating status parameter into a temperature prediction module to output a predicted temperature value at the condenser outlet; wherein the temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system, and the temperature prediction model predicts the temperature at the condenser outlet based on the at least one operating status parameter to obtain the predicted temperature value; based on the predicted temperature value and the measured temperature value at the condenser outlet, a diagnostic result is obtained to determine whether the temperature sensor at the condenser outlet is faulty; based on the diagnostic result, the system selects either the predicted temperature value or the measured temperature value to control the heat pump air conditioning system to operate.

[0007] In one possible implementation of this application, the operating modes of the heat pump air conditioning system include: an initialization mode, a non-heat pump operating mode, and a heat pump normal operation mode; wherein the heat pump normal operation mode includes a compressor shutdown sub-mode, a compressor operation sub-mode, and a compressor cut-off sub-mode; determining a temperature prediction model based on the operating modes of the heat pump air conditioning system includes: if the heat pump air conditioning system is detected to be in a first operating mode, then a pre-trained neural network model is used as the temperature prediction model, wherein the first operating mode is the heat pump air conditioning system being in the heat pump normal operation mode and in either the compressor shutdown sub-mode or the compressor operation sub-mode; if the heat pump air conditioning system is detected to be in a second operating mode, then a pre-constructed energy dissipation physical model is used as the temperature prediction model, wherein the second operating mode includes one of the following operating modes: the heat pump air conditioning system is in an initialization mode, the heat pump air conditioning system is in a non-heat pump operating mode, or the heat pump air conditioning system is in the heat pump normal operation mode and in the compressor cut-off sub-mode.

[0008] In one possible implementation of this application, the pre-trained neural network model includes any one of a fully connected neural network, a convolutional neural network, and a long short-term memory network.

[0009] In one possible implementation of this application, when the heat pump air conditioning system is in a non-heat pump operating mode, the energy dissipation physical model serves as the temperature prediction model. The temperature prediction model predicts the temperature of the condenser outlet based on the at least one operating state parameter, including any of the following scenarios: if the heat pump air conditioning system is equipped with a heater, the water temperature at the outlet of the heater is determined as the predicted temperature of the condenser outlet; if the heat pump air conditioning system is not equipped with a heater, and the electric drive and condenser are connected in series to form an electric drive circuit, and the electric drive stall heating is used to provide heat to the passenger compartment, the water temperature of the electric drive circuit is determined as the predicted temperature of the condenser outlet.

[0010] In one possible implementation of this application, it further includes any of the following scenarios: if the air conditioner of the heat pump air conditioning system has heating demand, and the air conditioning circuit and the electric drive circuit merge before entering the condenser, then the predicted temperature value of the condenser outlet is calculated based on the flow rate and outlet water temperature of the air conditioning circuit and the electric drive circuit; if only the electric drive of the heat pump air conditioning system has heat dissipation demand, then the predicted temperature value of the condenser outlet is determined based on the operating mode of the heat pump air conditioning system before heat dissipation, wherein the operating mode of the heat pump air conditioning system before heat dissipation includes cooling mode and heating mode.

[0011] In one possible implementation of this application, when the heat pump air conditioning system is in normal heat pump operation mode and compressor cut-off sub-mode, the energy dissipation physical model serves as the temperature prediction model. The temperature prediction model predicts the temperature of the condenser outlet based on at least one operating state parameter to obtain the predicted temperature value, including: determining the operating mode of the heat pump air conditioning system, wherein the operating mode of the heat pump air conditioning system includes a cooling mode and a heating mode; if the operating mode is a cooling mode, then obtaining a first set of operating state parameters of the heat pump air conditioning system, and obtaining the temperature of the condenser outlet based on the first set of operating state parameters to obtain the predicted temperature value; if the operating mode is a heating mode, then obtaining a second set of operating state parameters of the heat pump air conditioning system, and obtaining the temperature of the condenser outlet based on the second set of operating state parameters to obtain the predicted temperature value.

[0012] In one possible implementation of this application, the step of obtaining a diagnostic result regarding whether the temperature sensor at the condenser outlet is faulty based on the predicted temperature value and the measured temperature value at the condenser outlet includes: continuously monitoring a first temperature difference between the predicted temperature value and the measured temperature value within a set time window; if the first temperature difference is continuously detected to exceed a first preset deviation threshold within the set time window, a preliminary anomaly flag is triggered; in response to the preliminary anomaly flag, an auxiliary temperature parameter is acquired, and a diagnostic result regarding whether the temperature sensor at the condenser outlet is faulty is determined based on the auxiliary temperature parameter, wherein the auxiliary temperature parameter is the temperature collected at the target node in the heat pump air conditioning system.

[0013] In one possible implementation of this application, the step of determining whether the temperature sensor at the condenser outlet is faulty based on the auxiliary temperature parameter includes: determining a second temperature difference between the auxiliary temperature parameter and the predicted temperature value; if the second temperature difference is within a second preset deviation threshold, then a diagnosis result indicating that the temperature sensor at the condenser outlet is not faulty is obtained; if the second temperature difference exceeds the second preset deviation threshold, then a diagnosis result indicating that the temperature sensor at the condenser outlet is faulty is obtained.

[0014] In one possible implementation of this application, the step of controlling the heat pump air conditioning system to operate based on the diagnostic result by selecting the predicted temperature value or the measured temperature value includes: if the diagnostic result indicates that the temperature sensor at the condenser outlet is not faulty, then controlling the heat pump air conditioning system to maintain a first control mode; wherein the first control mode controls the heat pump air conditioning system to operate based on the measured temperature value of the temperature sensor at the condenser outlet; if the diagnostic result indicates that the temperature sensor at the condenser outlet is faulty, then switching the heat pump air conditioning system from the first control mode to a second control mode; wherein the second control mode controls the heat pump air conditioning system to operate based on the temperature predicted value of the temperature prediction module.

[0015] A second aspect of this application provides a control device for a heat pump air conditioning system, comprising: an information acquisition unit for acquiring measured temperature values ​​from a temperature sensor at the condenser outlet of a target vehicle's heat pump air conditioning system, and obtaining at least one operating status parameter of the heat pump air conditioning system; a temperature prediction unit for inputting the at least one operating status parameter into a temperature prediction module to output a predicted temperature value at the condenser outlet; wherein the temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system, and the temperature prediction model predicts the temperature at the condenser outlet based on the at least one operating status parameter to obtain the predicted temperature value; a fault diagnosis unit for obtaining a diagnostic result regarding whether the temperature sensor at the condenser outlet is faulty based on the predicted temperature value and the measured temperature value; and a control unit for selecting either the predicted temperature value or the measured temperature value to control the heat pump air conditioning system to operate based on the diagnostic result.

[0016] A third aspect of this application provides a control device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform a control method for a heat pump air conditioning system as described in the first aspect and possible implementations thereof.

[0017] The fourth aspect of this application provides a computer storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a control method for a heat pump air conditioning system as described in the first aspect and possible implementations thereof.

[0018] The fifth aspect of this application provides a computer program product comprising: a computer program that, when executed by a processor, implements a control method for a heat pump air conditioning system as described in the first aspect and possible implementations of the first aspect.

[0019] The control method, apparatus, equipment, medium, and product for a heat pump air conditioning system provided in this application include the following: The method acquires the measured temperature values ​​from a temperature sensor and generates independent predicted temperature values ​​in parallel based on the system's operating status parameters, creating a virtual backup data source. The sensor status is diagnosed by comparing the measured temperature values ​​with the predicted temperature values, and when a fault is diagnosed, the temperature data source of the control system is seamlessly switched to the predicted temperature value. In the event of a critical sensor failure, a reliable data replacement source is provided for the control system, ensuring the continuous closed loop of the control circuit, maintaining the basic operational capability and safety of the heat pump air conditioning system, effectively avoiding the risk of system shutdown or loss of control due to a single sensor failure, and improving the robustness and reliability of the heat pump air conditioning system. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this application, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating the control method of a heat pump air conditioning system provided in an embodiment of this application.

[0022] Figure 2 This is a schematic diagram illustrating the operating mode principle of a heat pump air conditioning system provided in an embodiment of this application.

[0023] Figure 3 A schematic diagram of the control device for a heat pump air conditioning system provided in an embodiment of this application.

[0024] Figure 4 This is a schematic diagram of the hardware structure of the control device provided in an embodiment of this application. Detailed Implementation

[0025] 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, and 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.

[0026] In vehicle heat pump air conditioning systems, especially for new energy vehicles, to achieve precise control of components such as compressors and water pumps to optimize energy efficiency and meet the thermal management needs of the cabin and battery, real-time temperature feedback is typically provided by a key water temperature sensor installed at the condenser outlet. Specifically, this physical sensor directly measures the coolant temperature at the condenser outlet, and this measured value is used as a core control parameter input into the control algorithm to control the operation of the heat pump air conditioning system.

[0027] However, when this solution is applied to the complex and ever-changing operating environment of actual vehicles, and when the sensors experience latent or explicit faults such as drifting or jamming due to aging, damage, or signal interference, its reliability faces severe challenges.

[0028] To overcome the aforementioned contradictions, this invention proposes a different technical approach. Its core concept lies in establishing a parallel water temperature estimation channel independent of the physical sensor and setting up a consistent monitoring and decision-making mechanism. This reconstructs the critical link of the control system's reliance on a single data source, thereby effectively improving the system's fault tolerance and continuous operational stability under abnormal sensor conditions without sacrificing the requirements for real-time control and accuracy. In other words, it provides a sensor redundancy control method based on multi-source information fusion and fault diagnosis to solve the problem of control system inaccuracy or failure caused by a single water temperature sensor malfunction, achieving the technical effect of safe and stable system operation even under sensor malfunctions.

[0029] Figure 1 This is a flowchart illustrating the control method for a heat pump air conditioning system provided in an embodiment of this application. The executing entity in this embodiment can be a vehicle controller, specifically a vehicle controller, a domain controller, or a dedicated thermal management controller. Figure 1 As shown, the method includes: S101: Collect the measured temperature value of the condenser outlet of the heat pump air conditioning system of the target vehicle.

[0030] In this embodiment, the temperature sensor can be a common type such as a negative temperature coefficient thermistor, thermocouple, or digital temperature sensor. It is installed in the water pipe or on the pipe wall near the condenser outlet to sense the temperature of the coolant flowing through that area. The acquisition process typically includes preprocessing operations such as analog-to-digital conversion of the signal and filtering to suppress high-frequency noise.

[0031] S102: Obtain at least one operating status parameter of the heat pump air conditioning system.

[0032] In this embodiment, the range of operating status parameters can be set to be relatively wide, and the core principle is that they have a physical or empirical correlation with the condenser outlet water temperature.

[0033] For example, the operating status parameters include, but are not limited to, one or more of the following: ambient temperature, actual compressor speed, exhaust temperature, exhaust pressure, suction temperature, suction pressure, electric drive circuit water temperature, heater pump speed, and battery outlet water temperature.

[0034] Understandably, operating status parameters can be obtained by reading directly from the corresponding sensors or by receiving them from other controllers via the controller area network bus.

[0035] In some embodiments, the initial reference values ​​for recording the initial operating state parameters of the vehicle after power-on are selected as follows: historical water temperature data before power-off are recorded, and the parking duration threshold is used to determine whether it is a short parking or a long parking. For long parking, initial boundary conditions are set according to ambient temperature and seasonal characteristics: for example, in summer, the minimum of the outlet water temperature of the electric drive circuit and the saturation temperature corresponding to the high pressure at power-on is taken as the initial reference; in winter, the minimum of the saturation temperature corresponding to the low pressure at power-on and the heater core temperature and ambient temperature is taken as the initial reference.

[0036] It should be noted that, in order to improve the robustness of the subsequent prediction model, further signal processing can be performed on the operating state parameters after obtaining them: such as filtering the compressor speed by its rising / falling rate, the filtering coefficient of which can be determined by looking up a table based on the speed itself; similar rate filtering can be performed on the exhaust pressure; and low-pass filtering can be performed on the ambient temperature and the speed of the heater pump, etc.

[0037] S103: Input at least one operating status parameter into the temperature prediction module to output the predicted temperature value of the condenser outlet; wherein the temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system, and the temperature prediction model predicts the temperature of the condenser outlet based on at least one operating status parameter to obtain the predicted temperature value.

[0038] In this embodiment, the temperature prediction module, as a functional entity, adaptively selects and invokes the corresponding temperature prediction model based on the different operating conditions of the heat pump air conditioning system. These operating conditions reflect different thermodynamic states and energy exchange characteristics of the system.

[0039] In this embodiment, the temperature prediction model is an input-output mapping relationship. It derives an estimated value of the condenser outlet temperature from the input operating state parameters through learning, calculation, or table lookup. This design enables the system to obtain a relatively reliable temperature reference value under various operating scenarios, providing a benchmark for sensor fault diagnosis.

[0040] In this embodiment, the function of determining and applying the temperature prediction model based on the operating condition mode can be implemented in several ways. In one embodiment, a mode judgment circuit can be designed, whose input is a signal characterizing the operating condition (such as a compressor enable signal or a valve position combination signal), and whose output is a control signal for selecting different model calculation chips or storage areas. In another embodiment, the current operating condition mode can be identified by a state machine program running in the controller, and the corresponding algorithm function or model parameter set can be called to perform prediction calculations according to a preset mode-model mapping table.

[0041] S104: Based on the predicted and measured temperatures at the condenser outlet, obtain the diagnostic results regarding whether the temperature sensor at the condenser outlet is faulty.

[0042] In one embodiment, if the measured temperature value is consistent with or deviates within an acceptable range from the predicted temperature value reasonably predicted based on other system states, the temperature sensor is functioning correctly. Conversely, if there is a persistent and significant deviation between the two, the temperature sensor may be malfunctioning.

[0043] In another embodiment, cross-validation of auxiliary signals can be introduced during the diagnostic process to increase the accuracy and reliability of the diagnosis and avoid misjudgments caused by instantaneous model errors or brief system disturbances.

[0044] S105: Based on the diagnostic results, select the predicted temperature value or the measured temperature value to control the operation of the heat pump air conditioning system.

[0045] In one embodiment of this application, if the diagnostic result indicates that the temperature sensor at the condenser outlet is not faulty, the heat pump air conditioning system maintains operation in the first control mode; wherein the first control mode controls the heat pump air conditioning system to operate based on the measured temperature value of the temperature sensor at the condenser outlet; if the diagnostic result indicates that the temperature sensor at the condenser outlet is faulty, the heat pump air conditioning system is switched from the first control mode to the second control mode; wherein the second control mode controls the heat pump air conditioning system to operate based on the temperature prediction value of the temperature prediction module.

[0046] This step enables seamless switching of the control signal source for the heat pump air conditioning system, a crucial step in ensuring continued system operation even after sensor failure. Specifically: if the condenser outlet temperature sensor is functioning correctly, high-fidelity measured values ​​continue to be used for control to maintain optimal performance; if the condenser outlet temperature sensor is diagnosed as faulty, the control signal source is automatically switched to the predicted temperature value, thus maintaining the closed control loop. This allows the heat pump air conditioning system to continue operating in a degraded but safe state, providing basic thermal management functions for the vehicle and preventing a complete system shutdown due to a single sensor failure.

[0047] Among them, the predicted temperature value or the measured temperature value serves as a reference benchmark for controlling key operations of the heat pump air conditioning system, such as compressor speed adjustment and fan start / stop decisions.

[0048] As described above, by acquiring the measured temperature values ​​from the temperature sensors and generating independent temperature prediction values ​​in parallel based on the system's operating status parameters, a virtual backup data source is created. The sensor status is diagnosed by comparing the measured temperature values ​​with the temperature prediction values, and when a fault is diagnosed, the temperature data source of the control system is seamlessly switched to the temperature prediction values. When a critical sensor fails, a reliable data replacement source is provided for the control system, ensuring the continuous closed loop of the control circuit, maintaining the basic operating capability and safety of the heat pump air conditioning system, effectively avoiding the risk of heat pump air conditioning system shutdown or loss of control due to a single sensor failure, and improving the robustness and reliability of the heat pump air conditioning system.

[0049] In one embodiment of this application, a specific process is provided for determining the temperature prediction model based on the operating mode of the heat pump air conditioning system. In an optional embodiment, the operating mode of the heat pump air conditioning system is specifically refined into: initialization mode, non-heat pump operating mode, and heat pump normal operation mode; wherein the heat pump normal operation mode further includes compressor shutdown sub-mode, compressor operation sub-mode, and compressor cut-off sub-mode.

[0050] refer to Figure 2 , Figure 2 A schematic diagram illustrating the operating mode principle of a heat pump air conditioning system provided in an embodiment of this application. (Reference) Figure 2 After the vehicle is powered on, it enters the initialization mode. After initialization, the system requests the heat pump to run. If yes, it continues to enter the normal heat pump operation mode; otherwise, it continues to enter the non-heat pump operation mode. The normal heat pump operation mode and the non-heat pump operation mode can be switched based on the request. In the normal heat pump operation mode, if it is necessary to maintain the current value (the temperature output by the heat pump air conditioning system), the compressor is controlled to stop (compressor stop sub-mode); otherwise, the compressor is controlled to run (compressor run sub-mode). During compressor operation, if a compressor failure is encountered, the system enters the compressor cut-off sub-mode.

[0051] Those skilled in the art will understand that the specific means of realizing operating condition mode recognition can be diverse. For example, the initialization mode can be determined by combining the vehicle power-on signal with the system self-test incomplete flag; the non-heat pump operating mode can be determined by the absence of cooling / heating requests on the air conditioning panel and the system executing other heat dissipation or heating logic (such as battery heating or electric drive cooling only); the various sub-modes of the compressor are directly distinguished by the compressor's control feedback signals (such as zero speed, speed greater than zero speed, fault protection cut-off signal). The pre-trained neural network model and the pre-built energy dissipation physical model can be stored in the controller's non-volatile memory and loaded into memory for execution under the corresponding operating conditions.

[0052] Accordingly, the temperature prediction model is determined based on the operating mode of the heat pump air conditioning system, which can be specifically implemented as follows: Scenario 1: If the heat pump air conditioning system is detected to be in the first operating condition, the pre-trained neural network model will be used as the temperature prediction model. The first operating condition is when the heat pump air conditioning system is in the normal operation mode of the heat pump and in the compressor stop sub-mode or compressor operation sub-mode.

[0053] Scenario 2: If the heat pump air conditioning system is detected to be in the second operating condition, the pre-built energy dissipation physical model will be used as the temperature prediction model. The second operating condition includes one of the following: the heat pump air conditioning system is in the initialization mode, the heat pump air conditioning system is in the non-heat pump operating mode, or the heat pump air conditioning system is in the normal heat pump operating mode and in the compressor cut-off mode.

[0054] In this embodiment, when the heat pump system is operating stably (compressor off or running), there is a complex nonlinear relationship between the system state and the condenser water temperature. Neural network models excel at learning and representing such relationships, providing high-precision predictions. However, under conditions such as system initialization, non-heat pump operation, or sudden compressor shutdown, the system's thermal process often resembles a simple energy dissipation or thermal equilibrium process. Alternatively, the neural network training data may struggle to cover these transient or edge conditions. In these cases, a physical model based on physical rules for energy dissipation is more robust and reasonable. Its advantage lies in its adaptive model switching, ensuring that the most suitable prediction tool is used under different thermodynamically dominant conditions, thereby maintaining high estimation accuracy across the entire operating range.

[0055] As can be seen from the above description, by adaptively selecting different neural network models or energy dissipation physical models as temperature prediction models according to the operating mode of the heat pump air conditioning system, the heat pump air conditioning system can generate accurate temperature prediction values ​​under different operating conditions. This improves the adaptability and accuracy of condenser outlet temperature prediction, enhances the reliability of sensor diagnosis, ensures the effectiveness of control data after switching, and further optimizes the overall performance of the heat pump air conditioning system.

[0056] In one embodiment of this application, the pre-trained neural network model includes any one of a fully connected neural network, a convolutional neural network, and a long short-term memory network.

[0057] It should be noted that fully connected neural networks have a simple structure and are suitable for capturing complex mappings between static features. Convolutional neural networks can effectively handle input data with local correlations. Long Short-Term Memory (LSTM) networks excel at processing time-series data and can utilize historical trends in water temperature to improve the prediction accuracy of the current moment. In practical deployment, the appropriate network type can be selected based on a trade-off between prediction accuracy, computational resource consumption, and real-time requirements. For example, in a controller with limited computational resources, a fully connected neural network with fewer layers might be preferred; while in a solution that pursues extremely high prediction accuracy, an LTM network can be used. These different types of neural network models can all achieve regression prediction functions from operating state parameters to condenser outlet water temperature.

[0058] In the embodiments of this application, at least one operating state parameter input to the pre-trained neural network model includes, but is not limited to: ambient temperature, actual compressor speed, exhaust temperature, suction temperature, exhaust pressure, suction pressure, electric drive water temperature, electric drive water pump speed, heater water pump speed, two-way valve opening, three-way valve opening, bypass valve opening, heater core temperature, evaporator temperature, heater core air volume, battery water pump speed, battery outlet water temperature, refrigerant saturation temperature corresponding to exhaust pressure, and battery inlet water temperature.

[0059] Specifically, the pre-trained neural network model can include a cooling sub-model and a heating sub-model, and can automatically switch between the heating sub-model and the cooling sub-model according to the signal of the working mode output by the heat pump air conditioning system.

[0060] When the heat pump air conditioning system is in cooling mode, a cooling sub-model is used. Its input operating parameters include, but are not limited to: ambient temperature, actual compressor speed, discharge temperature, suction temperature, discharge pressure, suction pressure, electric drive water temperature, electric drive water pump speed, heater core water pump speed, two-way valve opening, three-way valve opening, heater core temperature, evaporator temperature, heater core airflow, and the refrigerant saturation temperature corresponding to the discharge pressure. When the heat pump air conditioning system is in heating mode, a heating sub-model is used. Its input operating parameters include, but are not limited to: actual compressor speed, discharge temperature, suction temperature, discharge pressure, suction pressure, heater core water pump speed, three-way valve opening, bypass valve opening, heater core temperature, evaporator temperature, heater core airflow, battery water pump speed, and battery outlet water temperature.

[0061] In one embodiment of this application, when the heat pump air conditioning system is in non-heat pump operating mode, the energy dissipation physical model serves as the temperature prediction model; the process of obtaining the temperature prediction value by the energy dissipation physical model based on at least one operating state parameter to predict the temperature of the condenser outlet includes any of the following scenarios: Scenario 1: If the heat pump air conditioning system is equipped with a heater, the water temperature at the heater outlet will be determined as the predicted temperature at the condenser outlet.

[0062] Scenario 2: If the heat pump air conditioning system is not equipped with a heater, the electric drive and condenser are connected in series to form an electric drive circuit, and the electric drive stall heating is used to provide heat to the passenger compartment, then the water temperature of the electric drive circuit is determined as the predicted temperature value of the condenser outlet.

[0063] Scenario 3: If the heat pump air conditioning system has heating needs, and the air conditioning circuit and electric drive circuit merge before entering the condenser, the predicted temperature of the condenser outlet can be calculated based on the flow rate and outlet water temperature of the air conditioning circuit and electric drive circuit.

[0064] Scenario 4: If the heat pump air conditioning system only has heat dissipation requirements for the electric drive, then the predicted temperature value of the condenser outlet is determined according to the operating mode of the heat pump air conditioning system before heat dissipation. The operating mode of the heat pump air conditioning system before heat dissipation includes cooling mode and heating mode.

[0065] For scenario 1, if the heat pump air conditioning system is equipped with a heater, such as a PTC heater, then the water temperature at the heater's outlet is determined as the predicted temperature at the condenser's outlet. The principle is that in non-heat pump heating mode, the heater is the main heat source, and its outlet water temperature either passes through the mixing tank or flows directly through the condenser, so the two temperatures are very close.

[0066] For scenario 2, under this specific water circuit connection, the waste heat generated by the electric drive heats the coolant, which flows through the condenser, making the condenser outlet water temperature basically the same as the electric drive circuit water temperature.

[0067] For scenario 3, if the heat pump air conditioning system has heating needs and the air conditioning circuit (such as the circuit through the warm air core) and the electric drive circuit merge before entering the condenser, the predicted temperature of the condenser outlet can be calculated based on the flow rate of the air conditioning circuit and the electric drive circuit and their respective outlet water temperature, according to the energy conservation principle (the total heat after mixing is equal to the sum of the heat of the two circuits before mixing).

[0068] For example, the mixed water temperature (predicted temperature) ≈ (loop 1 flow rate × specific heat capacity × loop 1 water temperature + loop 2 flow rate × specific heat capacity × loop 2 water temperature) / total heat capacity, where loop 1 is the air conditioning loop and loop 2 is the electric drive loop; specific heat capacity is the constant of the coolant; "total heat capacity" actually refers to "total heat capacity ratio", that is, the total heat required for the temperature of the two coolants to change by 1 degree Celsius per unit time, and the unit is kilowatts per degree Celsius (kW / °C).

[0069] For scenario 4, if the heat pump air conditioning system only has heat dissipation requirements for the electric drive (no passenger compartment heating requirements), then the condenser mainly acts as a radiator. In this case, the predicted temperature of the condenser outlet can be determined based on the operating mode of the heat pump air conditioning system before heat dissipation. If the system is in heating mode before heat dissipation, the condenser may contain water at a higher temperature, and its temperature can be estimated by looking up a table based on the ambient temperature. If the system is in cooling mode before heat dissipation, the outlet water temperature of the condenser, acting as a radiator, will be lower than the inlet temperature. A temperature drop value can be obtained by looking up a table based on the electric drive water pump speed and the current water temperature. The initial water temperature is subtracted from this temperature drop value, and the larger value is compared with the electric drive outlet water temperature to take as the predicted value, in order to cope with different heat dissipation intensities. It is understood that the above-mentioned specific methods such as flow calculation and table lookup are only specific implementations of the energy dissipation model in this scenario, and other approximate calculation methods based on physical laws or empirical formulas should also be covered.

[0070] As can be seen from the above description, when the heat pump air conditioning system is in non-heat pump operation mode, the temperature prediction model based on the energy dissipation physics model can accurately and reliably predict the temperature of the condenser outlet under different scenarios, thus providing a high level of scenario applicability of the energy dissipation physics model.

[0071] In one embodiment of this application, when the heat pump air conditioning system is in normal heat pump operation mode and compressor cut-off sub-mode, the energy dissipation physical model serves as the temperature prediction model. Accordingly, the energy dissipation physical model, in processing the prediction of the condenser outlet temperature based on at least one operating state parameter to obtain the temperature prediction value, includes the following steps: S201: Determine the operating mode of the heat pump air conditioning system, which includes cooling mode and heating mode.

[0072] S202: If the working mode is cooling mode, then obtain the first set of operating state parameters of the heat pump air conditioning system, and obtain the temperature prediction value based on the temperature of the condenser outlet based on the first set of operating state parameters.

[0073] In the embodiments of this application, the first set of operating state parameters includes, but is not limited to: current ambient temperature, front-end radiator airflow, and flow rate of each loop.

[0074] In cooling mode, the radiator outlet water temperature can be calculated from the front-end radiator airflow. Combined with the flow rates of the electric-driven water pump, heater pump, three-way valve opening, and two-way valve opening, the flow rates at the electric drive circuit, heater circuit, and two-way valve are calculated. Then, the water temperature at the water-cooled condenser outlet (predicted temperature value) is obtained through energy conservation calculations. Specifically, firstly, by using the front-end cooling fan speed (front-end radiator airflow) and the current ambient temperature, the heat dissipated into the air through the front-end radiator can be estimated. Specifically, this can be done by looking up a preset "airflow-heat dissipation capacity" table or formula. From this, the radiator outlet water temperature (a reduced temperature value) can be calculated. Secondly, the speeds of the electric-driven water pump and heater pump, as well as the openings of the three-way and two-way valves, are obtained. Using this information, the coolant flow rate through each branch of the electric drive circuit and heater circuit can be estimated based on the pump characteristic curves and valve flow curves. Finally, the water flow from the radiator outlet (which has been cooled) and the water flow from heat sources such as electric drive and battery (which may be hotter) are mixed and calculated based on the energy conservation of each flow rate and outlet water temperature estimated in the previous step. The mixed water temperature is the water temperature (predicted temperature value) that flows back to the inlet of the water-cooled condenser.

[0075] S203: If the working mode is heating mode, then obtain the second set of operating state parameters of the heat pump air conditioning system, and obtain the temperature prediction value based on the temperature of the condenser outlet based on the second set of operating state parameters.

[0076] In the embodiments of this application, the second set of operating state parameters includes, but is not limited to: evaporator temperature, heating core air volume and air temperature, battery circuit inlet and outlet water temperature and flow rate, etc.

[0077] In heating mode, the heat dissipated to the passenger compartment can be calculated using evaporator temperature, heater core airflow, and heater core air temperature; the heat dissipated to the battery can be calculated using battery inlet and outlet water temperatures and battery circuit flow rate. The rate of water temperature change is then calculated, and the condenser outlet temperature is determined based on this rate of change to obtain a predicted temperature value. Specifically, firstly, the evaporator temperature (reflecting the ability to absorb heat from the vehicle's interior air, affecting the final heating efficiency), heater core airflow (blower speed), heater core inlet air temperature, and heater core outlet air temperature are collected. Using the specific heat capacity of air, the heat lost from the coolant to the passenger compartment per unit time can be estimated using the formula (airflow × air density × air specific heat capacity × (heater core outlet air temperature - heater core inlet air temperature / evaporator temperature)). Secondly, the water temperature difference between the battery inlet and outlet, the water pump speed and flow rate in the battery cooling circuit are collected. Using the specific heat capacity of water, the heat lost from the coolant to the battery per unit time can be estimated using the formula (flow rate × water specific heat capacity × water temperature difference). Finally, the calculated "heat lost to the passenger compartment" and "heat lost to the battery" are added together to obtain the total heat dissipation. Dividing this total heat dissipation by the total heat capacity of the coolant in the entire thermal management system (total water volume × specific heat capacity of water) yields the current rate of temperature decrease. Based on this rate and the previous reliable water temperature value, the condenser outlet temperature can be calculated to obtain the predicted temperature.

[0078] As can be seen from the above description, when the heat pump air conditioning system is in the normal operation mode of the heat pump and in the compressor cut-off sub-mode, the energy dissipation physical model, as the temperature prediction model, constructs differentiated temperature prediction paths that conform to physical characteristics for the two completely different energy flows of cooling and heating, thereby improving the applicability of the solution.

[0079] In one embodiment of this application, to further improve the reliability of sensor fault diagnosis and avoid false alarms caused by instantaneous errors in the temperature prediction model or noise interference, this application optimizes the diagnostic steps. Specifically, for step S104 above, based on the predicted and measured temperature values ​​at the condenser outlet, a diagnostic result is obtained regarding whether the temperature sensor at the condenser outlet is faulty, including: S141: Within a set time window, continuously monitor the first temperature difference between the predicted temperature value and the measured temperature value.

[0080] In this embodiment, the absolute value of the difference between the predicted temperature value and the measured temperature value is used to obtain the first temperature difference.

[0081] S142: If, within the set time window, the first temperature difference is continuously detected to exceed the first preset deviation threshold, a preliminary abnormality flag is triggered.

[0082] In this embodiment, the set time window can be configured according to requirements. Optionally, the set time window is 30 seconds.

[0083] The first preset deviation threshold can also be set according to requirements. Optionally, the first preset deviation threshold is 2°C.

[0084] S143: In response to the initial anomaly flag, acquire auxiliary temperature parameters and determine the diagnostic result of whether the temperature sensor at the condenser outlet is faulty based on the auxiliary temperature parameters, wherein the auxiliary temperature parameters are the temperature at the target node of the heat pump air conditioning system.

[0085] Specifically, a second temperature difference between the auxiliary temperature parameter and the predicted temperature value is determined; if the second temperature difference is within a second preset deviation threshold, a diagnosis result indicating that the temperature sensor at the condenser outlet is not faulty is obtained; if the second temperature difference exceeds the second preset deviation threshold, a diagnosis result indicating that the temperature sensor at the condenser outlet is faulty is obtained.

[0086] In this embodiment, when the water circuit of the heat pump air conditioning system is connected to the electric drive or heater, and the heat pump system has not been running for a long time, it is assumed that the temperatures of the three are relatively close. Therefore, the target nodes in the heat pump air conditioning system can be the electric drive circuit and the heater inlet. Accordingly, the auxiliary temperature parameters are the water temperature of the electric drive circuit and / or the temperature of the heater inlet.

[0087] It should be noted that the second preset deviation threshold can be set according to requirements. Optionally, the first preset deviation threshold is 2°C or 3°C.

[0088] In one embodiment, when a diagnosis result indicating that the temperature sensor at the condenser outlet is not faulty is obtained, the preliminary abnormality flag in step S142 is removed.

[0089] As can be seen from the above description, by introducing a delayed judgment mechanism (a delayed time window for continuous monitoring of deviation) and auxiliary temperature parameters (such as water temperature in the electric drive circuit), transient interference and algorithm-induced errors in the temperature prediction model can be filtered out, thereby significantly improving the accuracy and robustness of temperature sensor fault diagnosis, avoiding unnecessary switching caused by misdiagnosis, and ensuring the stability of control decisions.

[0090] Figure 3 This is a schematic diagram of the control device for a heat pump air conditioning system provided in an embodiment of this application. The control device for the heat pump air conditioning system includes: an information acquisition unit 301, a temperature prediction unit 302, a fault diagnosis unit 303, and a control unit 304.

[0091] The information acquisition unit 301 is used to acquire the measured temperature value of the condenser outlet of the heat pump air conditioning system of the target vehicle by the temperature sensor; and to obtain at least one operating status parameter of the heat pump air conditioning system.

[0092] Temperature prediction unit 302 is used to input the at least one operating status parameter into the temperature prediction module to output the temperature prediction value of the condenser outlet; wherein the temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system, and the temperature prediction model predicts the temperature of the condenser outlet based on the at least one operating status parameter to obtain the temperature prediction value.

[0093] The fault diagnosis unit 303 is used to obtain a diagnosis result on whether the temperature sensor at the condenser outlet is faulty based on the predicted temperature value and the measured temperature value at the condenser outlet.

[0094] Control unit 304 is used to select the predicted temperature value or the measured temperature value based on the diagnostic results to control the heat pump air conditioning system to operate.

[0095] In one possible implementation of this application, the operating modes of the heat pump air conditioning system include: an initialization mode, a non-heat pump operating mode, and a heat pump normal operation mode; wherein the heat pump normal operation mode includes a compressor shutdown sub-mode, a compressor operation sub-mode, and a compressor cut-off sub-mode; determining the temperature prediction model based on the operating modes of the heat pump air conditioning system includes: if the heat pump air conditioning system is detected to be in a first operating mode, then using a pre-trained neural network model as the temperature prediction model, wherein the first operating mode is the heat pump air conditioning system being in the heat pump normal operation mode and in either the compressor shutdown sub-mode or the compressor operation sub-mode; if the heat pump air conditioning system is detected to be in a second operating mode, then using a pre-constructed energy dissipation physical model as the temperature prediction model, wherein the second operating mode includes one of the following operating modes: the heat pump air conditioning system being in an initialization mode, the heat pump air conditioning system being in a non-heat pump operating mode, or the heat pump air conditioning system being in the heat pump normal operation mode and in the compressor cut-off sub-mode.

[0096] In one possible implementation of this application, the pre-trained neural network model includes any one of a fully connected neural network, a convolutional neural network, and a long short-term memory network.

[0097] In one possible implementation of this application, when the heat pump air conditioning system is in a non-heat pump operating mode, the energy dissipation physical model serves as the temperature prediction model. The temperature prediction model predicts the temperature of the condenser outlet based on the at least one operating state parameter, including any of the following scenarios: if the heat pump air conditioning system is equipped with a heater, the water temperature at the outlet of the heater is determined as the predicted temperature of the condenser outlet; if the heat pump air conditioning system is not equipped with a heater, and the electric drive and condenser are connected in series to form an electric drive circuit, and the electric drive stall heating is used to provide heat to the passenger compartment, the water temperature of the electric drive circuit is determined as the predicted temperature of the condenser outlet.

[0098] In one possible implementation of this application, it further includes any of the following scenarios: if the air conditioner of the heat pump air conditioning system has heating demand, and the air conditioning circuit and the electric drive circuit merge before entering the condenser, then the predicted temperature value of the condenser outlet is calculated based on the flow rate and outlet water temperature of the air conditioning circuit and the electric drive circuit; if only the electric drive of the heat pump air conditioning system has heat dissipation demand, then the predicted temperature value of the condenser outlet is determined based on the operating mode of the heat pump air conditioning system before heat dissipation, wherein the operating mode of the heat pump air conditioning system before heat dissipation includes cooling mode and heating mode.

[0099] In one possible implementation of this application, when the heat pump air conditioning system is in normal heat pump operation mode and compressor cut-off sub-mode, the energy dissipation physical model serves as the temperature prediction model. The temperature prediction model predicts the temperature of the condenser outlet based on at least one operating state parameter to obtain the predicted temperature value, including: determining the operating mode of the heat pump air conditioning system, wherein the operating mode of the heat pump air conditioning system includes a cooling mode and a heating mode; if the operating mode is a cooling mode, then obtaining a first set of operating state parameters of the heat pump air conditioning system, and obtaining the temperature of the condenser outlet based on the first set of operating state parameters to obtain the predicted temperature value; if the operating mode is a heating mode, then obtaining a second set of operating state parameters of the heat pump air conditioning system, and obtaining the temperature of the condenser outlet based on the second set of operating state parameters to obtain the predicted temperature value.

[0100] In one possible implementation of this application, the step of obtaining a diagnostic result regarding whether the temperature sensor at the condenser outlet is faulty based on the predicted temperature value and the measured temperature value at the condenser outlet includes: continuously monitoring a first temperature difference between the predicted temperature value and the measured temperature value within a set time window; if the first temperature difference is continuously detected to exceed a first preset deviation threshold within the set time window, a preliminary anomaly flag is triggered; in response to the preliminary anomaly flag, an auxiliary temperature parameter is acquired, and a diagnostic result regarding whether the temperature sensor at the condenser outlet is faulty is determined based on the auxiliary temperature parameter, wherein the auxiliary temperature parameter is the temperature collected at the target node in the heat pump air conditioning system.

[0101] In one possible implementation of this application, the step of determining whether the temperature sensor at the condenser outlet is faulty based on the auxiliary temperature parameter includes: determining a second temperature difference between the auxiliary temperature parameter and the predicted temperature value; if the second temperature difference is within a second preset deviation threshold, then a diagnosis result indicating that the temperature sensor at the condenser outlet is not faulty is obtained; if the second temperature difference exceeds the second preset deviation threshold, then a diagnosis result indicating that the temperature sensor at the condenser outlet is faulty is obtained.

[0102] In one possible implementation of this application, the step of controlling the heat pump air conditioning system to operate based on the diagnostic result by selecting the predicted temperature value or the measured temperature value includes: if the diagnostic result indicates that the temperature sensor at the condenser outlet is not faulty, then controlling the heat pump air conditioning system to maintain a first control mode; wherein the first control mode controls the heat pump air conditioning system to operate based on the measured temperature value of the temperature sensor at the condenser outlet; if the diagnostic result indicates that the temperature sensor at the condenser outlet is faulty, then switching the heat pump air conditioning system from the first control mode to a second control mode; wherein the second control mode controls the heat pump air conditioning system to operate based on the temperature predicted value of the temperature prediction module.

[0103] The apparatus provided in this application embodiment can be used to execute the technical solutions of the above method embodiments. Its implementation principle and technical effect are similar, and will not be repeated here.

[0104] Figure 4 This is a schematic diagram of the hardware structure of the control device provided in an embodiment of this application. Figure 4 As shown, the control device in this embodiment includes a processor 401 and a memory 402.

[0105] The memory 402 stores computer-executed instructions; the processor 401 executes the computer-executed instructions stored in the memory to implement the various steps performed by the control device in the above embodiments. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0106] Alternatively, the memory 402 can be either standalone or integrated with the processor 401.

[0107] When the memory 402 is set up independently, the control device also includes a bus 403 for connecting the memory 402 and the processor 401.

[0108] This application also provides a vehicle, which includes a vehicle body and is equipped with the aforementioned controller, which is used to execute the aforementioned control method for a heat pump air conditioning system.

[0109] This application also provides a computer storage medium storing computer execution instructions. When the processor executes the computer execution instructions, the control method of the heat pump air conditioning system described above is implemented.

[0110] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described control method for a heat pump air conditioning system.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0112] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0113] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0114] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0115] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0116] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0117] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0118] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0119] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in a control device or host device.

[0120] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A control method for a heat pump air conditioning system, characterized in that, include: Collect the actual temperature values ​​measured by the temperature sensor at the condenser outlet of the target vehicle's heat pump air conditioning system; Obtain at least one operating status parameter of the heat pump air conditioning system; The at least one operating status parameter is input into the temperature prediction module to output the predicted temperature value of the condenser outlet. The temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system. The temperature prediction model predicts the temperature of the condenser outlet based on the at least one operating state parameter to obtain the temperature prediction value. Based on the predicted temperature value and the measured temperature value at the condenser outlet, a diagnostic result is obtained regarding whether the temperature sensor at the condenser outlet is faulty. Based on the diagnostic results, the heat pump air conditioning system is controlled to operate by selecting either the predicted temperature value or the measured temperature value.

2. The method according to claim 1, characterized in that, The operating modes of the heat pump air conditioning system include: initialization mode, non-heat pump operating mode, and normal heat pump operation mode; wherein the normal heat pump operation mode includes compressor shutdown sub-mode, compressor operation sub-mode, and compressor cut-off sub-mode; the temperature prediction model is determined based on the operating modes of the heat pump air conditioning system, including: If the heat pump air conditioning system is detected to be in the first operating condition, the pre-trained neural network model is used as the temperature prediction model, wherein the first operating condition is that the heat pump air conditioning system is in the heat pump normal operation mode and in the compressor stop sub-mode or compressor operation sub-mode. If the heat pump air conditioning system is detected to be in the second operating condition, the pre-built energy dissipation physical model is used as the temperature prediction model, wherein the second operating condition includes one of the following: the heat pump air conditioning system is in the initialization mode, the heat pump air conditioning system is in the non-heat pump operating mode, and the heat pump air conditioning system is in the normal heat pump operating mode and in the compressor cut-off mode.

3. The method according to claim 2, characterized in that, The pre-trained neural network model mentioned therein includes any one of fully connected neural networks, convolutional neural networks, and long short-term memory networks.

4. The method according to claim 2, characterized in that, When the heat pump air conditioning system is in non-heat pump operating mode, the energy dissipation physical model is used as the temperature prediction model. The temperature prediction model predicts the temperature at the condenser outlet based on at least one operating state parameter to obtain the predicted temperature value, including any of the following scenarios: If the heat pump air conditioning system is equipped with a heater, the water temperature at the outlet of the heater is determined as the predicted temperature at the outlet of the condenser. If the heat pump air conditioning system is not equipped with a heater, and the electric drive and condenser are connected in series to form an electric drive circuit, and the electric drive stall heating is used to provide heat to the passenger compartment, then the water temperature of the electric drive circuit is determined as the predicted temperature value of the condenser outlet.

5. The method according to claim 4, characterized in that, This also includes any of the following scenarios: If the air conditioner of the heat pump air conditioning system has heating demand, and the air conditioning circuit and the electric drive circuit merge before entering the condenser, then the predicted temperature of the condenser outlet is calculated based on the flow rate and outlet water temperature of the air conditioning circuit and the electric drive circuit. If the heat pump air conditioning system only has a heat dissipation requirement for the electric drive, then the predicted temperature value of the condenser outlet is determined according to the operating mode of the heat pump air conditioning system before heat dissipation, wherein the operating mode of the heat pump air conditioning system before heat dissipation includes cooling mode and heating mode.

6. The method according to claim 2, characterized in that, When the heat pump air conditioning system is in normal heat pump operation mode and in compressor cut-off mode, the energy dissipation physical model is used as the temperature prediction model. The temperature prediction model obtains the predicted temperature value by predicting the temperature at the condenser outlet based on the at least one operating state parameter, including: Determine the operating mode of the heat pump air conditioning system, wherein the operating mode of the heat pump air conditioning system includes a cooling mode and a heating mode; If the working mode is a cooling mode, then the first set of operating state parameters of the heat pump air conditioning system is obtained, and the temperature prediction value is obtained based on the first set of operating state parameters and the temperature of the condenser outlet. If the operating mode is heating mode, then the second set of operating status parameters of the heat pump air conditioning system is obtained, and the temperature prediction value is obtained based on the temperature of the condenser outlet.

7. The method according to any one of claims 1 to 6, characterized in that, The diagnostic result for whether the temperature sensor at the condenser outlet is faulty, based on the predicted temperature value and the measured temperature value at the condenser outlet, includes: Within a set time window, continuously monitor the first temperature difference between the predicted temperature value and the measured temperature value; If, within the set time window, the first temperature difference is continuously detected to exceed the first preset deviation threshold, a preliminary anomaly flag is triggered. In response to the initial anomaly flag, auxiliary temperature parameters are acquired, and a diagnostic result is determined based on the auxiliary temperature parameters to determine whether the temperature sensor at the condenser outlet is faulty, wherein the auxiliary temperature parameters are the temperature collected at the target node of the heat pump air conditioning system.

8. The method according to claim 7, characterized in that, The diagnostic results for determining whether the temperature sensor at the condenser outlet is faulty based on auxiliary temperature parameters include: Determine a second temperature difference between the auxiliary temperature parameter and the predicted temperature value; If the second temperature difference is within the second preset deviation threshold, the diagnosis result is that the temperature sensor at the condenser outlet is not faulty. If the second temperature difference exceeds the second preset deviation threshold, a diagnosis result is obtained that the temperature sensor at the condenser outlet is faulty.

9. The method according to any one of claims 1 to 6, characterized in that, The step of selecting the predicted temperature value or the measured temperature value to control the heat pump air conditioning system based on the diagnostic results includes: If the diagnostic result indicates that the temperature sensor at the condenser outlet is not faulty, then the heat pump air conditioning system is controlled to maintain operation in the first control mode; wherein the first control mode is based on the measured temperature value of the temperature sensor at the condenser outlet to control the heat pump air conditioning system to operate. If the diagnostic result indicates that the temperature sensor at the condenser outlet is faulty, the heat pump air conditioning system is switched from the first control mode to the second control mode; wherein the second control mode controls the heat pump air conditioning system to operate based on the temperature prediction value of the temperature prediction module.

10. A control device for a heat pump air conditioning system, characterized in that, include: The information acquisition unit is used to acquire the measured temperature value of the condenser outlet of the heat pump air conditioning system of the target vehicle by the temperature sensor, and to obtain at least one operating status parameter of the heat pump air conditioning system. A temperature prediction unit is used to input the at least one operating status parameter into the temperature prediction module to output the predicted temperature value of the condenser outlet. The temperature prediction module is equipped with a temperature prediction model determined according to the operating mode of the heat pump air conditioning system. The temperature prediction model predicts the temperature of the condenser outlet based on the at least one operating state parameter to obtain the temperature prediction value. The fault diagnosis unit is used to obtain a diagnostic result on whether the temperature sensor at the condenser outlet is faulty based on the predicted temperature value and the measured temperature value at the condenser outlet. The control unit is used to select the predicted temperature value or the measured temperature value based on the diagnostic results to control the heat pump air conditioning system to operate.

11. A control device, characterized in that, include: At least one processor; The system includes a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the control method of the heat pump air conditioning system according to any one of claims 1 to 9.

12. A computer storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the control method of the heat pump air conditioning system as described in any one of claims 1 to 9.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the control method of the heat pump air conditioning system according to any one of claims 1 to 9.

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