A co2 transcritical rail vehicle air conditioning heat pump system and a control method thereof

Abstract

The application provides a CO2 transcritical rail vehicle air conditioner heat pump system and a control method thereof, and belongs to the technical field of rail vehicle air conditioner control. The control method comprises the following steps: acquiring heat pump system parameter data and vehicle running state data, and determining a vehicle condition mode according to the vehicle running state data; generating a high-pressure side pressure set value through a preset adaptive heat pump control model according to the determined vehicle condition mode and the heat pump system parameter data; calculating an electronic expansion valve opening degree value according to the generated pressure set value; adjusting the speed of a variable frequency compressor through PID closed-loop control according to the generated pressure set value, and adjusting the opening degree of the electronic expansion valve according to the calculated expansion valve opening degree value. The CO2 transcritical rail vehicle air conditioner heat pump control method provided by the application effectively improves the energy efficiency of the heat pump system and greatly improves the adaptability of the heat pump system.

Description

Technical Field

[0001] This invention relates to the field of air conditioning control technology for rail vehicles, and specifically to a CO2 transcritical rail vehicle air conditioning heat pump system and its control method. Background Technology

[0002] The air conditioning heat pump system of rail vehicles is a core component ensuring passenger comfort and safe equipment operation. The CO2 transcritical cycle system, in particular, has become the mainstream technology due to its environmental friendliness and high energy efficiency. Traditional control methods control cooling capacity by setting preset pressure setpoints and expansion valve opening rules, combined with PID control to adjust compressor speed. This method relies on engineers' experience to set parameters and can maintain operation under steady-state conditions. However, when faced with dynamic scenarios unique to rail vehicles (such as frequent starts and stops, passenger flow fluctuations, and tunnel-to-platform environment switching), redundant design or manual intervention is necessary to prevent system instability.

[0003] Traditional rail vehicle air conditioning heat pump systems mostly adopt control strategies based on fixed rules or PID. Rail vehicle operating scenarios are complex and changeable, and fixed parameter strategies are difficult to adapt to dynamic heat load demands in real time, which can easily lead to low energy efficiency ratio and fluctuating car temperature. Existing control methods do not deeply integrate vehicle operating status data (such as door opening and closing frequency and passenger density), and cannot predict sudden load changes. During peak hours or under extreme conditions, this can easily lead to problems such as frequent compressor start-stop and high-pressure side pressure overshoot. Summary of the Invention

[0004] This invention provides a CO2 transcritical rail vehicle air conditioning heat pump system and its control method to solve the problems of poor dynamic scenario adaptability and low energy efficiency in the prior art.

[0005] To achieve the above objectives, one embodiment of the present invention provides a method for controlling the air conditioning heat pump of a CO2 transcritical rail vehicle. The method includes: acquiring heat pump system parameter data and vehicle operating status data; determining a vehicle condition mode based on the vehicle operating status data; generating a high-pressure side pressure setpoint using a preset adaptive heat pump control model based on the determined vehicle condition mode and the heat pump system parameter data; calculating the opening value of an electronic expansion valve based on the generated pressure setpoint; adjusting the speed of the variable frequency compressor using PID closed-loop control based on the generated pressure setpoint; and adjusting the opening of the electronic expansion valve based on the calculated expansion valve opening value.

[0006] Optionally, the heat pump system parameters include high-pressure side pressure, evaporation temperature, gas cooler outlet temperature, and compressor speed, and the vehicle operating status data includes door opening and closing frequency, passenger density, geographical location, and power supply mode.

[0007] Optionally, the adaptive heat pump control model is constructed based on a lightweight near-end strategy optimization algorithm and is equipped with an LSTM module. The step of generating a high-pressure side pressure setpoint based on the determined vehicle condition mode and the heat pump system parameter data through a preset adaptive heat pump control model includes: constructing a state vector of the heat pump system based on the heat pump system parameter data; encoding the vehicle condition mode as an independent feature and fusing the state vector; predicting the heat load demand and generating a pressure adjustment amount through an LSTM module based on the fused state vector; and calculating the pressure setpoint based on the generated pressure adjustment amount and a preset pressure threshold.

[0008] Optionally, the step of calculating the electronic expansion valve opening value based on the generated pressure setpoint includes: determining a basic adjustment amount for the electronic expansion valve opening based on the deviation between the pressure setpoint and the current high-pressure side pressure; correcting the basic adjustment amount based on the evaporator superheat; calculating a vibration compensation amount based on a preset vibration compensation mechanism; and calculating the electronic expansion valve opening value based on the vibration compensation amount and the corrected basic adjustment amount.

[0009] Optionally, the step of calculating the vibration compensation amount according to the preset vibration compensation mechanism includes: embedding the historical electronic expansion valve opening adjustment sequence into the state vector to generate a new state vector; and, based on the generated new state vector, learning the law of electronic expansion valve response hysteresis under vibration environment through the adaptive heat pump control model, and generating the vibration compensation amount.

[0010] Optionally, determining the vehicle condition mode based on the vehicle operating status data includes: switching the vehicle condition mode to energy-saving mode when the power supply mode is regenerative braking mode and the geographical location is a platform area; switching the vehicle condition mode to sudden load mode when the door opening and closing frequency is detected to be greater than a preset frequency, or the passenger density is greater than a preset density value; switching the vehicle condition mode to energy-saving mode when the vehicle operating status data simultaneously meets both energy-saving mode and sudden load mode; otherwise, switching the vehicle condition mode to normal mode.

[0011] Optionally, the CO2 transcritical rail vehicle air conditioning heat pump control method further includes: when the door opening and closing frequency is detected to be greater than a preset frequency, expanding the adjustment range of the pressure setting value; when the passenger density is greater than a preset density value, expanding the adjustment range of the electronic expansion valve opening value; when the geographical location is a tunnel, switching the vehicle condition mode to the normal mode and limiting the adjustment range of the pressure setting value.

[0012] Optionally, the training process of the adaptive heat pump control model adopts a multi-objective reward function, and the weights in the multi-objective reward function are adjusted according to the vehicle operating status data and the vehicle condition mode. The adjustment of the weights in the multi-objective reward function includes: when the door opening and closing frequency is detected to exceed the preset frequency, the weight of the compressor power over-limit penalty term is increased to strengthen the priority of temperature stability; when the vehicle is in regenerative braking mode, the weight of the real-time energy efficiency ratio is increased to prioritize improving the energy efficiency ratio.

[0013] Optionally, the CO2 transcritical rail vehicle air conditioning heat pump control method further includes: triggering a defrost command when the outlet temperature of the gas cooler is lower than the dew point temperature and the duration exceeds a preset time; outputting a bypass valve opening command through the adaptive heat pump control model according to the defrost command; adjusting the bypass valve opening according to the output opening command to directionally introduce the exhaust heat of the variable frequency compressor into the gas cooler.

[0014] On the other hand, the present invention also provides a CO2 transcritical rail vehicle air conditioning heat pump system to implement the above-mentioned CO2 transcritical rail vehicle air conditioning heat pump control method. The CO2 transcritical rail vehicle air conditioning heat pump system includes: a variable frequency compressor, an electronic expansion valve, a gas cooler, a bypass valve, a sensor network, and an on-board edge controller. The on-board edge controller is equipped with a multi-source data fusion module and an adaptive heat pump regulation model. The on-board edge controller is used to generate a high-pressure side pressure setpoint and an electronic expansion valve opening value through the adaptive heat pump regulation model, and to adjust the variable frequency compressor and the electronic expansion valve according to the generated high-pressure side pressure setpoint and electronic expansion valve opening value.

[0015] This invention provides a CO2 transcritical rail vehicle air conditioning heat pump system and its control method. By integrating an adaptive heat pump regulation model and multi-source data fusion technology, it significantly improves the overall performance of the CO2 transcritical rail vehicle air conditioning heat pump system. It can dynamically adjust the pressure setpoint and expansion valve opening based on the vehicle condition mode to achieve high stability control of the car temperature fluctuation. By optimizing the collaborative efficiency of the compressor and expansion valve through a lightweight reinforcement learning model (PPO+LSTM), the energy efficiency ratio (COP) is effectively improved. The innovative vibration compensation mechanism combined with anti-vibration hardware design effectively reduces the control accuracy error of the expansion valve and effectively copes with random track vibration interference. At the same time, the system integrates multi-objective optimization, geographical environment perception and intelligent defrosting functions, taking into account energy efficiency, safety and adaptability to extreme operating conditions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0017] Figure 1 This is a flowchart of the CO2 transcritical rail vehicle air conditioning heat pump control method provided in an embodiment of the present invention;

[0018] Figure 2 This is an architecture diagram of the adaptive heat pump control model provided in an embodiment of the present invention;

[0019] Figure 3 This is a diagram of the vibration compensation mechanism provided in an embodiment of the present invention;

[0020] Figure 4 This is a defrosting control flowchart provided in an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the CO2 transcritical rail vehicle air conditioning heat pump system provided in an embodiment of the present invention. Detailed Implementation

[0022] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0023] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0024] The air conditioning heat pump system in rail vehicles is a core component ensuring passenger comfort and safe equipment operation. Faced with the unique dynamic scenarios of rail vehicles, redundant design or manual intervention is necessary to prevent system instability. Existing technologies have attempted to introduce fuzzy control or simple feedback mechanisms, but the core logic remains limited to local parameter adjustment, failing to achieve multi-source data fusion and global optimization. Therefore, developing a more effective air conditioning heat pump control method is crucial.

[0025] To address this problem, this invention provides a CO2 transcritical rail vehicle air conditioning heat pump system and its control method. It achieves precise control through multi-source data fusion and a dynamic decision-making mechanism. Vehicle operating status data is incorporated to provide scenario-based decision-making basis for generating pressure setpoints and expansion valve openings. Simultaneously, an innovative vibration compensation mechanism and multi-objective reward function are embedded to ensure stable execution of control commands in complex vibration environments, balancing multiple objectives such as energy efficiency, temperature stability, and power limitation. Compared to traditional methods, this invention significantly improves the response speed, anti-interference capability, and overall energy efficiency of rail vehicle air conditioning systems in dynamic scenarios.

[0026] The CO2 transcritical cycle is a highly efficient thermodynamic cycle using carbon dioxide (R744) as a refrigerant. Its core characteristic lies in the refrigerant crossing a critical point (critical temperature 31.1℃, critical pressure 7.38MPa) during the cycle. In this cycle, CO2 exchanges heat with ambient air in a supercritical fluid state (pressure > 7.38MPa, temperature > 31.1℃) in a gas cooler, without undergoing the condensation phase change of traditional refrigerants. Instead, heat transfer is achieved through continuous changes in pressure and temperature. Subsequently, the high-pressure CO2 is throttled down to a subcritical state through an expansion valve, enters the evaporator to absorb heat, and completes the refrigeration cycle. This technology, with CO2's natural environmental friendliness (ODP = 0, GWP = 1), high volumetric refrigeration capacity (3-5 times higher than Freon), and excellent adaptability to high-temperature environments, has become an ideal solution for fields such as rail transportation and heat pump heating. However, its high-pressure operating characteristics (8-12MPa) and dynamic control requirements also bring technical challenges to system design and energy efficiency optimization.

[0027] The following is combined Figures 1 to 5 This invention is described in detail.

[0028] This invention provides a CO2 transcritical rail vehicle air conditioning heat pump system, which includes: a variable frequency compressor, an electronic expansion valve, a gas cooler, a bypass valve, a sensor network, and an on-board edge controller. The on-board edge controller is equipped with a multi-source data fusion module and an adaptive heat pump control model. The on-board edge controller is used to generate a high-pressure side pressure setpoint and an electronic expansion valve opening value through the adaptive heat pump control model, and to adjust the variable frequency compressor and the electronic expansion valve according to the generated high-pressure side pressure setpoint and electronic expansion valve opening value.

[0029] like Figure 5As shown, specifically, the sensor network includes: pressure sensors installed at the compressor outlet and evaporator inlet, a temperature sensor installed at the gas cooler outlet, Hall effect sensors installed in the doors, and cameras. The onboard edge controller acquires vehicle data through the sensor network, synchronizes it with heat pump parameters, and constructs a state vector. It then outputs the pressure setpoint and electronic expansion valve opening value through an adaptive heat pump control model. The variable frequency compressor tracks the pressure setpoint through a PID controller, and the electronic expansion valve adjusts itself according to its opening value, using a PWM signal to drive a stepper motor to adjust the opening. In defrost mode, the bypass valve adjusts according to the opening command.

[0030] This invention also provides a CO2 transcritical rail vehicle air conditioning heat pump control method, applied to the aforementioned heat pump system, such as... Figure 1 As shown, the control method for the CO2 transcritical rail vehicle air conditioning heat pump system includes:

[0031] S101: Obtain heat pump system parameter data and vehicle operating status data, and determine the vehicle condition mode based on the vehicle operating status data;

[0032] S102: Based on the determined vehicle condition mode and the heat pump system parameter data, a high-pressure side pressure setpoint is generated through a preset adaptive heat pump control model.

[0033] S103: Calculate the opening value of the electronic expansion valve based on the generated pressure setpoint;

[0034] S104: Based on the generated pressure setpoint, the speed of the variable frequency compressor is adjusted through PID closed-loop control, and the opening of the electronic expansion valve is adjusted according to the calculated expansion valve opening value.

[0035] Preferably, the heat pump system parameters include high-pressure side pressure, evaporation temperature, gas cooler outlet temperature, and compressor speed, and the vehicle operating status data includes door opening and closing frequency, passenger density, geographical location, and power supply mode.

[0036] This invention provides a CO2 transcritical rail vehicle air conditioning heat pump control method, constructing a scientific and efficient system operation and regulation mechanism. First, by comprehensively collecting heat pump system parameter data, such as high-pressure side pressure and evaporation temperature—key data reflecting the system's internal operating state—as well as vehicle operating status data, such as door opening and closing frequency and passenger density—data closely related to the vehicle's actual usage scenarios, a rich and accurate information foundation is provided for subsequent control decisions. Next, based on the acquired vehicle operating status data, the vehicle condition mode is accurately determined. For example, when in regenerative braking mode and in a platform area, it can be identified as an energy-saving mode, while when door opening and closing is frequent or passenger density is high, it switches to a sudden load mode. Subsequently, using a preset adaptive heat pump regulation model, the determined vehicle condition mode is combined with the heat pump system parameter data. Through complex calculations and analysis, a high-pressure side pressure setpoint that meets the current operating conditions is generated. Finally, based on this pressure setpoint, on the one hand, a PID closed-loop control algorithm is used to dynamically adjust the speed of the variable frequency compressor to ensure that the system pressure remains stable near the setpoint; on the other hand, the opening value of the electronic expansion valve is calculated through a series of calculations, and the opening of the electronic expansion valve is adjusted accordingly, thereby achieving precise control of the refrigerant flow. Through this complete control process, the air conditioning heat pump system can intelligently and accurately adapt to different operating conditions, effectively optimize system performance, and improve energy efficiency and the comfort of the in-vehicle environment.

[0037] Preferred, such as Figure 2 As shown, the adaptive heat pump control model is constructed based on a lightweight near-end strategy optimization algorithm and is equipped with an LSTM module. The step of generating a high-pressure side pressure setpoint based on the determined vehicle condition mode and the heat pump system parameter data, through a preset adaptive heat pump control model, includes: constructing a state vector of the heat pump system based on the heat pump system parameter data; encoding the vehicle condition mode as an independent feature and fusing the state vector; predicting the heat load demand and generating a pressure adjustment amount through the fused state vector using the LSTM module; and calculating the pressure setpoint based on the generated pressure adjustment amount and a preset pressure threshold.

[0038] In a preferred embodiment of the present invention, the construction of the adaptive heat pump control model utilizes a lightweight near-end strategy optimization algorithm. This algorithm can optimize the model efficiently, reducing computational resource consumption while ensuring the model's convergence speed and performance. It is particularly suitable for rail vehicle air conditioning systems with strict requirements for real-time performance and resource consumption. LSTM (Long Short-Term Memory) networks have powerful sequential data processing capabilities and can capture long-term dependencies in data, which is crucial for accurately predicting heat load demand, as heat load is affected by various factors at different time scales. In the step of generating the high-pressure side pressure setpoint, the state vector of the heat pump system is first constructed based on the acquired heat pump system parameter data. The state vector S t It can be represented as:

[0039] S t =[P high ,T gc N comp (1)

[0040] Among them, P high T represents the high-pressure side pressure. gc Indicates the outlet temperature of the gas cooler, N comp The compressor speed is represented by this state vector. This state vector provides a comprehensive quantitative representation of the system's current operating state, laying the foundation for subsequent calculations and predictions. Subsequently, vehicle condition modes (such as energy-saving mode and sudden load mode) are encoded as independent features and fused with the state vector. This approach incorporates external operating condition information into the state representation, enabling the model to more comprehensively consider the impact of various factors on heat load and pressure. Finally, the fused state vector is input into the LSTM module, utilizing its powerful sequence analysis capabilities to predict future heat load demands. Heat load demand is a key factor in air conditioning system control; accurate prediction allows the system to prepare for adjustments in advance, improving response speed and control accuracy. Based on the predicted heat load demand, the model generates a pressure adjustment amount. This adjustment amount reflects the change required in the high-pressure side pressure to meet the predicted heat load demand. After obtaining the pressure adjustment amount, the final pressure setpoint is calculated by combining it with a preset pressure threshold. This adaptive heat pump control model, through advanced algorithms and modules, processes and analyzes multi-source data, achieving accurate calculation of the high-pressure side pressure setpoint, providing strong support for the efficient and stable operation of the CO2 transcritical rail vehicle air conditioning heat pump system.

[0041] For example, suppose a train is at a platform and in regenerative braking mode. Its transcritical CO2 air conditioning heat pump system acquires heat pump system parameter data (high-pressure side pressure 10 MPa, evaporation temperature 5°C, gas cooler outlet temperature 35°C, compressor speed 3000 rpm) and vehicle operating status data (doors opened and closed 10 times in the past 5 minutes, 5 passengers per square meter), and determines the vehicle mode to be energy-saving mode. Then, the heat pump system parameters are constructed into a state vector [10,5,35,3000], the energy-saving mode is encoded as [1,0,0], and fused with the state vector to obtain [1,0,0,10,5,35,3000], which is then input into an adaptive heat pump control model constructed based on a lightweight near-end strategy optimization algorithm and configured with an LSTM module. After predicting the heat load demand, the LSTM module generates a pressure adjustment of -1MPa. Combined with the initial base pressure setting of 11MPa and the preset pressure threshold of 8-12MPa, the final high-pressure side pressure setting is calculated to be 10MPa. The system then adjusts the compressor speed and the opening of the electronic expansion valve accordingly to achieve energy-saving operation.

[0042] Preferred, such as Figure 3 As shown, the step of calculating the electronic expansion valve opening value based on the generated pressure setpoint includes: determining the basic adjustment amount of the electronic expansion valve opening based on the deviation between the pressure setpoint and the current high-pressure side pressure; correcting the basic adjustment amount based on the evaporator superheat; calculating the vibration compensation amount based on the preset vibration compensation mechanism; and calculating the electronic expansion valve opening value based on the vibration compensation amount and the corrected basic adjustment amount.

[0043] More preferably, the step of calculating the vibration compensation amount according to the preset vibration compensation mechanism includes: embedding the historical electronic expansion valve opening adjustment sequence into the state vector to generate a new state vector; and, based on the generated new state vector, learning the law of electronic expansion valve response hysteresis under vibration environment through the adaptive heat pump control model, and generating the vibration compensation amount.

[0044] In a preferred embodiment of the present invention, vibrations during the operation of the rail vehicle can interfere with the normal response of the electronic expansion valve, leading to lag or inaccurate opening adjustment. To address this issue, the present invention incorporates a vibration compensation mechanism. First, the historical electronic expansion valve opening adjustment sequence is embedded into a state vector to generate a new state vector. This operation integrates historical adjustment information, enabling the new state vector to more comprehensively reflect the system's operational history and dynamic changes. Then, an adaptive heat pump control model is used to analyze the new state vector. This model is built based on a lightweight near-end strategy optimization algorithm and equipped with an LSTM module, possessing powerful learning and prediction capabilities. By learning the new state vector, the model can capture the pattern of electronic expansion valve response lag under vibration conditions and generate vibration compensation accordingly. The formula for calculating the vibration compensation can be expressed as:

[0045]

[0046] Where, Δθ vib This represents the vibration compensation amount, 'a' represents the compensation coefficient, and 'N' is the historical window length. This represents the i-th historical adjustment of the expansion valve opening.

[0047] For example, assuming the historical window length N = 10, the compensation coefficient a = 0.2, and the historical expansion valve opening adjustments for the past 10 times are 0.1, 0.2, 0.15, 0.25, 0.12, 0.22, 0.18, 0.28, 0.16, and 0.26 respectively, then the vibration compensation amount Δθ vib After calculation using equation (2), we obtain: Δθ vib

[0048] =0.0384. Add 0.0384 to the basic adjustment amount to obtain the final electronic expansion valve opening value.

[0049] Preferably, determining the vehicle condition mode based on the vehicle operating status data includes: switching the vehicle condition mode to energy-saving mode when the power supply mode is regenerative braking mode and the geographical location is a platform area; switching the vehicle condition mode to sudden load mode when the door opening and closing frequency is detected to be greater than a preset frequency, or the passenger density is greater than a preset density value; switching the vehicle condition mode to energy-saving mode when the vehicle operating status data simultaneously meets both energy-saving mode and sudden load mode; otherwise, switching the vehicle condition mode to normal mode.

[0050] In a preferred embodiment of the invention, the vehicle condition mode is closely linked to the vehicle operating status data. When the vehicle operating status data simultaneously meets the conditions for both energy-saving mode and sudden load mode, the system prioritizes switching to energy-saving mode. This fully considers the characteristics of vehicle operation and energy-saving needs. Although the sudden load mode is designed to cope with rapid changes in heat load, energy saving has a higher priority in the platform area and under regenerative braking mode. At this time, even with some heat load fluctuations, reasonable system regulation under energy-saving mode can still maximize energy savings while ensuring basic comfort.

[0051] For example, at 10:00 AM on Saturday, the train stops at platform C. This platform is near a large amusement park, where passengers frequently board and alight, doors open and close frequently, and passenger density in the carriages is high, meeting the conditions for a sudden load mode. However, at the same time, the train is in regenerative braking mode and is located in the platform area, thus meeting the conditions for an energy-saving mode. According to the rules, the system prioritizes switching to energy-saving mode. In energy-saving mode, the system optimizes control strategies and appropriately adjusts the cooling capacity to ensure basic comfort while maximizing the use of regenerative braking energy and reducing energy consumption.

[0052] Preferably, the CO2 transcritical rail vehicle air conditioning heat pump system control method further includes: when the door opening and closing frequency is detected to be greater than a preset frequency, expanding the adjustment range of the pressure setting value; when the passenger density is greater than a preset density value, expanding the adjustment range of the electronic expansion valve opening value; when the geographical location is a tunnel, switching the vehicle condition mode to the normal mode and limiting the adjustment range of the pressure setting value.

[0053] In a preferred embodiment of the invention, larger fluctuations in heat load require a stronger system regulation capability. By expanding the adjustment range of the pressure setpoint, the system can more flexibly adjust the high-pressure side pressure. For example, in hot weather, frequent opening and closing of vehicle doors allows a large amount of hot air to rush into the passenger compartment. At this time, a wider range of pressure regulation allows the compressor to output a more suitable cooling capacity, quickly reducing the temperature inside the vehicle and meeting the passengers' comfort needs. As a key component for controlling refrigerant flow, expanding the opening adjustment range of the electronic expansion valve allows for more precise control of the amount of refrigerant entering the evaporator. For example, during peak hours, when the passenger compartment is crowded, a large amount of heat dissipation from the human body causes a surge in heat load. A wider range of opening adjustment ensures that the evaporator can fully exert its cooling function and maintain a suitable temperature inside the vehicle. The environment inside the tunnel is relatively enclosed, and the vehicle's operating conditions are relatively stable, with relatively small changes in heat load. Switching to the normal mode allows the system to operate according to parameters under stable conditions, ensuring operational stability. Limiting the pressure setpoint adjustment range prevents the system from generating additional energy consumption due to unnecessary frequent pressure adjustments, while also avoiding damage to system components caused by excessive pressure fluctuations, ensuring stable and efficient operation inside the tunnel.

[0054] Preferably, the training process of the adaptive heat pump control model adopts a multi-objective reward function, and the weights in the multi-objective reward function are adjusted according to the vehicle operating status data and the vehicle condition mode. The adjustment of the weights in the multi-objective reward function includes: when the door opening and closing frequency is detected to exceed the preset frequency, the weight of the compressor power over-limit penalty term is increased to strengthen the priority of temperature stability; when the vehicle is in regenerative braking mode, the weight of the real-time energy efficiency ratio is increased to prioritize improving the energy efficiency ratio.

[0055] Specifically, the multi-objective reward function can be expressed as:

[0056]

[0057] Where α, β, and γ all represent weighting coefficients, and COP t P represents the real-time energy efficiency ratio. high This indicates the current high-pressure side pressure. T represents the high-pressure side pressure setpoint. cab Indicates the temperature of the carriage, T setThis indicates the target temperature of the carriage, and Power_p indicates the compressor power over-limit penalty.

[0058] In a preferred embodiment of the invention, frequent opening and closing of vehicle doors can cause significant fluctuations in the vehicle's heat load, making prioritizing temperature stability crucial. Increasing the weight of the compressor power over-limit penalty term encourages the model to avoid excessive compressor power increases when adjusting system parameters, preventing large temperature fluctuations caused by pursuing rapid cooling and heating. For example, if compressor power is increased without limit to cope with sudden changes in heat load, although the temperature can be changed quickly, it may cause temperature overshoot or large oscillations, affecting passenger comfort. Through this weight adjustment, the model prioritizes maintaining temperature stability while ensuring a certain cooling and heating capacity, keeping the vehicle's interior temperature within a comfortable range even with frequent changes in heat load. In regenerative braking mode, the vehicle can recover energy, and prioritizing the improvement of the energy efficiency ratio aligns with the overall goal of energy conservation. By increasing the weight of the real-time energy efficiency ratio, the model will be more inclined to optimize system operating parameters during training, enabling the air conditioning system to operate more efficiently while utilizing regenerative braking energy. For example, the model will adjust parameters such as compressor speed and electronic expansion valve opening to ensure that the system meets the vehicle's heat load requirements while minimizing additional power consumption, thereby maximizing energy utilization, improving the overall energy efficiency of the system, and reducing dependence on the external power grid.

[0059] Preferred, such as Figure 4 As shown, the control method for the CO2 transcritical rail vehicle air conditioning heat pump system further includes: triggering a defrost command when the outlet temperature of the gas cooler is lower than the dew point temperature and the duration exceeds a preset time; outputting a bypass valve opening command through the adaptive heat pump control model according to the defrost command; adjusting the bypass valve opening according to the output opening command to directionally introduce the exhaust heat of the variable frequency compressor into the gas cooler.

[0060] For example, imagine a train in operation. While the outside temperature drops to -10°C, the heat load inside the carriages remains relatively stable, but the gas cooler is continuously affected by the low temperature. At this point, the gas cooler outlet temperature sensor detects a temperature drop to 5°C, while the calculated dew point temperature is 8°C due to high humidity in the area. The gas cooler outlet temperature is below the dew point. Furthermore, this low-temperature condition persists for 15 minutes, exceeding the system's preset 10-minute timeframe. Therefore, the system quickly triggers a defrosting command. The adaptive heat pump control model immediately begins operating, comprehensively considering current system operating parameters such as high-pressure side pressure, compressor speed, and evaporator temperature, as well as the vehicle's operating mode. Through complex algorithms and pre-learned experience, the model quickly calculates the bypass valve opening command, assuming an output opening value of 40%. The system then precisely adjusts the bypass valve opening to 40% according to this command. At this time, some of the high-temperature, high-pressure gas discharged from the variable frequency compressor flows directly to the gas cooler through the bypass valve. This high-temperature gas carries a large amount of heat, rapidly acting on the frost layer on the gas cooler surface. Within minutes of continuous heating, the frost gradually melts into water droplets and drains through designated drainage channels, gradually restoring the heat exchange performance of the gas cooler. As the frost is cleared, the outlet temperature of the gas cooler gradually rises. Once the temperature stabilizes above the dew point and remains there for a period of time, the defrosting process ends, and the system returns to normal operation, continuing to provide a comfortable temperature environment for passengers inside the carriage.

[0061] In summary, this invention provides a CO2 transcritical rail vehicle air conditioning heat pump system and its control method. By comprehensively collecting heat pump system parameters and vehicle operating status data, the system determines the vehicle condition mode. An adaptive heat pump control model generates a high-pressure side pressure setpoint, and combined with PID closed-loop control to adjust the variable frequency compressor speed, it precisely calculates and adjusts the electronic expansion valve opening, achieving refined intelligent control of the system. In terms of adaptability, it can flexibly switch between energy-saving, sudden load, and normal vehicle condition modes based on different operating conditions such as door opening and closing frequency, passenger density, geographical location, and power supply mode, meeting the heat load requirements under different scenarios and effectively ensuring the comfort of the in-vehicle environment. Regarding energy-saving design, it switches to energy-saving mode when in regenerative braking mode and in the platform area. Simultaneously, when training the adaptive heat pump control model, the real-time energy efficiency ratio weight is increased for regenerative braking mode to optimize system energy efficiency and reduce energy consumption. In terms of the defrosting mechanism, scientific defrosting trigger conditions are set, and the adaptive heat pump control model accurately outputs bypass valve opening commands. Defrosting is achieved by directionally introducing heat from the variable frequency compressor exhaust, ensuring high efficiency and system stability and safety, and comprehensively improving system performance.

[0062] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0063] Furthermore, the terms "system" and "network" are often used interchangeably in this paper. The term "and / or" in this paper merely describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " in this paper generally indicates that the preceding and following related objects have an "or" relationship.

[0064] It should be understood that, in the embodiments of the present invention, "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0065] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0066] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0067] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, apparatuses, or units, or they may be electrical, mechanical, or other forms of connection.

[0068] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0069] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0070] From the above description of the embodiments, those skilled in the art will clearly understand that the present invention can be implemented in hardware, firmware, or a combination thereof. When implemented in software, the above-described functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a computer. For example, but not limited to, computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media, or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible to a computer. Furthermore, any connection can suitably be a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the scope of the medium. As used in this invention, disks and discs include CDs, laser discs, optical discs, DVDs, floppy disks, and Blu-ray discs, wherein disks typically magnetically copy data, while discs optically copy data using lasers. The combinations described above should also be included within the scope of protection for computer-readable media.

[0071] In summary, the above description is merely a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling a CO2 transcritical rail vehicle's air conditioning heat pump, characterized in that, The CO2 transcritical rail vehicle air conditioning heat pump control method includes: Acquire heat pump system parameter data and vehicle operating status data, and determine vehicle condition mode based on the vehicle operating status data; Based on the determined vehicle condition mode and the heat pump system parameter data, a high-pressure side pressure setpoint is generated through a preset adaptive heat pump control model. Based on the generated pressure setpoint, calculate the opening value of the electronic expansion valve, including: determining the basic adjustment amount of the electronic expansion valve opening based on the deviation between the pressure setpoint and the current high-pressure side pressure; The basic adjustment amount is adjusted based on the evaporator superheat. According to the preset vibration compensation mechanism, the vibration compensation amount is calculated, specifically: the historical electronic expansion valve opening adjustment sequence is embedded into the constructed state vector to generate a new state vector; based on the generated new state vector, the adaptive heat pump control model is used to learn the law of electronic expansion valve response hysteresis under vibration environment, and the vibration compensation amount is generated. Based on the vibration compensation amount and the corrected basic adjustment amount, the opening value of the electronic expansion valve is calculated. Based on the generated pressure setpoint, the speed of the variable frequency compressor is adjusted through PID closed-loop control, and the opening of the electronic expansion valve is adjusted according to the calculated expansion valve opening value.

2. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 1, characterized in that, The heat pump system parameters include high-pressure side pressure, evaporation temperature, gas cooler outlet temperature, and compressor speed. The vehicle operating status data includes door opening and closing frequency, passenger density, geographical location, and power supply mode.

3. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 2, characterized in that, The adaptive heat pump control model is constructed based on a lightweight near-end strategy optimization algorithm and is equipped with an LSTM module. The step of generating a high-pressure side pressure setpoint based on the determined vehicle condition mode and the heat pump system parameter data, through a preset adaptive heat pump control model, includes: Based on the heat pump system parameter data, construct the state vector of the heat pump system; The vehicle condition pattern is encoded as an independent feature and then fused with the state vector; Based on the fused state vector, the heat load demand is predicted and the pressure adjustment is generated using the LSTM module. The pressure setpoint is calculated based on the generated pressure adjustment amount and the preset pressure threshold.

4. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 2, characterized in that, The step of determining the vehicle condition mode based on the vehicle operating status data includes: When the power supply mode is regenerative braking mode and the geographical location is a platform area, switch the vehicle condition mode to energy-saving mode; When the frequency of the vehicle door opening and closing is detected to be greater than the preset frequency, or the passenger density is greater than the preset density value, the vehicle condition mode is switched to the sudden load mode. When the vehicle operating status data simultaneously meets the requirements of both energy-saving mode and sudden load mode, switch the vehicle status mode to energy-saving mode. Otherwise, switch the vehicle status mode to normal mode.

5. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 2, characterized in that, The CO2 transcritical rail vehicle air conditioning heat pump control method also includes: When the frequency of door opening and closing is detected to be greater than the preset frequency, the adjustment range of the pressure setting value is expanded. When the passenger density is greater than the preset density value, the adjustment range of the electronic expansion valve opening value is expanded. When the geographical location is a tunnel, the vehicle condition mode is switched to normal mode, and the adjustment range of the pressure setting value is limited.

6. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 1, characterized in that, The training process of the adaptive heat pump control model employs a multi-objective reward function, and the weights in the multi-objective reward function are adjusted based on the vehicle operating status data and the vehicle condition mode. The adjustment of the weights in the multi-objective reward function includes: When the frequency of door opening and closing is detected to exceed the preset frequency, the weight of the compressor power over-limit penalty item will be increased, and the priority of temperature stability will be strengthened. When the vehicle is in regenerative braking mode, the weight of the real-time energy efficiency ratio is increased, and the energy efficiency ratio is improved first.

7. The CO2 transcritical rail vehicle air conditioning heat pump control method according to claim 1, characterized in that, The CO2 transcritical rail vehicle air conditioning heat pump control method also includes: When the outlet temperature of the gas cooler is lower than the dew point temperature and the duration exceeds the preset time, a defrosting command is triggered. Based on the defrosting command, the bypass valve opening command is output through the adaptive heat pump control model; According to the output opening command, the opening of the bypass valve is adjusted to direct the exhaust heat of the variable frequency compressor into the gas cooler.

8. A CO2 transcritical rail vehicle air conditioning heat pump system, used to implement the CO2 transcritical rail vehicle air conditioning heat pump control method according to any one of claims 1-7, characterized in that, The CO2 transcritical rail vehicle air conditioning heat pump system includes: a variable frequency compressor, an electronic expansion valve, a gas cooler, a bypass valve, a sensor network, and an on-board edge controller; The vehicle-mounted edge controller is equipped with a multi-source data fusion module and an adaptive heat pump control model. The vehicle-mounted edge controller is used to generate a high-pressure side pressure setpoint and an electronic expansion valve opening value through the adaptive heat pump control model, and to adjust the variable frequency compressor and the electronic expansion valve according to the generated high-pressure side pressure setpoint and electronic expansion valve opening value.

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