A control method and power saving analysis method for an air conditioning system of a rail vehicle

Abstract

The application provides a control method and power saving analysis method of a rail vehicle air conditioning system, and relates to the technical field of rail vehicle air conditioning system control. The control method comprises the following steps: collecting at least one environmental parameter data by using at least one environmental parameter sensor distributed in each carriage, and classifying and marking the collected environmental parameter data according to the carriage number; generating an execution command for the zoned control of the rail vehicle based on the collected at least one environmental parameter data and a preset air conditioning regulation strategy; and sending the execution command to an execution unit of the corresponding carriage, so that the execution unit responds to the execution command and performs dynamic adjustment, thereby realizing the zoned control of the rail vehicle air conditioning system. Through zoned control, dynamic adjustment, intelligent management and data-driven decision-making, the comfort, reliability and energy utilization efficiency of the rail vehicle air conditioning system are significantly improved, and the adaptability and flexibility of the system are also enhanced.

Description

Technical Field

[0001] This invention relates to the field of air conditioning system control technology for rail vehicles, specifically to a control method and energy-saving analysis method for an air conditioning system for rail vehicles. Background Technology

[0002] Current rail air conditioning technology centers on centralized cooling, variable frequency control, and heat recovery systems, optimizing energy efficiency through magnetic levitation direct expansion technology, aluminum corrugated pipe heat exchangers, and SVPWM variable frequency regulation. However, the system still faces technical bottlenecks such as heat loss from centralized cooling pipes, insufficient adaptability to extreme climates, and frequent defrosting due to condensation dehumidification. The industry is breaking through energy efficiency ceilings through intelligent upgrades and the application of new materials. Existing rail vehicle air conditioning systems mostly adopt a centralized control strategy, uniformly adjusting compressor power and air volume after collecting average environmental parameters of the entire train through a single sensor.

[0003] However, this type of technology has significant drawbacks: high energy consumption and inefficient regulation. Centralized control cannot differentiate between the environmental differences between carriages, causing the compressor to run at full power for extended periods, resulting in wasted energy. For example, using the same cooling intensity for carriages with low passenger flow as for fully loaded carriages increases energy consumption and reduces comfort. Summary of the Invention

[0004] The purpose of this invention is to provide a control method and energy-saving analysis method for a rail vehicle air conditioning system. This method is based on a multi-parameter fusion-based rail vehicle air conditioning zoning control method and energy-saving strategy.

[0005] To achieve the above objectives, embodiments of the present invention provide a control method for a rail vehicle air conditioning system. The rail vehicle air conditioning system includes at least one environmental parameter sensor, a control center, and an execution unit. The rail vehicle air conditioning system control method is applied to the control center and includes: using the at least one environmental parameter sensor distributed in each car to collect at least one environmental parameter data, and classifying and labeling the collected environmental parameter data according to the car number; generating an execution command for rail vehicle zone control based on the collected at least one environmental parameter data and a preset air conditioning control strategy; sending the execution command to the execution unit of the corresponding car, so that the execution unit responds to the execution command and performs dynamic adjustment to realize zone control of the rail vehicle air conditioning system.

[0006] Furthermore, the at least one environmental parameter data includes key parameters and correction parameters; the key parameters include the interior temperature, exterior temperature, interior humidity, and carbon dioxide corresponding to individual carriages; the correction parameters include the number of passengers and the light intensity outside the carriage.

[0007] Furthermore, the number of passengers is calculated using passenger flow counters installed at the entrances and exits of the carriages and at the connection points between adjacent carriages; and the light intensity is measured using light sensors installed on the outside of the carriages.

[0008] Furthermore, the execution unit includes an air circulation system, a temperature regulation module, and a humidity regulation module; the air circulation system is used to independently supply air to each compartment, the temperature regulation module is used to regulate the air supply temperature, and the humidity regulation module is used to regulate the air supply humidity.

[0009] Furthermore, the step of generating execution commands for the zoned control of rail vehicles based on at least one collected environmental parameter data and a preset air conditioning control strategy includes: calculating the target power of the air conditioner based on the preset temperature, in-vehicle humidity, temperature difference between inside and outside the vehicle and the thermal conductivity of the carriage; then correcting the target power of the air conditioner based on the number of passengers in the carriage and the light intensity; and performing adjustment at the target power of the air conditioner to prevent the air conditioner from running at full power and reduce temperature control oscillations.

[0010] Furthermore, the temperature regulation module includes a compressor and a motor, both of which are equipped with a frequency converter. The frequency converter adjusts the air supply temperature and air supply volume according to the executed command.

[0011] Furthermore, the humidity control module generates an execution command for the zoned control of the rail vehicle based on at least one collected environmental parameter data and a preset air conditioning control strategy, including: when the humidity parameter data exceeds a preset upper limit value, activating the condensation dehumidification function of the humidity control module to adjust the supply air humidity.

[0012] Furthermore, the air circulation system includes a fresh air system and an internal circulation system. Based on at least one collected environmental parameter data and a preset air conditioning control strategy, the air circulation system generates execution commands for the zoned control of the rail vehicle, including: when the carbon dioxide parameter exceeds a preset value, the fresh air system is activated through the execution command of the control center. The fresh air system is connected to the air outside the car and is collected by the purifier and then replenished into the car.

[0013] Furthermore, the fresh air system is equipped with a flow detection sensor, and the temperature regulation module calculates the compressor's compensation power based on the detected fresh air flow parameters and the outside temperature to ensure the stability of the supply air temperature.

[0014] This invention also discloses a power-saving analysis method, which includes: controlling the target rail vehicle air conditioning system based on the above-mentioned rail vehicle air conditioning system control method; acquiring historical power consumption data and historical operating data affecting power consumption of the target rail vehicle air conditioning system; converting the correlation calculation between operating parameters and power consumption into a quadratic inequality optimization model based on the acquired historical power consumption data and historical operating data affecting power consumption, so as to screen key influencing factors affecting power consumption on a quantum computing simulator; and adjusting the preset air conditioning control strategy based on the screened key influencing factors and combined with environmental parameter data.

[0015] Beneficial effects:

[0016] This invention proposes a control method for a rail vehicle air conditioning system. Through zoned control, dynamic adjustment, intelligent management, and data-driven decision-making, it significantly improves the comfort, reliability, and energy efficiency of the rail vehicle air conditioning system, while also enhancing its adaptability and flexibility. By collecting and classifying environmental parameter data from each carriage, zoned control can be implemented based on the environmental conditions of different carriages, achieving more precise air conditioning adjustment. Simultaneously, dynamic commands can be generated based on real-time collected environmental parameters and preset air conditioning control strategies, and transmitted to the execution unit, enabling the air conditioning system to quickly adapt to environmental changes and maintain a stable environment within the carriage.

[0017] This invention also provides a method for energy-saving analysis of rail vehicle air conditioning systems. By combining the control methods and historical data of the rail vehicle air conditioning system, and utilizing a quantum computing simulator, it efficiently screens key influencing factors and optimizes air conditioning control strategies, demonstrating significant technical advantages. This method, based on in-depth analysis of historical electricity consumption data and operating parameters, accurately identifies key factors affecting electricity consumption through a quadratic inequality optimization model, avoiding reliance on redundant data in traditional methods and significantly improving analysis efficiency. Secondly, quantum computing can drastically shorten the solution time of complex models, providing technical support for real-time optimization. This method can dynamically adjust air conditioning strategies based on environmental parameters, significantly reducing energy consumption while ensuring passenger comfort, achieving a balance between energy saving and user experience.

[0018] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0020] Figure 1 This is a schematic diagram of the system workflow provided in an embodiment of the present invention.

[0021] Figure 2 This is a calculation flowchart provided in an embodiment of the present invention.

[0022] Figure 3 This is a flowchart illustrating the power-saving analysis method provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Unlike the crude vehicle control strategies of traditional technologies, this invention employs a method of setting up at least one environmental parameter sensor, a control center, and an execution unit in each independent compartment.

[0025] Figures 1 to 2 This is a flowchart of a method for controlling an air conditioning system in a rail vehicle, according to an embodiment of the present invention. Figure 1 As shown, the method for controlling the air conditioning system of a rail vehicle may include the following steps:

[0026] Step S100: Using the at least one environmental parameter sensor distributed in each carriage, collect at least one environmental parameter data, and classify and label the collected environmental parameter data according to the carriage number.

[0027] In this embodiment of the application, a classification and labeling method can be adopted so that the data of each carriage can be recorded and stored independently, avoiding confusion and interference between data, ensuring the originality and integrity of the data, so that the data of each carriage can be analyzed and traced separately during the traceability process, which facilitates subsequent feedback.

[0028] In this application, at least one preferred environmental parameter data may include: key parameters and correction parameters, etc.

[0029] The preferred key parameters in the embodiments of this application may include the interior temperature, exterior temperature, interior humidity, and carbon dioxide concentration corresponding to a single carriage; the correction parameters may include the number of passengers and the intensity of sunlight outside the carriage.

[0030] The interior and exterior temperatures can be obtained using temperature sensors located inside or outside the vehicle, while the interior humidity and carbon dioxide concentration can be obtained using humidity and carbon dioxide sensors located inside the vehicle.

[0031] In a preferred embodiment of this application, the passenger flow parameter can be calculated using passenger flow counters installed at the entrances and exits of the carriages and at the connections between adjacent carriages. Light intensity is measured using a light sensor installed outside the carriages.

[0032] Step S200: Based on the collected environmental parameter data and the preset air conditioning control strategy, generate an execution command for the zone control of the rail vehicle.

[0033] The embodiments of this application can generate independent control commands based on the environmental parameter data of a single carriage, so that the temperature, humidity and carbon dioxide concentration in each carriage are in a suitable state, thereby improving the passenger riding experience.

[0034] Among these factors, the interior temperature, exterior temperature, interior humidity, and carbon dioxide concentration directly affect the three key functions of the air conditioning system: cooling, air supply, and dehumidification. These are crucial parameters influencing the air conditioning power within the vehicle. Furthermore, passengers generate heat through breathing and movement, impacting the interior temperature, and direct sunlight also raises the interior temperature. Therefore, passenger volume and external sunlight intensity allow for calculations to adjust the air conditioning power required in this solution.

[0035] The primary issue to consider in air conditioning control is temperature; ensuring a suitable temperature inside the vehicle is the main task of the air conditioning system.

[0036] The power of the air conditioning system inside the carriage, generated from the temperature parameters, is shown in the following formula:

[0037]

[0038] In the formula, The temperature control power generated by the vehicle's air conditioning system based on temperature parameters. For preset temperature, For the temperature inside the car, The outside temperature of the vehicle. τ For integration variables, k The thermal conductivity of the vehicle; , These are the weighting coefficients.

[0039] For example, the comfortable perceived temperature for people is between 24-28°C. Therefore, the temperature inside the car can be set according to this comfortable perceived temperature. The value range is, for example, 24-28℃. The difference between the preset temperature and the real-time in-vehicle temperature is the main factor affecting the air conditioning power.

[0040] In equation (1), This can be used to illustrate the impact of the difference between the current interior temperature and the preset temperature on the air conditioning output power. When the difference between the interior temperature and the preset temperature is large, this value will increase significantly, meaning that the air conditioning needs to output more power to regulate the temperature. The exponential function in the denominator of this formula is: This function acts as a smooth regulator. When the temperature difference is large, the exponential function value increases rapidly, preventing the overall fractional value from becoming too large. This avoids excessive and drastic changes in power output, thus simulating the actual situation of an air conditioning system gradually increasing its power output under large temperature differences, rather than instantly reaching maximum power. This makes the change in air conditioning output power gradual, thereby achieving energy-saving effects.

[0041] In equation (1), The primary consideration is the impact of outside temperature on in-vehicle temperature regulation. The difference between outside and inside temperature reflects the degree of interference between the external environment and the vehicle's thermal balance. The larger this value, the greater the impact of the external environment on the in-vehicle temperature, and the more power the air conditioner needs to consume to offset this impact. The numerator of the second term is a cubic term, which can amplify the effect of the difference between inside and outside the vehicle. When the difference between inside and outside the vehicle is large, the air conditioning power is significantly increased.

[0042] For weighting coefficients and ,in > This allows the air conditioner to use the difference between the interior temperature and the preset temperature as the main control indicator.

[0043] Humidity inside the carriage is also an important factor affecting passenger comfort. When the humidity parameter exceeds the preset upper limit, the control center generates a control command to activate the condensation dehumidification function of the humidity regulation module and adjust the air supply humidity.

[0044] The control command is generated based on the humidity parameter, expressed by the following formula:

[0045]

[0046] In the formula, The air conditioning power required for dehumidification. The calculation period is specified. The volume of the carriage interior. This refers to the air circulation cycle. The latent heat of vaporization of water is approximately 2,260,000 J / kg. The density of air is approximately 1.2 kg / m³. The dehumidification efficiency of the air conditioning system is dimensionless and ranges from 0 to 1, determined based on the performance of the air conditioning system. For the thermal resistance of the condenser, This is the thermal resistance of the evaporator.

[0047] in, The difference between the absolute humidity of the air inside the carriage and the preset upper limit of humidity can be expressed as follows:

[0048]

[0049] in, The real-time humidity inside the carriage. This is the preset upper limit for humidity.

[0050] The above control methods are only applicable when When the humidity level is greater than 0 (i.e., the real-time humidity inside the vehicle is higher than the preset humidity), the dehumidifier will activate to prevent it from running unnecessarily, thus achieving energy savings. After the dehumidifier is activated, its power can also be adjusted based on the real-time humidity parameters inside the vehicle.

[0051] In a preferred embodiment of this application, the air circulation system may include a fresh air system and an internal circulation system. The air circulation system generates an execution command for the zoned control of the rail vehicle based on at least one collected environmental parameter data and a preset air conditioning control strategy. This may include: when the carbon dioxide parameter exceeds a preset value, the fresh air system is activated by the execution command of the control center. The fresh air system is connected to the air outside the car and is collected by a purifier and then replenished into the car.

[0052] The fresh air volume can be calculated using the following formula:

[0053]

[0054] In the formula, For fresh air flow, For the volume of the carriage, This represents the real-time concentration of carbon dioxide inside the train carriage. This is the preset concentration of carbon dioxide. For ventilation rate, The oxygen content of fresh air is weighted.

[0055] when hour, A value greater than zero allows for the introduction of fresh air. When... When necessary, the introduction of fresh air can be reduced or stopped.

[0056] However, there is a temperature difference between the fresh air and the temperature inside the vehicle. Therefore, when fresh air is introduced, the air conditioning compressor needs to generate additional power to adjust the temperature of the fresh air.

[0057] The fresh air system is equipped with a flow detection sensor. The temperature regulation module calculates the compressor's compensation power based on the detected fresh air flow parameters and the outside temperature to ensure the stability of the supply air temperature. The additional power generated by introducing fresh air is:

[0058]

[0059] In the formula, This is the additional power generated by introducing fresh air. It's the fresh air flow rate. It is air density. It is the specific heat capacity of air. For the temperature inside the car, The outside temperature of the vehicle.

[0060] In summary, the air conditioning power of a certain carriage, generated from the key parameters, is:

[0061]

[0062] In the formula, This is the air conditioning power of a certain carriage, generated from key parameters. The output power generated by the vehicle's air conditioning system based on temperature parameters. The air conditioning power required for dehumidification, This refers to the additional power generated due to the introduction of fresh air.

[0063] The method for adjusting the air conditioning power inside the carriage based on passenger flow and outdoor light intensity is as follows:

[0064]

[0065] In the formula, For the correction power, The number of passengers in the carriage. The average heat dissipation per passenger, The angle of incidence of sunlight entering the car window is given by I, where I is the external light intensity. This refers to the total area of ​​the car windows. For the internal volume of the carriage, air density, This is the specific heat capacity of air. For the thermal resistance of the air conditioning system, For the heat capacity of the air conditioning system, The initial time constant, expressed in seconds (s), is a time parameter used during the initial startup phase of the air conditioning system to describe its dynamic characteristics. t is a time constant, measured in seconds (s), and represents the time parameter required for the air conditioning system to reach a steady state. As the weight of human body radiant heat, It is the weight of solar radiation.

[0066] in, This refers to the total heat dissipated by the vehicle. As the number of passengers increases, the heat dissipation gradually increases. In summer, more power is needed to maintain the interior temperature within a comfortable range. In winter, the power can be reduced accordingly.

[0067] Similarly, sunlight entering a vehicle will cause the interior temperature to rise. This warming effect is particularly pronounced in areas with strong sunlight. Furthermore, the warming effect of sunlight is also related to the angle of incidence of the sunlight.

[0068] In summary, after correction, the output power of the air conditioner in a certain carriage can be expressed as:

[0069]

[0070] In the formula, This refers to the output power of the air conditioner in a single carriage after modification. The power of the air conditioning in the carriage is generated through key parameters. To correct the power, Number the carriages It is 0 in summer and 1 in winter.

[0071] The total power consumption of air conditioning in rail vehicles can be calculated using the following formula:

[0072]

[0073] In the formula, This refers to the total power of the air conditioning units in the rail vehicles. This refers to the output power of the air conditioner in a single carriage after modification. Number the carriages This represents the total number of carriages.

[0074] The control center calculates the target power of the air conditioner based on the preset temperature, humidity inside the vehicle, temperature difference between inside and outside the vehicle, and thermal conductivity of the passenger compartment. Then, it corrects the target power of the air conditioner based on the number of passengers and light intensity in the passenger compartment, and adjusts the air conditioner to the target power to prevent it from running at full power and reduce temperature control oscillations.

[0075] Step S300: Send the execution command to the execution unit of the corresponding carriage, so that the execution unit responds to the execution command and performs dynamic adjustment to realize the zone control of the rail vehicle air conditioning system.

[0076] The execution unit includes an air circulation system, a temperature control module, and a humidity control module.

[0077] The air circulation system provides independent airflow to each carriage. It consists of a fresh air system and an internal circulation system. The fresh air system draws in fresh air from outside the carriage, reducing carbon dioxide concentration and ensuring passengers breathe clean air. The internal circulation system circulates air within the carriage, maintaining consistent temperature and humidity throughout. Furthermore, the internal circulation system can be equipped with filters to remove dust, bacteria, viruses, and other harmful substances, keeping the air clean and improving passenger comfort.

[0078] The temperature control module includes a compressor and a motor. Both the compressor and the motor are equipped with a frequency converter. The frequency converter adjusts the air supply temperature and air supply volume according to the executed command.

[0079] The humidity control module includes a condenser and an evaporator, used to regulate the humidity of the supply air.

[0080] This application embodiment can collect environmental parameter data of each carriage and classify and label them, thereby enabling zoned control based on the environmental conditions of different carriages, achieving more precise air conditioning adjustment, improving passenger comfort while reducing the power consumption of the air conditioning system.

[0081] The embodiments of this application have intelligent dynamic adjustment capabilities. They can generate dynamic instructions based on real-time collected environmental parameters and preset air conditioning control strategies, and send them to the execution unit, so that the air conditioning system can quickly adapt to environmental changes and maintain the stability of the environment inside the vehicle.

[0082] In summary, the embodiments of this application significantly improve the comfort, reliability, and energy efficiency of the rail vehicle air conditioning system through zoned control, dynamic adjustment, intelligent management, and data-driven decision-making, while also enhancing the system's adaptability and flexibility.

[0083] like Figure 3 As shown, this application embodiment also provides a power-saving analysis method for a rail vehicle air conditioning system, the power-saving analysis method may include the following steps S10-S40:

[0084] Step S10: Based on the above-described control method for the air conditioning system of a rail vehicle, control the air conditioning system of the target rail vehicle;

[0085] Step S20: Obtain historical power consumption data and historical operational data affecting power consumption of the target rail vehicle's air conditioning system;

[0086] Step S30: Based on the acquired historical electricity consumption data and historical operating data affecting electricity consumption, the correlation calculation between operating parameters and electricity consumption is transformed into a quadratic inequality optimization model in order to screen key influencing factors affecting electricity consumption on the quantum computing simulator;

[0087] Step S40: Adjust the preset air conditioning control strategy based on the selected key influencing factors and combined with environmental parameter data.

[0088] For example, the analysis method can adopt multi-objective collaborative optimization, and introduce Pareto front analysis into the QUBO model to balance multiple objectives such as energy saving rate (≥15%), comfort (PMV compliance rate >95%), and equipment life (compressor start-stop frequency reduced by 50%).

[0089] First, calculate the conditional mutual information (CMI) between each parameter and energy consumption in the above control method, using the following formula:

[0090]

[0091] In the formula, x, y, and z can be any combination of the air conditioning parameters mentioned above, such as the interior temperature ( ), outside temperature ( ), preset temperature ( Substitute the parameters into the above formula, and use the above formula to filter parameters with CMI > 0.3 to enter the QUBO model.

[0092] Define binary decision variables ,and The objective function is:

[0093]

[0094] In the formula, The CMI value of parameter i. The redundancy of parameters i and j (absolute value of Pearson correlation coefficient). =0.4 (empirical value) and Let i and j be the decision variables, respectively.

[0095] N is the decision variable with parameter i. The quantity, decision variables This represents a binary choice that can take the value 0 or 1, such as whether to turn on the fresh air system or activate the condensation dehumidification function within a certain period of time under the target condition; N is the total number of these decision variables.

[0096] H is the objective function value of the QUBO model, representing the degree of optimization of the system state when given a specified combination of parameters i and j.

[0097] The QUBO model can be used to calculate the objective function value H of the optimization degree of each parameter combination in the air conditioning system. By comparing H, the optimal parameter combination can be obtained, thereby optimizing the combination of each parameter in the air conditioning system and achieving a balanced optimization of multiple objectives such as energy saving, comfort and equipment life.

[0098] The following three scenarios illustrate the air conditioning control strategy:

[0099] Scenario 1: In special scenarios such as tunnels, the operating parameters of the air conditioning system can be optimized by adjusting the weight of the oxygen content in the fresh air to meet the comfort and health needs of the specific environment.

[0100] By using GPS positioning technology to identify when a train enters a tunnel area, a rule is triggered to increase the weight of fresh air oxygen content. By increasing the weight of fresh air oxygen content, the air conditioning system is ensured to prioritize the introduction of more fresh air in this scenario, thereby improving the air quality inside the train and enhancing passenger comfort.

[0101] In this scenario, the trigger rule for the control strategy is: GPS data is used to measure the airflow into the tunnel area and the air pressure difference is greater than 200 Pa. At this time, the weighting of the fresh air oxygen content is adjusted. Up to 0.6-0.8.

[0102] By adjusting the weighting of oxygen content in fresh air, the ventilation effect of the air conditioning system can be optimized based on the external environment to achieve the best ventilation effect. Simultaneously, by combining the actual operating parameters of the air conditioning system, such as humidity and temperature, the air conditioning control strategy can be further optimized to ensure that comfort requirements are met while also considering other objectives such as energy consumption.

[0103] Scenario 2: Under high passenger density conditions, the cooling efficiency of the air conditioning system and the local comfort of passengers can be improved by adjusting the weight of human body radiant heat and triggering directional air supply mode.

[0104] By introducing a binocular vision system to monitor passenger density in the carriage in real time, when passenger density is high, the impact of human body radiant heat on the surrounding environment increases. In addition, due to the crowded conditions, air circulation between passengers is poor, which can easily lead to a problem where the temperature is lower near the outside of the carriage and higher between passengers. At this time, it is necessary to change the direction of the air conditioning to improve the heat dissipation problem between passengers.

[0105] In this scenario, the triggering rule for the control strategy is: when the passenger density is greater than 4 people / m², and the duration exceeds 10 minutes.

[0106] At this time, the human body's radiant heat weight The temperature range is reduced to 0.85-0.95, allowing the air conditioning system to pay more attention to the heat dissipation needs of the human body. By enhancing the cooling capacity or adjusting the air supply mode, the heat generated by the human body can be eliminated in a timely and effective manner, thereby improving the overall thermal comfort.

[0107] Scenario 3: When the vehicle is exposed to sunlight for a long time, the power of the air conditioning system compressor is increased by adjusting the solar radiation weight and the air conditioning set temperature, and the air volume on the side where the sun is shining is increased.

[0108] In this scenario, the triggering rules for the control strategy are: light intensity > 250,000 lux and roof temperature > 45℃.

[0109] At this point, adjust the solar radiation weight. The air conditioner's set temperature is between 0.5 and 0.7. Increase the temperature by 1°C and change the airflow direction to increase the airflow on the side where the sun is shining, thereby improving the comfort level on the sunlit side.

[0110] Scenario 4: Aggregate the operation data of multiple trains through a federated learning framework to build a dynamic energy consumption baseline model; when the real-time power consumption deviates from the baseline value by ±15%, initiate Bayesian network source tracing analysis to locate fault parameters and generate maintenance work orders.

[0111] The system employs a federated learning framework to aggregate train operation data and train a representative and accurate dynamic energy consumption baseline model. This model can comprehensively consider factors such as the operating conditions and environmental conditions of different trains, reflecting the normal energy consumption level of trains under various circumstances in real time.

[0112] By comparing real-time power consumption with baseline values, abnormal energy consumption can be detected in a timely manner, providing a basis for subsequent fault tracing and maintenance. When real-time power consumption deviates from the baseline value by ±15%, Bayesian network tracing analysis is initiated. By analyzing the probabilistic relationships and dependency structures between various parameters, the Bayesian network infers the most likely cause of the fault, thereby quickly locating the fault parameters leading to abnormal energy consumption and generating targeted maintenance work orders.

[0113] This method, based on data-driven fault diagnosis and repair, can improve the timeliness and accuracy of repairs, effectively reduce the impact of equipment failures on train operation, extend equipment lifespan, help optimize air conditioning control strategies, and avoid energy waste caused by equipment failures.

[0114] The energy-saving analysis method provided in this application combines the control method of the rail vehicle air conditioning system with historical data, and utilizes a quantum computing simulator to efficiently screen key influencing factors and optimize air conditioning control strategies, exhibiting significant technical advantages. Based on in-depth analysis of historical electricity consumption data and operating parameters, this method accurately identifies key factors affecting electricity consumption through a quadratic inequality optimization model, avoiding reliance on redundant data in traditional methods and significantly improving analysis efficiency. Secondly, quantum computing can drastically shorten the solution time of complex models, providing technical support for real-time optimization. This method can dynamically adjust air conditioning strategies based on environmental parameters, significantly reducing energy consumption while ensuring passenger comfort, achieving a balance between energy saving and user experience.

[0115] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0117] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0118] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0119] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0120] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0121] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0122] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0123] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A control method for an air conditioning system of a rail vehicle, characterized in that, The rail vehicle air conditioning system includes at least one environmental parameter sensor, a control center, and an execution unit. The execution unit includes an air circulation system, a temperature regulation module, and a humidity regulation module. The temperature regulation module includes a compressor and a motor. The rail vehicle air conditioning system control method is applied to the control center and includes: Using at least one environmental parameter sensor distributed in each carriage, at least one environmental parameter data is collected, and the collected environmental parameter data is classified and labeled according to the carriage number; the at least one environmental parameter data includes the interior temperature, exterior temperature, preset temperature, interior humidity, carbon dioxide concentration, passenger flow, and exterior light intensity. Based on at least one collected environmental parameter data and a preset air conditioning control strategy, an execution command for zonal control of the rail vehicle is generated; the execution command is sent to the execution unit of the corresponding car, and the execution unit responds to the execution command and performs dynamic adjustment to realize zonal control of the rail vehicle air conditioning system; Generating the execution command includes: Calculate the cabin air conditioning power generated from key parameters ; Calculate the temperature control power using the following formula. : in, For preset temperature, For the temperature inside the car, The outside temperature of the vehicle. For integration variables, The thermal conductivity of the vehicle. , These are the weighting coefficients; when A negative value indicates that the air conditioning system is in heating mode; When the humidity level inside the vehicle exceeds the preset upper limit, the condensation dehumidification function of the humidity control module is activated, the supply air humidity is adjusted, and the required air conditioning power for dehumidification is calculated. ; The air circulation system includes a fresh air system and an internal circulation system. Based on at least one collected environmental parameter data and a preset air conditioning control strategy, the air circulation system generates execution commands for the zoned control of the rail vehicle: when the carbon dioxide concentration exceeds a preset value, the fresh air system is activated, and the compressor's compensation power is calculated based on the detected fresh air flow rate and the outside temperature. To ensure the stability of the supply air temperature; The corrected power is calculated based on the number of passengers and the light intensity inside the carriage. The corrected output power of the air conditioner inside the carriage is obtained according to the following formula. in, Number the carriages It is 0 in summer and 1 in winter; with the aforementioned output power Execute adjustments to prevent the air conditioner from operating at full power and reduce temperature control oscillations; The method further includes an energy-saving analysis step: acquiring historical power consumption data of the target rail vehicle's air conditioning system and historical operating data affecting power consumption; calculating the conditional mutual information (CMI) between each parameter and energy consumption based on the acquired historical power consumption data and historical operating data affecting power consumption, and selecting parameters with a CMI greater than 0.3 as key influencing factors affecting power consumption to enter the quadratic inequality optimization model (QUBO); and calculating the objective function value based on the QUBO model on a quantum computing simulator. : in, For parameters CMI value For parameters With parameters Redundancy, Based on experience points. and Parameters and parameters Decision variables, The total number of decision variables; by comparing the values ​​of the objective function. The optimal parameter combination is obtained through screening; Based on the selected optimal parameter combination and combined with environmental parameter data, the preset air conditioning control strategy is adjusted.

2. The control method for a rail vehicle air conditioning system according to claim 1, characterized in that, The number of passengers is calculated using passenger flow counters installed at the entrances and exits of the carriages and at the connection points between adjacent carriages; the light intensity is measured using light sensors installed on the outside of the carriages.

3. The control method for a rail vehicle air conditioning system according to claim 1, characterized in that, The air circulation system is used to independently supply air to each compartment, the temperature regulation module is used to regulate the air supply temperature, and the humidity regulation module is used to regulate the air supply humidity.

4. The control method for a rail vehicle air conditioning system according to claim 1, characterized in that, Both the compressor and the motor are equipped with frequency converters, which adjust the air supply temperature and air supply volume according to the executed command.

5. The control method for a rail vehicle air conditioning system according to claim 1, characterized in that, The fresh air system is equipped with a flow detection sensor. The temperature regulation module calculates the compressor's compensation power based on the detected fresh air flow parameters and the outside temperature to ensure the stability of the supply air temperature.

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