Vehicle cabin partition temperature control method, electronic equipment and vehicle

Abstract

The embodiment of the invention provides a cabin partition temperature control method of a vehicle, electronic equipment and the vehicle. The cabin partition temperature control method comprises the steps that environment data of the position where the vehicle is located and human body feature data of at least one area in a vehicle cabin are collected; according to the environment data and the human body characteristic data of the at least one area, calculating a personnel cooling and heating load and a human body heat effect calibration factor of each area, and according to the personnel cooling and heating load and the human body heat effect calibration factor of each area, calculating a total load of the corresponding area; and determining an optimization function of the corresponding region according to the total load of each region, determining a temperature adjustment parameter value of the corresponding region according to the optimization function of each region, and controlling the temperature of the corresponding region according to the temperature adjustment parameter value of each region. Therefore, the problems that an existing multi-temperature-zone air conditioner technology is mostly based on an air temperature sensor in a compartment, human body thermal inductance factors are not fully considered, and response according to individual differences is lacked are solved, the human body comfort of a passenger compartment is improved, and the air conditioner energy consumption of the whole vehicle is optimized.

Description

Technical Field

[0001] This application relates to the field of automotive intelligence and energy-saving technology, and in particular to a method for cabin temperature control, electronic equipment, and vehicle. Background Technology

[0002] Currently, multi-zone climate control technology in vehicles cannot adjust according to individual user differences. Furthermore, existing control systems are mostly based on sensors for overall air temperature control within the vehicle cabin, without fully considering factors directly related to human body temperature. This leads to energy waste or discomfort for users in certain controlled areas, which urgently needs to be addressed. Summary of the Invention

[0003] This application provides a method for cabin temperature control, an electronic device, and a vehicle, aiming to improve the current multi-zone air conditioning technology, which is mostly based on in-cabin air temperature sensors, does not fully consider the relevant factors of human body heat perception, and lacks accurate response to individual differences.

[0004] This application proposes a method for zoned temperature control of a vehicle cabin, comprising: collecting environmental data of the vehicle's location and human characteristic data of at least one area within the vehicle cabin; calculating the human thermal load and human thermal effect calibration factor for each area based on the environmental data and / or the human characteristic data of the at least one area, and calculating the total load of the corresponding area based on the human thermal load and human thermal effect calibration factor for each area; determining the optimization function for the corresponding area based on the total load of each area, and determining the temperature adjustment parameter value for the corresponding area based on the optimization function for each area, so as to control the temperature of the corresponding area according to the temperature adjustment parameter value of each area.

[0005] In some embodiments, calculating the thermal load of personnel in each region based on the environmental data and / or the human characteristic data of the at least one region includes: calculating a first heat exchange between the vehicle shell and the environment, a second heat exchange between personnel in each region and the external environment, and a third heat exchange between personnel in each region and the external environment based on the environmental data and / or the human characteristic data of the at least one region; calculating the thermal load of personnel in the corresponding region based on the first heat exchange, the second heat exchange, and the third heat exchange, thereby obtaining the thermal load of personnel in each region.

[0006] In some embodiments, calculating the thermal load of personnel in the corresponding area based on the first heat exchange, the second heat exchange, and the third heat exchange to obtain the thermal load of personnel in each area includes: calculating the blood circulation compensation factor of the corresponding area based on the human characteristic data of the personnel in each area, calculating the difference between the body temperature of the personnel in each area and the preset body temperature benchmark to obtain the body temperature difference value of each area, and calculating the product of the blood circulation compensation factor of each area and the body temperature difference value of the corresponding area; calculating the ratio of the product of each area to the heart rate coefficient of the personnel in the corresponding area, and calculating the thermal load of personnel in each area based on the ratio of each area, the first heat exchange, the second heat exchange, and the third heat exchange.

[0007] In some embodiments, calculating the first heat exchange between the vehicle shell and the environment, the second heat exchange between personnel in each area and the external environment, and the third heat exchange between personnel in each area and the external environment based on the environmental data and / or the human characteristic data of the at least one area includes: acquiring the vehicle's current cabin temperature, cabin shell surface area, vehicle body thickness at its thickest point, solar radiation angle factor, glass reflectivity, sunlight intensity, exposed skin area of ​​personnel in each area, and temperature at at least one location; calculating the second heat exchange based on the solar radiation angle factor, glass reflectivity, and sunlight intensity of each area; obtaining the third heat exchange based on the current cabin temperature, the exposed skin area of ​​personnel in each area, and temperature at at least one location; and obtaining the first heat exchange based on the current ambient temperature, the cabin shell surface area, and the vehicle body thickness at its thickest point from the environmental data.

[0008] In some embodiments, calculating a human thermal effect calibration factor for each region based on the environmental data and / or the human characteristic data of the at least one region includes: obtaining the total number of people in the vehicle cabin, the current cabin temperature in the environmental data, and the temperature of at least one location of the people in the human characteristic data of the at least one region; and calculating the human thermal effect calibration factor for each region based on the total number of people, the current cabin temperature, and the temperature of at least one location of the people.

[0009] In some embodiments, the optimization function for each region is: C(t) = w4 * f pmv +w5*EER; EER = Q / P; Where C(t) is the optimization function, P is the power consumption of the compressor, Q is the total load, and w4 is the power of f. pmv The corresponding weighting coefficients, w5 is the weighting coefficient corresponding to EER, f pmv EER represents the overall thermal comfort ratio inside the vehicle.

[0010] In some embodiments, calculating the overall thermal comfort ratio inside the vehicle includes: collecting temperature and humidity parameters for each area inside the vehicle cabin; determining the number of areas where the temperature parameter is within a first preset range and the humidity parameter is within a second preset range based on the temperature and humidity parameters of each area; and calculating the overall thermal comfort ratio inside the vehicle based on the ratio of the number of areas to the total number of areas.

[0011] In some embodiments, determining the temperature adjustment parameter value of the corresponding region based on the optimization function of each region includes: adjusting the initial blower air volume, initial compressor speed, and initial air outlet angle of the vehicle according to a preset adjustment strategy; calculating the optimization function value corresponding to the adjusted blower air volume, compressor speed, and air outlet angle based on the optimization function; and obtaining the target blower air volume adjustment parameter value, target compressor speed adjustment parameter value, and target air outlet angle adjustment parameter value of the corresponding region when the optimization function value satisfies a preset minimum value condition.

[0012] This application also proposes a vehicle cabin zoned temperature control system, comprising: a data acquisition module for acquiring environmental data of the vehicle's location and human characteristic data of at least one area within the vehicle cabin; a calculation module for calculating the human thermal load and human thermal effect calibration factor for each area based on the environmental data and / or the human characteristic data of the at least one area, and calculating the total load of the corresponding area based on the human thermal load and human thermal effect calibration factor of each area; and an optimization module for determining an optimization function for the corresponding area based on the total load of each area, and determining the temperature adjustment parameter value of the corresponding area based on the optimization function of each area, so as to control the temperature of the corresponding area according to the temperature adjustment parameter value of each area.

[0013] In some embodiments, the calculation module is further configured to: calculate a first heat exchange between the vehicle shell and the environment, a second heat exchange between personnel in each area and the external environment, and a third heat exchange between personnel in each area and the external environment based on the environmental data and / or human characteristic data of the at least one area; calculate the human heating and cooling load of the corresponding area based on the first heat exchange, the second heat exchange, and the third heat exchange, to obtain the human heating and cooling load of each area.

[0014] In some embodiments, the calculation module is further configured to: calculate the blood circulation compensation factor for the corresponding region based on the human characteristic data of the personnel in each region, and calculate the difference between the body temperature of the personnel in each region and the preset body temperature benchmark to obtain the body temperature difference value of each region, and calculate the product of the blood circulation compensation factor of each region and the body temperature difference value of the corresponding region; calculate the ratio of the product of each region to the heart rate coefficient of the personnel in the corresponding region, and calculate the thermal load of the personnel in each region based on the ratio of each region, the first heat exchange, the second heat exchange, and the third heat exchange.

[0015] In some embodiments, the calculation module is further configured to: acquire the vehicle's current cabin temperature, cabin shell surface area, vehicle body thickness at its thickest point, solar radiation angle factor for each region, glass reflectivity, sunlight intensity, exposed skin area of ​​personnel, and temperature at at least one location; calculate a second heat exchange based on the solar radiation angle factor, glass reflectivity, and sunlight intensity of each region; obtain a third heat exchange based on the current cabin temperature, the exposed skin area of ​​personnel in each region, and temperature at at least one location; and obtain the first heat exchange based on the current ambient temperature, the cabin shell surface area, and the vehicle body thickness at its thickest point from the environmental data.

[0016] In some embodiments, the calculation module is further configured to: obtain the total number of people in the vehicle cabin, the current cabin temperature in the environmental data, and the temperature of at least one location of the people in the human characteristic data of the at least one region; and calculate the human thermal effect calibration factor for each region based on the total number of people, the current cabin temperature, and the temperature of at least one location of the people.

[0017] In some embodiments, the optimization function for each region is: C(t) = w4 * f pmv +w5*EER; EER = Q / P; Where C(t) is the optimization function, P is the power consumption of the compressor, Q is the total load, and w4 is the power of f. pmv The corresponding weighting coefficients, w5 is the weighting coefficient corresponding to EER, f pmv EER represents the overall thermal comfort ratio inside the vehicle.

[0018] In some embodiments, the optimization module is further configured to: collect temperature and humidity parameters for each area within the vehicle cabin; determine the number of areas where the temperature parameter is within a first preset range and the humidity parameter is within a second preset range based on the temperature and humidity parameters of each area; and obtain the overall thermal comfort ratio within the vehicle based on the ratio of the number of areas to the total number of areas.

[0019] In some embodiments, the optimization module is further configured to: adjust the initial blower air volume, initial compressor speed, and initial air outlet angle of the vehicle according to a preset adjustment strategy; calculate the optimization function value corresponding to the adjusted blower air volume, compressor speed, and air outlet angle based on the optimization function; and obtain the target blower air volume adjustment parameter value, target compressor speed adjustment parameter value, and target air outlet angle adjustment parameter value of the corresponding region when the optimization function value satisfies the preset minimum value condition.

[0020] This application also proposes an electronic device, including a processor and a memory, wherein the memory is used to store computer programs; and the processor is used to execute the programs stored in the memory to implement the above-mentioned vehicle cabin partition temperature control method.

[0021] This application also proposes a vehicle that includes the aforementioned electronic equipment. Attached Figure Description

[0022] Figure 1 This is a flowchart of a vehicle cabin zoned temperature control system provided in one embodiment of this application; Figure 2 This is a flowchart of an implementation method for intelligent temperature control provided in an embodiment of this application; Figure 3 This is a flowchart of a method for determining partition adjustment parameters provided in an embodiment of this application; Figure 4 This is a structural diagram of the vehicle cabin zoned temperature control system provided in the embodiments of this application; Figure 5 This is a structural diagram of the electronic device provided in the embodiments of this application; Figure 6 This is a vehicle structure diagram provided in one embodiment of this application. Detailed Implementation

[0023] To make the technical problems, technical solutions, and beneficial effects solved by this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] Current mainstream thermal comfort assessment methods (such as PMV (Predicted Mean Vote) / PPD (Predicted Percentage of Dissatisfied)) rely almost entirely on environmental parameters (temperature, humidity, wind speed, etc.) and do not incorporate individual real-time physiological states (heart rate, body temperature, metabolic rate) or behavioral data. These static models are ill-suited to address population differences (different metabolisms among the elderly, children, and athletes) and dynamic scenarios (changes in perceived comfort due to sweating after strenuous exercise).

[0025] While some studies attempt to learn user preferences using historical data (such as deep learning models), their training relies heavily on subjective rating data, making it difficult to dynamically adjust for real-time physiological changes in individuals (such as sudden fatigue or disease states). Furthermore, traditional indicators like WBGT (Wet Bulb Globe Temperature, a comprehensive thermal stress assessment index that considers multiple environmental factors) are based on population statistics and fail to account for the impact of local blood circulation differences on perceived temperature. For example, temperature differences between active muscle areas (hands, back) and inactive areas can lead to uneven heat dissipation, and existing models lack a quantitative description of this mechanism.

[0026] Furthermore, the heat exchange between the human body's metabolic rate and the ambient temperature involves complex heat transfer equations. Current research often simplifies modeling through empirical formulas, leading to significant prediction errors in extreme scenarios (such as profuse sweating in winter or static low temperatures in summer).

[0027] To address the aforementioned issues, this application provides a method for zoned temperature control in a vehicle cabin. This method involves collecting environmental data of the vehicle's location and human characteristic data for at least one area within the vehicle cabin; calculating the thermal load and human thermal effect calibration factor for each area based on the environmental data and the human characteristic data for at least one area; calculating the total load for the corresponding area based on the thermal load and human thermal effect calibration factor for each area; calculating an optimization function for the corresponding area based on the total load for each area; determining the temperature regulation parameter value for the corresponding area based on the optimization function for each area; and controlling the temperature of the corresponding area based on the temperature regulation parameter value for each area.

[0028] Compared with the closest prior art, a vehicle air conditioning control method, electronic device and storage medium are proposed (Publication No.: CN120080689A). The method includes: in response to an air conditioning start signal of a designated seat, controlling sensors to acquire environmental parameters and thermal radiation data of a passenger in the designated seat; estimating human body thermal parameters of the passenger in the designated seat based on the environmental parameters, the location of the designated seat and the thermal radiation data, and calculating the corresponding comfort value of the passenger in the designated seat based on the human body thermal parameters; configuring an interactive body temperature option based on the comfort value, and controlling the air conditioning to adjust the temperature of the area where the designated seat is located after receiving an interactive command.

[0029] Therefore, the comparative document only calculates the heat exchange value of the human body's thermal environment, hypothalamic temperature, average skin temperature, and neutral skin temperature through sensors, and controls the air conditioning to regulate the temperature of the designated seat area. However, it does not involve parameters related to the thermal effect of the human body itself or the heat exchange between the vehicle and the environment, such as the radiative heat exchange between the person and the outside world, the convective heat exchange between the person and the surrounding environment, and the heat exchange between the vehicle shell and the environment. Furthermore, it does not adjust the temperature of the corresponding area according to the different loads of the people. The vehicle can respond according to the individual differences in the passenger compartment, and achieve optimal energy consumption while meeting the multi-temperature comfort of the passenger compartment.

[0030] This application provides a method for cabin temperature control in a vehicle. Please refer to [link / reference]. Figure 1 This includes the following steps: In step S101, environmental data of the vehicle's location and human characteristic data of at least one area inside the vehicle's cabin are collected.

[0031] In this embodiment, the environmental data of the vehicle's location includes indoor temperature T1, indoor humidity φ1, outdoor temperature T2, outdoor humidity φ2, sunlight intensity E, and indoor set temperature T3. The human characteristic data of at least one area in the vehicle cabin includes head surface temperature T4, temperature of other exposed locations T5, real-time heart rate Y, personnel type, and micro-motion sensing data M(t). The micro-motion sensing data M(t) is determined according to the intensity of the personnel's activities. The human characteristic data is generally obtained through a human data acquisition device, which can be collected through the personnel's smart bracelet, infrared sensor, etc.

[0032] There is at least one area in the vehicle cabin that is related to the location within the vehicle cabin. For example, if the vehicle is a 5-seater, then the vehicle cabin includes 5 areas.

[0033] In step S102, the human thermal load and human thermal effect calibration factor for each region are calculated based on environmental data and / or human characteristic data of at least one region, and the total load of the corresponding region is calculated based on the human thermal load and human thermal effect calibration factor for each region.

[0034] In some embodiments, calculating the human thermal load of each region based on environmental data and / or human characteristic data of at least one region includes: calculating a first heat exchange between the vehicle shell and the environment, a second heat exchange between the human in each region and the external environment, and a third heat exchange between the human in each region and the external environment based on environmental data and / or human characteristic data of at least one region; calculating the human thermal load of the corresponding region based on the first heat exchange, the second heat exchange between the human in each region and the external environment, and the third heat exchange between the human in each region and the external environment, thereby obtaining the human thermal load of each region.

[0035] It should be noted that the first heat exchange is the heat exchange between the vehicle shell and the environment, and its calculation needs to take into account the thermal conductivity of the shell and environmental data; the second heat exchange refers to the radiative heat exchange between personnel and the external environment, mainly the radiative heat exchange between personnel and glass; and the third heat exchange is the convective heat exchange between personnel and the surrounding environment, which is related to the exposed skin area and temperature of personnel.

[0036] Specifically, such as Figure 2 As shown, by dividing the vehicle interior into zones and calculating the first heat exchange between the vehicle shell and the environment, the radiative heat exchange between the personnel and the outside world, and the convective heat exchange between the personnel and the surrounding environment for each zone, the heating and cooling load of the personnel in each zone can be calculated based on the first heat exchange between the vehicle shell and the environment, the radiative heat exchange between the personnel and the outside world, and the convective heat exchange between the personnel and the surrounding environment for each zone, thereby achieving differentiated temperature regulation of the vehicle zones.

[0037] By using the above technical solution, human characteristic data (head and exposed position temperature, heart rate, micro-motion sensor data) and zoned environmental parameters are collected in zones. Combined with the heat exchange between the vehicle shell and the environment, the radiative heat exchange between people and the external environment, and the convective heat exchange between people and the external environment, the system can achieve refined calculation of the heating and cooling load of people in different zones. This can accurately reflect the differences in the actual heat demand of people in different seats, so as to achieve temperature control based on the differences in the actual heat demand of people in different seats.

[0038] In some embodiments, calculating a first heat exchange between the vehicle shell and the environment, a second heat exchange between personnel in each area and the external environment, and a third heat exchange between personnel in each area and the external environment based on environmental data and / or human characteristic data of at least one area includes: acquiring the vehicle's current cabin temperature, cabin shell surface area, vehicle body thickness at its thickest point, solar radiation angle factor, glass reflectivity, sunlight intensity, personnel skin exposure area, and temperature at at least one location for each area; calculating the second heat exchange between personnel in the corresponding area and the external environment based on the solar radiation angle factor, glass reflectivity, and sunlight intensity for each area; obtaining the third heat exchange between personnel in the corresponding area and the external environment based on the current cabin temperature, personnel skin exposure area in each area, and temperature at at least one location; and obtaining the first heat exchange based on the current ambient temperature, cabin shell surface area, and vehicle body thickness at its thickest point from the environmental data.

[0039] Specifically, the calculation methods for the first heat exchange between the vehicle shell and the environment, the second heat exchange between personnel and the external environment, and the third heat exchange between personnel and the external environment are as follows: The third heat exchange between personnel and the external environment is: Q 对流 =k*A*δT; Where k is the convective heat transfer coefficient, A is the skin area exposed in the crew compartment, δT is the temperature difference between the skin temperature and the room temperature, where δT=((T4+λT5) / 2)-T1, λ is the exposure location correction factor, which can be taken as 1.2 for arm exposure and 1.5 for arm and leg exposure, T4 is the head surface temperature of the personnel, and T5 is the temperature of other exposure locations of the personnel (such as arms or legs).

[0040] The second heat exchange between personnel and the external environment is: Q 辐射 =α*E*(1–ρ 车窗 ); Where α is the solar insolation angle factor, which is determined based on time and location, ρ is the glass reflectivity, which depends on the glass material, and E is the sunlight intensity.

[0041] The first heat exchange between the vehicle body and the environment is: Q 导热 =-k'*A'*(dT / dx; Where k' is the average thermal conductivity of the vehicle body material, and A' is the surface area of ​​the passenger compartment outer shell, (dT / dx) = (T2-T1) / x, x is the thickness of the thickest part of the vehicle body, T1 is the current temperature inside the cabin, and T2 is the vehicle temperature.

[0042] It should be noted that the convective heat transfer coefficient represents the ability of airflow to remove heat from the human body surface. It usually needs to be obtained by combining experiments, theories or semi-empirical formulas, and taking into account specific application scenarios (such as natural convection, forced convection, wind speed, clothing effects, etc.) and is summarized from experiments.

[0043] The solar zenith angle factor is a correction factor for the effect of the angle of sunlight perpendicular to or deviating from the surface normal on radiative transfer efficiency. It is typically calculated using the vehicle's GPS coordinates, time, and date to determine the local real-time solar zenith angle θ. z And solar azimuth φ s Based on the vehicle design, determine the angle θ between the surface normal of the glass and the ground plane. n and azimuth φ n Thus, the solar insolation angle factor is obtained: α=sinθ z ×sinθ n ×cos(φ) s -φ n ) + cosθ z ×cosθ n .

[0044] The average thermal conductivity of vehicle body materials depends on the material properties of the vehicle body. For example, the thermal conductivity of pure aluminum at 100℃ is 240W / m. 2 0.5% carbon steel has a W / m² of 47.5. 2 The arithmetic average is obtained based on the heat exchange area between the vehicle and the outside environment.

[0045] Through the above technical solutions, the radiative heat transfer incorporates the solar angle factor and glass reflectivity to capture the differences in solar radiation in different areas (such as the second row under direct sunlight and the driver's seat in the shade); the convective heat transfer is calculated based on the exposed area of ​​human skin and the difference between skin temperature and cabin temperature, and the effects of arm exposure and arm + leg exposure are corrected by the exposure location correction factor to compensate for the differences in heat exchange efficiency in different parts, avoid the deviation of averaging calculation, and make it more consistent with the actual heat exchange state of the occupants; the conductive heat transfer combines the thermal conductivity of the vehicle body material, the surface area of ​​the outer shell, and the thickness of the vehicle body to adapt to the structural differences of different models, avoiding the load calculation deviation caused by ignoring the thermal conductivity of the shell or using fixed empirical values ​​in traditional solutions, and providing reliable data support for subsequent zonal heating and cooling load calculations.

[0046] In some embodiments, the thermal load of the personnel in a corresponding area is calculated based on the first heat exchange, the second heat exchange between the personnel in each area and the external environment, and the third heat exchange between the personnel in each area and the external environment, to obtain the thermal load of the personnel in each area. This includes: calculating the blood circulation compensation factor of the corresponding area based on the human characteristic data of the personnel in each area, calculating the difference between the body temperature of the personnel in each area and the preset body temperature benchmark to obtain the body temperature difference value of each area, and calculating the product of the blood circulation compensation factor of each area and the body temperature difference value of the corresponding area; calculating the ratio of the product of each area to the heart rate coefficient of the personnel in the corresponding area, and calculating the thermal load of the personnel in each area based on the ratio of each area, the first heat exchange, the second heat exchange, and the third heat exchange.

[0047] In this application, blood circulation compensation factor ρ ccf The calculation method is as follows: ρ ccf =(a1-a2) / a 血 ×exp(φ*M(t) 0.8 ) Among them, a 血 =36.5+0.6δT 2 δT = ((T4 + λT5) / 2) - T1, φ is the intensity of individual activity, which is generally taken as 1, but can be adjusted according to individual differences to meet the actual situation, M(t) is the micro-motion sensing data, which is generally taken as 0, 1, 2, 3, representing the increase from stillness to vigorous movement, such as taking 0 for prohibition of stillness and taking 3 for vigorous movement, a2 represents the average surface temperature of the human body, which can be obtained by the arithmetic mean of the temperature at the exposure location.

[0048] Further calculations of the difference between the body temperature of individuals in each area and the preset body temperature baseline yield the body temperature difference value for each area, i.e., calculating a1-a b Where a1 is the current core body temperature, a b To preset the body temperature baseline, a b ≈36.8℃.

[0049] Further calculation of the product of the blood circulation compensation factor and the corresponding temperature difference in each region yields ρ. ccf (a1-a) b Furthermore, the ratio ρ is calculated based on the product of the corresponding regions and the individual's heart rate coefficient Y'. ccf (a1-a) b ) / Y'.

[0050] Finally, based on the ratio of each area, the first heat exchange, the second heat exchange, and the third heat exchange, the heating and cooling load of the people in each area is calculated, specifically the heating and cooling load of the people Q. 总 for: Q 总=Q 对流 +Q 导热 +ρ ccf (a1-a) b ) / Y'+Q 辐射 .

[0051] Where Y' = 0.18 + 12 × ln(Y / Y0), Y0 is the resting heart rate of the person, and Y is the real-time heart rate of the person in the corresponding area.

[0052] For example, the driver's head surface temperature T4 is 34.2℃, the driver's exposed arm temperature T5 is 33.8℃, the driver's area temperature in the cabin T1 is 28℃, the exposure position correction factor λ is 1.2, the individual activity intensity coefficient φ is 1, the micromotion sensor data is 0, a1 is 37.0℃, the average human body surface temperature a2 is 34℃, the resting heart rate Y0 is 70 beats / minute, the real-time heart rate Y is 75 beats / minute, the convective heat transfer is 80W, the conductive heat transfer is 50W, and the radiative heat transfer is 40W. Then δT = ((T4 + λT5) / 2) - T1 is 9.38, a 血 The value was 89.29, and the blood circulation compensation factor ρ ccf The value is 0.0336, a1-a b =0.2, Y'=0.18+12×ln(Y / Y0)=1.008, ρ ccf (a1-a) b The value of Y' is 0.0067.

[0053] Then Q 总 =80+50+0.0067+40 is approximately equal to 170W.

[0054] Through the above technical solution, blood circulation compensation, by combining individual activity intensity, micro-motion sensing data, and the influence of environmental temperature difference, can reflect the impact of human activity status on blood circulation efficiency and heat generation and dissipation capacity. The body temperature difference is related to the deviation between the human core body temperature and the comfort baseline body temperature, and the heart rate coefficient reflects changes in human metabolic intensity. The physiological correction term ρ is calculated using the above data. ccf (a1-a) b The physiological correction term is incorporated into the total load calculation, so that the cooling and heating load is no longer a simple environmental-heat exchange calculation value, but a personalized load value that fits the real-time physiological state of the human body. This can realize differentiated air conditioning temperature output in different areas and improve the thermal comfort experience of different occupants in the vehicle.

[0055] Furthermore, in some embodiments, the human thermal effect calibration factor for each region is calculated based on environmental data and human characteristic data of at least one region, including: obtaining the total number of people in the vehicle cabin, the current cabin temperature, and the temperature of at least one location of the people; and calculating the human thermal effect calibration factor for each region based on the total number of people, the current cabin temperature, and the temperature of at least one location of the people.

[0056] Specifically, after calculating the thermal load of personnel in the corresponding area, it is necessary to correct the thermal load of personnel using the human body thermal effect calibration factor. This needs to be calculated based on the total number of personnel in the vehicle cabin, the current cabin temperature, and the temperature of at least one position of the personnel. The temperature of at least one position includes the head surface temperature T4 and the temperature of other exposed positions T5.

[0057] The calculation method for the human body thermal effect calibration factor is as follows: M = w1*n 总 + w2*n 人员种类 + w3*((T4 + λT5) / 2)-T1 Where M is the human body thermal efficiency calibration factor, w1, w2, and w3 are characteristic coefficients, where w1 can be 0.27, w2 can be 0.43, w3 can be 0.3, and n... 人员种类 The criteria for personnel types are: male adults 3, children 2, female adults 1.5, and elderly 1. Personnel types are identified by infrared sensors, and user input can also be made on the vehicle's screen.

[0058] After calculating the human thermal effect calibration factor, the total load of the personnel in the corresponding area is calculated, i.e.: Q = M * Q 总 .

[0059] For example, w1 is 0.27, w2 is 0.43, w3 is 0.3, and n... 总 For 3, n 人员种类 The value is 3, the head surface temperature is 34.5℃, T5 is 33.9℃, the exposure location correction factor λ is 1.2, T1 is 29℃, and Q... 总 It is 180W.

[0060] Then M = w1*n 总 + w2*n 人员种类 + w3*((T4 + λT5) / 2)- T1=0.27×3+0.43×3+0.3×((34.5+ 1.2×33.9) / 2)- 29=4.677, then Q = 4.677×180W approximately equals 842W.

[0061] The above technical solution integrates the total number of occupants, personnel types, average head and exposed position temperatures with the actual cabin temperature to calculate a human thermal effect calibration factor. This calibration factor corrects the calculation results of the personnel's heating and cooling load in the corresponding area, resulting in the total load of the personnel in the corresponding area. This offsets the calculation errors caused by individual differences in personnel and changes in the number of occupants, ensuring that the final heating and cooling load value is highly consistent with the actual thermal perception of the human body, thereby improving the accuracy of the calculation of the personnel load in the corresponding area.

[0062] In step S103, the optimization function for each region is determined based on the total load of each region, and the temperature regulation parameter value for each region is determined based on the optimization function of each region, so as to control the temperature of the corresponding region according to the temperature regulation parameter value of each region.

[0063] In some embodiments, the optimization function for each region is: C(t) = w4 * f pmv +w5*EER; EER = Q / P; Where C(t) is the optimization function, P is the power consumption of the compressor, Q is the total load, and w4 is the power of f. pmv The corresponding weighting coefficients, w5 is the weighting coefficient corresponding to EER, f pmv The overall thermal comfort ratio inside the vehicle is represented by W4 and W5, which are weights optimized based on a genetic algorithm and can be adjusted according to the scenario.

[0064] In some embodiments, calculating the overall thermal comfort ratio inside the vehicle includes: collecting temperature and humidity parameters for each area inside the vehicle cabin; determining the number of areas where the temperature parameters are within a first preset range and the humidity parameters are within a second preset range based on the temperature and humidity parameters for each area; and calculating the overall thermal comfort ratio inside the vehicle based on the ratio of the number of areas to the total number of areas.

[0065] Specifically, temperature and humidity parameters are collected for each area of ​​the vehicle's cabin. It is then determined whether the temperature parameter in each area falls within a first preset range and the humidity parameter falls within a second preset range. The number of areas where both temperature and humidity parameters fall within the first and second preset ranges is determined, thereby obtaining the overall thermal comfort ratio f within the vehicle. pmv .

[0066] Among them, F pmv The calculation is as follows: f pmv = ∑I(PMV i inPMV0) / n 总 (PMV) i (inPMV0) refers to determining whether the temperature parameter is within the first preset range and whether the humidity parameter is within the second preset range.i PMV of the i-th region i i can be 1, 2, 3, 4, 5, etc., depending on the vehicle zone. Generally, 5-seater vehicles are divided into 5 zones and 7-seater vehicles are divided into 7 zones. PMV0 refers to the first preset zone as 23℃~25℃ and the second preset zone as 45RH~65RH. ∑I is the cumulative count.

[0067] For example, consider a 5-seater car as 5 zones, according to PMV i For different zones, determine whether the temperature and humidity within each zone fall within the PMV0 range (temperature: 23℃~25℃, humidity: 45RH~65RH). For example, if a vehicle is fully occupied by 5 people (n total = 5), and only one zone (driver's seat) meets the temperature and humidity parameters, then f... pmv =0.2.

[0068] Where, if f pmv Not up to standard (e.g., f) pmv If the value is ≤0.3, then both the compressor speed and the blower air volume will be increased simultaneously to prioritize comfort.

[0069] After calculating the overall thermal comfort ratio inside the vehicle, the optimization function for each region is determined as follows: C(t) = w4 * f pmv +w5*EER; EER = Q / P.

[0070] Through the above technical solution, the optimization function integrates two core indicators: thermal comfort ratio and energy efficiency ratio. fpmv quantifies the overall comfort level of the vehicle cabin by statistically analyzing the proportion of areas with temperatures between 23℃ and 25℃ and humidity between 45%RH and 65%RH, ensuring that the temperature control effect meets the human body's needs. EER reflects the energy utilization efficiency of the air conditioning system. The higher the EER, the lower the power consumption of the compressor under the same load, and the better the energy consumption. Finally, the adjustment parameter value of the corresponding area is determined by C(t), achieving the dual goal of minimizing system energy consumption while meeting the comfort requirements of most areas.

[0071] In some embodiments, determining the temperature regulation parameter values ​​for a corresponding region based on the optimization function for each region includes: adjusting the initial blower air volume, initial compressor speed, and initial air outlet angle of the vehicle according to a preset adjustment strategy; calculating the optimization function values ​​corresponding to the adjusted blower air volume, compressor speed, and air outlet angle based on the optimization function; and obtaining the target blower air volume regulation parameter value, target compressor speed regulation parameter value, and target air outlet angle regulation parameter value for the corresponding region when the optimization function value meets the preset minimum value condition.

[0072] For example, the preset adjustment strategy is as follows: the adjustment amount of the air outlet angle is 5°, the adjustment amount of the blower air volume is 1 small level, and the adjustment amount of the compressor speed is 500 rpm. If the air outlet angle, blower air volume, and compressor speed are increased or decreased according to the adjustment amount, the optimization function value is calculated based on the adjusted blower air volume, compressor speed, and air outlet angle.

[0073] Specifically, such as Figure 3 As shown, after calculating the total load of each region, the total load of each region is input into the preset dynamic control model, which outputs the initial blower air volume, initial compressor speed, and initial air outlet angle, and calculates the optimization function value. It should be noted that the preset dynamic control model is obtained by pre-building a vehicle temperature control test bench to simulate different environmental conditions (temperature, humidity, sunlight intensity) and different occupant states (number of people, type of personnel, activity intensity), and collecting the corresponding data of load Q, compressor speed N, blower air volume s, and air outlet angle ω under each condition.

[0074] If the overall thermal comfort ratio inside the vehicle is f pmv If the deviation exceeds 30%, the vehicle's blower airflow, compressor speed, and vent angle will be adjusted according to preset adjustment values. For example, the blower airflow may be increased by 5°, the compressor speed by 500 rpm, and the vent angle by one level. Alternatively, the blower airflow may be decreased by 5°, the compressor speed by 500 rpm, and the vent angle by one level. The preset dynamic control model will then be consulted to determine Q, and the overall thermal comfort ratio f within the vehicle will be recalculated. pmv Based on the queried Q and the calculated f pmv Calculate the optimization function value again.

[0075] When the optimization function value meets the preset minimum value condition, the target blower air volume adjustment parameter value, target compressor speed adjustment parameter value, and target air outlet angle adjustment parameter value for the corresponding region are obtained. The vehicle is then controlled to perform temperature control according to the corresponding region based on these parameters. If the optimization function value does not meet the preset minimum value condition, the blower air volume, compressor speed, and air outlet angle are continuously adjusted until the optimization function value meets the preset minimum value condition. The preset minimum value condition is: abs(adjusted C(t) - unadjusted C(t)') / adjusted C(t) ≤ 5%.

[0076] By using the above technical solution, the blower air volume, compressor speed, and air outlet angle are adjusted according to the adjustment amount, and the optimal parameter combination that meets the minimum value condition is selected, avoiding the problems of over-adjustment or under-adjustment, so that the air conditioning system always operates in the optimal working state.

[0077] To enable those skilled in the art to further understand the vehicle cabin temperature control method of the embodiments of this application, the following detailed description is provided in conjunction with specific embodiments.

[0078] Collect vehicle parameter data, including indoor temperature T1, indoor humidity φ1, outdoor temperature T2, outdoor humidity φ2, sunlight intensity E, indoor set temperature T3, blower speed s, compressor gear N, number of passengers in the passenger compartment n1 (driver), n2 (passenger), n3 (second row left), n4 (second row middle), n5 (second row right) {taking a 5-seater vehicle as an example}, and human body data including head surface temperature T4, temperature of other exposed positions T5, real-time heart rate Y, personnel type, and micro-motion sensor data M(t).

[0079] Further calculations are made of the radiative and convective heat exchange between personnel and the external environment, as well as the conductive heat exchange between the vehicle shell and the environment. Based on the blood circulation compensation factor, the thermal load of personnel in the corresponding area is calculated to obtain the thermal load of personnel in each area.

[0080] The human body thermal effect calibration factor is used to calibrate the human body thermal load in each area, and the total human body load Q in each area is obtained.

[0081] The total human load Q of each region is input into the dynamic control model, and the initial blower air volume s, initial compressor speed N, and initial air outlet angle ω are output. The optimization function value corresponding to the initial blower air volume s, initial compressor speed N, and initial air outlet angle ω is calculated. If the optimization function value does not meet the minimum value condition, the initial blower air volume s, initial compressor speed N, and initial air outlet angle ω are adjusted.

[0082] Calculate the comfort zone ratio of the vehicle. If the comfort zone ratio of the vehicle is greater than 30%, adjust the initial blower air volume s, initial compressor speed N, and initial air outlet angle ω according to the preset adjustment amount. Calculate whether the adjusted C(t) is optimal. If it is optimal, then perform temperature control based on the adjusted blower air volume s, compressor speed N, and air outlet angle ω.

[0083] According to the vehicle cabin zoned temperature control method provided in this application, environmental data of the vehicle's location and human characteristic data of at least one area within the vehicle cabin are collected. Based on the environmental data and the human characteristic data of at least one area, the occupant heating / cooling load and human thermal effect calibration factor for each area are calculated. The total load of the corresponding area is calculated based on the occupant heating / cooling load and human thermal effect calibration factor for each area. An optimization function for the corresponding area is determined based on the total load of each area, and a temperature regulation parameter value for the corresponding area is determined based on the optimization function for each area. The temperature of the corresponding area is then controlled according to the temperature regulation parameter value. This solves the problem that current multi-zone air conditioning technologies are mostly based on in-cabin air temperature sensors, failing to fully consider factors related to human thermal perception and lacking accurate response to individual differences. It improves the occupant cabin zoned human comfort and optimizes the vehicle's air conditioning energy consumption while meeting overall comfort requirements.

[0084] This application also provides a vehicle cabin zone temperature control system, please refer to... Figure 4 The vehicle's cabin temperature control system 10 includes: a data acquisition module 100, a calculation module 200, and an optimization module 300.

[0085] The system includes a data acquisition module 100, which collects environmental data of the vehicle's location and human characteristic data of at least one area within the vehicle's cabin; a calculation module 200, which calculates the human thermal load and human thermal effect calibration factor for each area based on the environmental data and the human characteristic data of at least one area, and calculates the total load of the corresponding area based on the human thermal load and human thermal effect calibration factor for each area; and an optimization module 300, which determines the optimization function for the corresponding area based on the total load of each area, and determines the temperature regulation parameter value for the corresponding area based on the optimization function for each area, so as to control the temperature of the corresponding area based on the temperature regulation parameter value for each area.

[0086] In some embodiments, the calculation module 200 is further configured to: calculate a first heat exchange between the vehicle shell and the environment, a second heat exchange between personnel in each area and the external environment, and a third heat exchange between personnel in each area and the external environment based on environmental data and / or human characteristic data of at least one area; calculate the human heating and cooling load of the corresponding area based on the first heat exchange, the second heat exchange between personnel in each area and the external environment, and the third heat exchange between personnel in each area and the external environment, thereby obtaining the human heating and cooling load of each area.

[0087] In some embodiments, the calculation module 200 is further configured to: calculate the blood circulation compensation factor of the corresponding region based on the human characteristic data of the personnel in each region, and calculate the difference between the body temperature of the personnel in each region and the preset body temperature benchmark to obtain the body temperature difference value of each region, and calculate the product of the blood circulation compensation factor of each region and the body temperature difference value of the corresponding region; calculate the ratio of the product of each region to the heart rate coefficient of the personnel in the corresponding region, and calculate the cold and heat load of the personnel in each region based on the ratio of each region, the first heat exchange, the second heat exchange, and the third heat exchange.

[0088] In some embodiments, the calculation module 200 is further configured to: acquire the vehicle's current cabin temperature, cabin shell surface area, vehicle body thickness at its thickest point, solar radiation angle factor for each area, glass reflectivity, sunlight intensity, exposed skin area of ​​personnel, and temperature at at least one location; calculate a second heat exchange based on the solar radiation angle factor, glass reflectivity, and sunlight intensity of each area; obtain a third heat exchange based on the current cabin temperature, exposed skin area of ​​personnel in each area, and temperature at at least one location; and obtain a first heat exchange based on the current ambient temperature, cabin shell surface area, and vehicle body thickness at its thickest point from the environmental data.

[0089] In some embodiments, the calculation module 200 is further configured to: obtain the total number of people in the vehicle cabin, the current cabin temperature, and the temperature of at least one location of the people; and calculate a human thermal effect calibration factor for each region based on the total number of people, the current cabin temperature in the environmental data, and the temperature of at least one location of the people in the human characteristic data of at least one region.

[0090] In some embodiments, the optimization function for each region is: C(t) = w4 * f pmv +w5*EER; EER = Q / P; Where C(t) is the optimization function, P is the power consumption of the compressor, Q is the total load, and w4 is the power of f. pmv The corresponding weighting coefficients, w5 is the weighting coefficient corresponding to EER, f pmv EER represents the overall thermal comfort ratio inside the vehicle.

[0091] In some embodiments, the optimization module 300 is further configured to: collect temperature and humidity parameters for each area within the vehicle cabin; determine the number of areas whose temperature parameters are within a first preset range and whose humidity parameters are within a second preset range based on the temperature and humidity parameters for each area; and obtain the overall thermal comfort ratio within the vehicle based on the ratio of the number of areas to the total number of areas.

[0092] In some embodiments, the optimization module 300 is further configured to: adjust the initial blower air volume, initial compressor speed and initial air outlet angle of the vehicle according to a preset adjustment strategy; calculate the optimization function value corresponding to the adjusted blower air volume, compressor speed and air outlet angle based on the optimization function; and obtain the target blower air volume adjustment parameter value, target compressor speed adjustment parameter value and target air outlet angle adjustment parameter value of the corresponding region when the optimization function value meets the preset minimum value condition.

[0093] It should be noted that the foregoing explanation of the vehicle cabin zone temperature control method embodiment also applies to the vehicle cabin zone temperature control system of this embodiment, and will not be repeated here.

[0094] This application also provides an electronic device, please refer to... Figure 5 The electronic device 20 includes a processor 501 and a memory 502. The memory 501 is used to store computer programs, and the processor 502 is used to execute the programs stored in the memory 501 to implement the vehicle cabin partition temperature control method described in any embodiment of this application.

[0095] This application also provides a vehicle, please refer to the embodiments thereof. Figure 6 The vehicle 30 includes the aforementioned electronic equipment 20.

[0096] In this application, "multiple" refers to two or more.

[0097] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0098] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0099] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0100] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, if a method includes steps A and B, it means that the method may include steps A and B performed sequentially, or it may include steps B and A performed sequentially. For example, if a method may also include step C, it means that step C may be added to the method in any order. For example, the method may include steps A, B, and C, or it may include steps A, C, and B, or it may include steps C, A, and B, etc.

[0101] The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for zoned temperature control in a vehicle cabin, characterized in that, Includes the following steps: Collect environmental data of the vehicle's location and human characteristic data of at least one area inside the vehicle's cabin; Calculate the human thermal load and human thermal effect calibration factor for each region based on the environmental data and / or the human characteristic data of at least one region, and calculate the total load of the corresponding region based on the human thermal load and human thermal effect calibration factor for each region; The optimization function for each region is determined based on the total load of each region, and the temperature regulation parameter value for each region is determined based on the optimization function for each region, so as to control the temperature of the corresponding region according to the temperature regulation parameter value for each region.

2. The method according to claim 1, characterized in that, The calculation of the human thermal load for each area based on the environmental data and / or the human characteristic data of at least one area includes: Calculate the first heat exchange between the vehicle shell and the environment, the second heat exchange between personnel in each area and the external environment, and the third heat exchange between personnel in each area and the external environment based on the environmental data and / or the human characteristic data of at least one area. The heating and cooling load of the personnel in the corresponding area is calculated based on the first heat exchange, the second heat exchange, and the third heat exchange, thus obtaining the heating and cooling load of the personnel in each area.

3. The method according to claim 2, characterized in that, The step of calculating the human heating and cooling load of the corresponding area based on the first heat exchange, the second heat exchange, and the third heat exchange to obtain the human heating and cooling load of each area includes: The blood circulation compensation factor for each region is calculated based on the human characteristic data of the people in each region. The difference between the body temperature of the people in each region and the preset body temperature benchmark is calculated to obtain the body temperature difference value of each region. The product of the blood circulation compensation factor and the body temperature difference value of the corresponding region is also calculated. Calculate the product of each region and the ratio of the heart rate coefficient of the corresponding region, and calculate the heat load of the people in each region based on the ratio of each region, the first heat exchange, the second heat exchange, and the third heat exchange.

4. The method according to claim 2, characterized in that, The calculation of the first heat exchange between the vehicle shell and the environment, the second heat exchange between personnel in each area and the external environment, and the third heat exchange between personnel in each area and the external environment based on the environmental data and / or the human characteristic data of at least one area includes: Acquire the vehicle's current cabin temperature, cabin shell surface area, vehicle body thickness at its thickest point, solar radiation factor for each area, glass reflectivity, sunlight intensity, exposed skin area of ​​personnel, and temperature at at least one location; The second heat exchange is calculated based on the solar angle factor of each region, the glass reflectivity, and the sunlight intensity. The third heat exchange is obtained based on the current cabin temperature, the area of ​​exposed skin of the personnel in each region, and the temperature at at least one location. The first heat exchange is obtained based on the current ambient temperature, the surface area of ​​the cabin shell, and the thickness of the thickest part of the vehicle body from the environmental data.

5. The method according to claim 1, characterized in that, Calculate the human thermal effect calibration factor for each region based on the environmental data and the human characteristic data of the at least one region, including: The system obtains the total number of people in the vehicle cabin, the current cabin temperature from the environmental data, and the temperature of at least one location of a person from the human characteristic data of at least one area. The human thermal effect calibration factor for each region is calculated based on the total number of people, the current cabin temperature, and the temperature at at least one location of the people.

6. The method according to claim 1, characterized in that, The optimization function for each region is: C(t)=w4*f pmv +w5*EER? EER = Q / P; Where C(t) is the optimization function, P is the power consumption of the compressor, Q is the total load, and w4 is the power of f. pmv The corresponding weighting coefficients, w5 is the weighting coefficient corresponding to EER, f pmv EER represents the overall thermal comfort ratio inside the vehicle.

7. The method according to claim 6, characterized in that, Calculate the overall thermal comfort ratio inside the vehicle, including: Collect temperature and humidity parameters for each area inside the vehicle cabin; Based on the temperature and humidity parameters of each region, determine the number of regions where the temperature parameter is within a first preset range and the humidity parameter is within a second preset range; The overall thermal comfort ratio inside the vehicle is obtained by the ratio of the number of said areas to the total number of areas.

8. The method according to claim 1, characterized in that, The step of determining the temperature regulation parameter value for the corresponding region based on the optimization function of each region includes: The vehicle's initial blower air volume, initial compressor speed, and initial air outlet angle are adjusted according to a preset adjustment strategy. Based on the optimization function, calculate the optimization function values ​​corresponding to the adjusted blower air volume, compressor speed and air outlet angle; When the optimization function value satisfies the preset minimum value condition, the target blower air volume adjustment parameter value, the target compressor speed adjustment parameter value, and the target air outlet angle adjustment parameter value for the corresponding region are obtained.

9. An electronic device, characterized in that, Including processor and memory, among which Memory, used to store computer programs; A processor for executing a program stored in memory to implement the cabin partition temperature control method for the vehicle as described in any one of claims 1-8.

10. A vehicle, characterized in that, It includes the electronic device as described in claim 9.

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