Automobile seat ventilation parameter determination method and device and computer

Abstract

The invention relates to an automobile seat ventilation parameter determination method and device and a computer. The method comprises the steps that three-dimensional contour information, object physiological information and in-car environment information of a target object on a car seat are acquired; according to the physiological information of the object and the in-vehicle environment information, comfort analysis is carried out, and comfortable physiological information is determined; taking the comfortable physiological information as a target condition, and constructing ventilation duct information of the automobile seat according to the three-dimensional contour information; inputting the comfort physiological information and the ventilation air duct information into a fan control model to obtain initial fan working parameters corresponding to each fan; performing ventilation simulation according to the initial fan working parameters to obtain fan working information corresponding to each fan; for any fan, performing energy-saving optimization on the initial fan working parameters according to the fan working information to obtain target fan working parameters; and fusing the working parameters of each target fan to obtain the seat ventilation parameters of the automobile seat. By adopting the method, the seat ventilation effect can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent vehicles, and particularly to a method, device and computer for determining ventilation parameters of an automotive seat. Background Art

[0002] In traditional technologies, seat ventilation technology mainly relies on users to manually adjust the seat air volume or seat ventilation mode. During use, users can select different air volume levels or ventilation intensities through buttons or touchscreens in the vehicle, and combine preset modes to ventilate different seat areas (such as the back, seat cushion, etc.). However, the seat ventilation technology of traditional technologies cannot automatically optimize the ventilation effect according to factors such as the physical condition of vehicle occupants, environmental changes, or driving time, resulting in poor seat ventilation effects. Summary of the Invention

[0003] Based on this, in view of the above technical problems, it is necessary to provide a method, device and computer for determining ventilation parameters of an automotive seat that can improve the seat ventilation effect.

[0004] In a first aspect, the present application provides a method for determining ventilation parameters of an automotive seat, including: Obtaining three-dimensional contour information of a target object on an automotive seat, object physiological information of the target object, and in-vehicle environment information; Performing a comfort analysis on the target object according to the object physiological information and the in-vehicle environment information to determine comfortable physiological information of the target object; Taking the comfortable physiological information as a target condition, constructing ventilation duct information of the automotive seat according to the three-dimensional contour information; Inputting the comfortable physiological information and the ventilation duct information into a fan control model of the automotive seat to obtain initial fan working parameters corresponding to each fan in the automotive seat; Performing ventilation simulation on the automotive seat according to the initial fan working parameters to obtain fan working information corresponding to each fan; For any one of the fans, performing energy-saving optimization on the initial fan working parameters according to the fan working information to obtain target fan working parameters corresponding to the fan; Fusing the target fan working parameters to obtain seat ventilation parameters of the automotive seat.

[0005] In a second aspect, the present application further provides a device for determining ventilation parameters of an automotive seat, including: An information acquisition module, configured to acquire three-dimensional contour information of a target object on an automotive seat, object physiological information of the target object, and in-vehicle environment information; An information analysis module, configured to perform a comfort analysis on the target object according to the physiological information of the object and the in-vehicle environment information, and determine the comfortable physiological information of the target object; An air duct construction module, used to construct ventilation air duct information of the automobile seat according to the three-dimensional contour information, taking the comfortable physiological information as a target condition; A parameter calculation module, used for inputting the comfort physiological information and the ventilation duct information into the fan control model of the car seat to obtain initial fan operating parameters corresponding to each fan in the car seat; A ventilation simulation module, used to perform ventilation simulation on the car seat according to the initial fan operating parameters, and obtain fan operating information corresponding to each fan; A parameter optimization module, for performing energy-saving optimization on the initial fan operating parameters according to the fan operating information for any of the fans, to obtain target fan operating parameters corresponding to the fan; The parameter fusion module is used to fuse the target fan operating parameters to obtain the seat ventilation parameters of the vehicle seat.

[0006] In a third aspect, the present application further provides a computer, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any step of a method for determining vehicle seat ventilation parameters when executing the computer program.

[0007] The above-mentioned method, device and computer for determining ventilation parameters of automobile seats comprehensively obtain the three-dimensional contour information, individual physiological characteristics (such as body temperature, sweating, metabolic rate, etc.) of the target passenger on the automobile seat and real-time in-vehicle environmental parameters (such as temperature, humidity, air flow, etc.), and then carry out multi-dimensional comfort analysis on this basis to accurately determine the optimal comfortable physiological state of the passenger in the current environment. Then, with the comfort state as the core goal, the personalized ventilation duct structure information is intelligently constructed in combination with the three-dimensional contour data of the seat, and it is input into the fan control model together with the comfort physiological information to obtain the initial working parameters of each fan. Further, the simulation method is used to simulate and evaluate the ventilation effect to obtain the actual working information of the fan, and based on this, the initial parameters are optimized and adjusted with energy saving orientation to obtain the optimal energy-saving working parameters of each fan under the premise of ensuring comfort. Finally, the target parameters of all fans are integrated to form an overall seat ventilation control scheme, which can improve the seat ventilation effect and realize the intelligent and personalized adjustment of the seat ventilation system while improving individual comfort and taking into account energy efficiency, which significantly improves the comfort management level and energy utilization efficiency of the whole vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] To more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the accompanying drawings required in the description of the embodiments or the related art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0009] Figure 1 It is an application environment diagram of a method for determining automobile seat ventilation parameters in an embodiment; Figure 2 It is a schematic flowchart of a method for determining automobile seat ventilation parameters in an embodiment; Figure 3 It is a schematic flowchart of a first method for constructing ventilation duct information in an embodiment; Figure 4 It is a schematic flowchart of a second method for constructing ventilation duct information in an embodiment; Figure 5 It is a schematic flowchart of a first method for obtaining initial fan operating parameters in an embodiment; Figure 6 It is a schematic flowchart of a second method for obtaining initial fan operating parameters in an embodiment; Figure 7 It is a structural block diagram of an automobile seat ventilation parameter determination device in an embodiment; Figure 8 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0010] In order to make the objectives, technical solutions and advantages of the present application clearer, the following further details the present application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0011] A method for determining automobile seat ventilation parameters provided by an embodiment of the present application can be applied to, for example, Figure 1 the application environment shown. Among them, the terminal 102 communicates with the server 104 through a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed in the cloud or other network servers. Among them, the server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0012] In an exemplary embodiment, as Figure 2 shown, a method for determining automobile seat ventilation parameters is provided, and this method is applied to Figure 1Taking the server in as an example, the following steps 202 to 214 are included. Among them: Step 202, obtain the three-dimensional contour information of the target object on the vehicle seat, the physiological information of the target object, and the in-vehicle environment information.

[0013] Among them, the three-dimensional contour information can be the body surface contact form and spatial distribution characteristics of the target object on the vehicle seat obtained through sensors (such as a pressure sensor array, an infrared depth camera, or a laser scanning device), including the concave and convex structures and sitting posture contours in areas such as the back, waist, buttocks, and thighs.

[0014] Among them, the physiological information of the object can be various physiological parameters related to the physical state of the occupant, such as one or more of body temperature, heart rate, skin humidity, sweating amount, metabolic rate, etc.

[0015] Among them, the in-vehicle environment information can be the climate and air state data in the current vehicle cockpit, including one or more of air temperature, relative humidity, wind speed, air quality (such as CO2 concentration), light intensity, etc.

[0016] Specifically, through devices such as a pressure sensor array, an infrared camera, or a lidar installed on the vehicle seat, the three-dimensional contour data of the contact area between the occupant and the seat is collected in real time to reflect their sitting posture and body shape characteristics; at the same time, the physiological information of the occupant, such as one or more of body temperature, heart rate, skin electrical response, sweating amount, etc., is collected through wearable physiological sensing devices or physiological monitoring modules integrated in the seat; in addition, one or more in-vehicle environment information such as in-vehicle temperature and humidity, air flow rate, and light intensity are collected through in-vehicle environment sensors.

[0017] Step 204, based on the physiological information of the object and the in-vehicle environment information, perform a comfort analysis on the target object to determine the comfortable physiological information of the target object.

[0018] Among them, the comfort analysis can be a process of comprehensively evaluating the current thermal comfort state of the occupant based on the physiological information of the object and the in-vehicle environment information. Usually, a thermal comfort model (such as the PMV / PPD model, the Fanger model) or an intelligent algorithm (such as a machine learning classifier) is used to predict the subjective feelings of the occupant, judge whether they are in the comfort interval, and identify the specific physiological reasons for deviating from comfort (such as local overheating, dampness, etc.).

[0019] Among them, the comfortable physiological information can be the target values of physiological parameters that should be possessed to enable the occupant to reach the optimal thermal comfort state in a specific in-vehicle environment, such as the ideal skin temperature, the desired local wind speed, or the appropriate humidity level.

[0020] Specifically, the obtained physiological information of the occupant (such as body temperature, heart rate, skin humidity, sweating rate, etc.) is fused with the in-vehicle environment information (including cockpit temperature, humidity, air velocity, CO2 concentration, light intensity, etc.), and the comfort of the current riding state is analyzed by constructing a thermal comfort evaluation model. The thermal comfort evaluation model can be based on the PMV / PPD model, the Fanger model, or a multi-parameter regression network trained by machine learning to evaluate whether the passenger is currently in the comfort range. If the current state deviates from the comfort standard, the human thermoregulation mechanism is further combined to predict the target physiological parameters required for the occupant to return to the thermal balance or the optimal perception state in the current environment, such as the ideal skin temperature, the desired local wind speed, the optimal humidity perception value, etc.; the obtained comfort physiological information not only reflects the subjective comfort needs of the occupant, but also provides an objective and quantitative target reference for the subsequent adjustment of the ventilation system.

[0021] Step 206: Taking the comfort physiological information as the target condition, construct the ventilation duct information of the vehicle seat according to the three-dimensional contour information.

[0022] Among them, the ventilation duct information can be a set of structural parameters of the internal air circulation path of the seat constructed based on the three-dimensional contour and the comfort physiological requirements, including the duct orientation, the outlet distribution, the duct size, the wind resistance coefficient, the connection relationship, etc.

[0023] Specifically, according to the three-dimensional contour information of the occupant, reconstruct the three-dimensional structure model of the contact area between the occupant and the seat, and identify the spatial distribution characteristics of the key contact parts such as the occupant's back, buttocks, and thighs; combined with the determined comfort physiological information as the target condition (such as local temperature adjustment requirements, desired wind speed, ventilation uniformity, etc.), use computer-aided design tools (such as CAD, CFD simulation platform) to model and simulate the ventilation structure inside the seat. During the modeling and simulation process, factors such as the duct layout, the number and position of the outlets, the air flow direction, and the wind resistance distribution are comprehensively considered to ensure that the ventilation system can efficiently and directionally deliver air flow to the key heat areas of the human body while conforming to the human body contour, meeting the personalized thermoregulation requirements. Moreover, by using the method of multi-round modeling and simulation iteration, optimize the duct smoothness and structural feasibility to generate personalized ventilation duct information that highly matches the physiological comfort requirements of the occupant.

[0024] Step 208: Input the comfort physiological information and the ventilation duct information into the fan control model of the vehicle seat to obtain the initial fan working parameters corresponding to each fan in the vehicle seat.

[0025] Among them, the fan control model can be a mathematical or data-driven model that converts the input comfort physiological information and ventilation duct information into specific fan control instructions, and can adopt a rule-based control logic, physical modeling, or a neural network structure based on deep learning.

[0026] Among them, the initial fan operating parameters can be the initial operating set values assigned by the system to each fan after the fan control model is calculated, usually including the fan speed, output air volume, wind direction angle, start time, and operating duration, etc.

[0027] Specifically, the constructed ventilation duct information and the comfortable physiological information of the occupant are jointly used as inputs and fed into a pre-established fan control model. The fan control model is based on physical modeling, preset control rules, or uses deep learning methods to construct a multi-input multi-output (MIMO) predictive control network, which has the ability to accurately predict the fan response under different working conditions. The fan control model calculates the initial operating parameters required for each fan according to the layout characteristics of the ventilation duct in the ventilation duct information (such as the distance from each air outlet to the target area, air resistance, and local ventilation capacity) and the comfortable physiological information required by the occupant (such as the back wind speed, hip temperature, and leg humidity, etc.), including fan speed, air volume, operating time, start-stop rhythm, etc. Among them, this set of initial parameters aims to achieve distributed and regional regulation of the fan on the basis of meeting the target comfortable physiological information.

[0028] Step 210, perform ventilation simulation on the vehicle seat according to the initial fan operating parameters to obtain the fan operating information corresponding to each fan.

[0029] Among them, the fan operating information can be the operating state data of each fan under the action of the initial parameters collected through ventilation simulation or actual operation, reflecting the flow situation of the air flow inside the seat, wind speed distribution, cooling effect, temperature and humidity changes, etc., which is used to evaluate whether the initial setting reaches the expected comfort effect and provide a basis for energy-saving optimization at the same time.

[0030] Specifically, perform ventilation simulation on the vehicle seat according to the initial fan operating parameters. During the process of obtaining the fan operating information through ventilation simulation, based on the initial operating parameters generated by the fan control model and combined with the constructed ventilation duct structure, the computational fluid dynamics (CFD) simulation method is used to dynamically simulate the ventilation process inside the seat. Among them, physical phenomena such as the flow path of the air flow in the complex duct, wind speed distribution, pressure drop change, heat exchange process, and humidity migration need to be considered during the simulation to truly reflect the transmission efficiency and distribution uniformity of the air flow in different regions under the current initial fan configuration. The air flow temperature and humidity field distribution, wind speed field image output by the simulation, and the microenvironment parameters of the human contact parts corresponding to each air outlet are further analyzed according to the above output data to analyze the specific working state of each fan, including its influence degree on the target comfort area, cooling or drying effect, and whether there are problems such as over-ventilation or insufficient ventilation, so as to obtain detailed fan operating information.

[0031] Step 212: For any blower, optimize the initial blower operating parameters for energy conservation according to the blower operating information to obtain the corresponding target blower operating parameters for the blower.

[0032] Among them, energy conservation optimization can be a process of calculating and adjusting the operating parameters of the blower on the premise of maintaining the comfort of the occupants, aiming to reduce the energy consumption of the blower and reduce unnecessary air flow output.

[0033] Among them, the target blower operating parameters can be the optimal operating settings finally determined for each blower after energy conservation optimization, including the optimized air volume, rotation speed, operating duration, wind direction, etc., which can not only meet the target comfort physiological information but also minimize energy consumption to the greatest extent.

[0034] Specifically, however, each blower may be inefficient or energy-consuming in the current working environment. Therefore, first evaluate whether there is energy waste in the current blower operating state, such as excessive air volume, redundant wind speed, or cooling range exceeding the target area, etc., and set an optimization objective function based on the premise of maintaining comfort, such as minimizing energy consumption or blower load. Subsequently, use optimization algorithms (such as genetic algorithms, particle swarm optimization, gradient descent, etc.) to iteratively adjust the initial operating parameters of the blower on the premise of ensuring that the blower maintains the target comfort physiological parameters within its control area, and find the optimal balance point, so as to obtain the target operating parameters of the blower. Among them, the target operating parameters not only meet the personalized needs of the occupants in terms of heat sensation, moisture sensation, wind sensation, etc., but also achieve the minimization of energy utilization.

[0035] Step 214: Integrate the target blower operating parameters of each blower to obtain the seat ventilation parameters of the vehicle seat.

[0036] Among them, the seat ventilation parameters can be a set of seat-level ventilation control configurations formed after integrating and fusing the target operating parameters of all blowers. This parameter set is used to guide the overall operation strategy of the ventilation system, realize the coordinated work among multiple blowers, and thus build an intelligent seat ventilation system that can adaptively adjust, be energy-saving and efficient, and meet individual needs.

[0037] Specifically, in the process of integrating the working parameters of each target fan to generate the seat ventilation parameters, it is necessary to uniformly integrate the target working parameters obtained after energy-saving optimization of all fans, and construct a set of coordinated and efficient seat ventilation control strategies. Therefore, the integration process not only considers the independent operating states of each fan within its control area, but also comprehensively analyzes the mutual influence relationships between the fans, such as air flow superposition, air flow interference, ventilation overlap in the boundary area, etc., to ensure the coordination and consistency of the local and global parts during the operation of the overall ventilation system. At the same time, a real-time feedback mechanism is also combined to uniformly schedule the starting sequence, operating rhythm, air volume ratio, etc. of different fans, so that while the entire seat meets the personalized comfort needs of the occupants, it realizes the dynamic balance of thermal management and the optimal allocation of ventilation resources. The finally formed seat ventilation parameters will be used as the centralized control instructions for the fan group and input into the execution control system.

[0038] In the above method for determining the ventilation parameters of an automotive seat, by comprehensively obtaining the three-dimensional contour information of the target occupant on the automotive seat, individual physiological characteristics (such as body temperature, sweating amount, metabolic rate, etc.), and real-time in-vehicle environment parameters (such as temperature, humidity, air flow, etc.), a multi-dimensional comfort analysis is carried out on this basis to accurately determine the optimal comfortable physiological state of the occupant in the current environment. Subsequently, with this comfortable state as the core goal, the personalized ventilation duct structure information is intelligently constructed in combination with the three-dimensional contour data of the seat, and it is input into the fan control model together with the comfortable physiological information to obtain the initial working parameters of each fan. Further, simulation means are used to simulate and evaluate the ventilation effect, obtain the actual working information of the fans, and based on this, optimize and adjust the initial parameters in an energy-saving direction to obtain the optimal energy-saving working parameters of each fan while ensuring comfort. Finally, the target parameters of all fans are integrated to form an overall seat ventilation control scheme, which can improve the seat ventilation effect and realize the intelligent and personalized adjustment of the seat ventilation system while improving individual comfort, and significantly improve the overall vehicle comfort management level and energy utilization efficiency.

[0039] In an exemplary embodiment, as Figure 3 shown, taking the comfortable physiological information as the target condition, the ventilation duct information of the automotive seat is constructed according to the three-dimensional contour information, including steps 302 to 304. Among them: Step 302, taking the comfortable physiological information as the target condition, construct a heat exchange equation set for the automotive seat according to the three-dimensional contour information.

[0040] Among them, the heat exchange equation set can be a set of mathematical models describing the air flow and heat transfer processes inside the automotive seat, usually including the energy conservation equation, heat conduction equation, convective heat transfer formula, and boundary condition definition, etc.

[0041] Specifically, in the process of constructing the heat exchange equation set of the vehicle seat based on the three-dimensional contour information with the comfortable physiological information as the target condition, first, a spatial model that matches the sitting posture and body shape of the occupant is constructed according to the high-precision three-dimensional contour data of the contact area between the occupant and the seat; combined with the comfortable physiological information of the occupant (such as the expected skin surface temperature, ideal heat dissipation rate, local heat flux density, etc.), the contact area between the human body and the seat is regarded as the heat exchange interface, and considering the flow characteristics of air in the air duct, a heat exchange equation set covering various heat transfer mechanisms such as conduction, convection, and radiation is established. Among them, the heat exchange equation set must take variables such as wind speed, temperature, pressure, contact area, thermal conductivity, and local sitting pressure distribution as input parameters to accurately describe the heat energy transfer path and intensity between the human body and the seat at different positions and conditions.

[0042] Step 304, according to the heat exchange equation set, perform heat exchange shape mapping on the ventilation air duct of the vehicle seat to obtain ventilation air duct information.

[0043] Among them, the heat exchange shape mapping can be a process of dynamically adjusting and optimizing the geometric structure of the internal air duct of the vehicle seat on the basis of constructing the heat exchange equation set to achieve the optimal heat transfer effect in the key areas in contact with the human body. This mapping process combines the heat simulation results and three-dimensional contour data to perform iterative design on the path, cross-sectional size, air outlet position, etc. of the air duct to ensure that the heat flow is efficiently transferred in the expected direction, so as to meet the comfort requirements of the occupant in local areas (such as the back, buttocks, etc.).

[0044] Specifically, based on the constructed heat exchange equation set as the physical model, according to the three-dimensional contour data and comfortable physiological information of the occupant, through numerical simulation means (such as finite element analysis or computational fluid dynamics simulation), multiple rounds of geometric transformation and optimization iteration are performed on the air duct structure inside the seat, including adjusting key parameters such as the air duct path, cross-sectional size, air outlet position and angle, so that the heat can be transferred in the optimal way at the contact interface between the seat and the human body, realizing efficient cooling or ventilation in local areas. At the same time, engineering constraints such as the continuity of air flow, wind resistance loss, and uniformity of air flow distribution are also considered in the above calculations to ensure that while meeting the personalized thermal comfort requirements of the occupant, the energy efficiency and structural feasibility of the entire system are improved, and finally the ventilation air duct information is generated.

[0045] In this embodiment, by taking the comfortable physiological information of the occupant as the target condition and combining the three-dimensional contour information of the occupant on the seat, a heat exchange equation set that accurately describes the heat transfer process between the human body and the seat is constructed. Based on this, a heat exchange shape mapping is performed on the internal ventilation air ducts of the seat, thereby generating ventilation air duct information that efficiently matches the individual heat comfort requirements. It can be realized that the seat ventilation system fully considers the personalized heat regulation requirements and actual contact states of the occupants at the structural design stage, making the ventilation path layout more reasonable, the air flow coverage more accurate, and the heat exchange efficiency higher, significantly improving the local adjustment ability and overall comfort performance of the seat. At the same time, it provides accurate and structured basic support for subsequent fan control and energy-saving optimization.

[0046] In an exemplary embodiment, as Figure 4 shown, according to the heat exchange equation set, a heat exchange shape mapping is performed on the ventilation air ducts of the vehicle seat to obtain ventilation air duct information, including steps 402 to 404. Among them: Step 402, according to the heat exchange equation set, perform a heat exchange shape mapping on the ventilation air ducts to obtain air duct shape data.

[0047] Among them, the heat exchange shape mapping can be an optimization process that, under the theoretical guidance of the heat exchange equation set, maps the spatial distribution result of the heat transfer efficiency between the human body and the seat to the geometric structure of the internal ventilation air ducts of the seat, thereby guiding the air duct shape design.

[0048] Among them, the air duct shape data can be a parameter set obtained after completing the heat exchange shape mapping and used to describe the geometric structure of the internal ventilation air ducts of the vehicle seat. This data includes information such as the three-dimensional path of the air duct, the change in cross-sectional dimensions, the bending angle, and the position and direction of the air outlet, and is the basic form for digitally expressing the air duct layout and structural characteristics.

[0049] Specifically, a spatial correspondence relationship is established between the three-dimensional contour model of the occupant and the internal structure of the seat. Based on this geometric basis, combined with the set heat exchange equation set, a simulation model is established for the ventilation air ducts that may be arranged in the seat. The heat exchange equation set comprehensively considers the convective heat transfer generated by the air flowing in the air duct, the conductive heat transfer between the air duct wall surface and the contact area of the human body, and the thermal energy of the possible thermal radiation effect during the calculation process. The heat exchange equation set is solved by a CFD (Computational Fluid Dynamics) simulation tool, and a thermal response simulation is performed on multiple air duct layout schemes to analyze the efficiency and uniformity of heat exchange achieved by different structures in each key contact area (such as the back, waist, legs, etc.), thereby mapping the heat exchange performance to the specific air duct shape. Finally, the preliminary air duct structure that meets the heat exchange requirements is extracted, including parameters such as the air duct direction, width change, air outlet position and angle, etc., to generate air duct shape data.

[0050] In one embodiment, the heat exchange equation set includes a fluid continuity equation, an air momentum equation, a temperature transport equation, and a humidity transport equation. The expression of the fluid continuity equation is The expression of the air momentum equation is The expression of the temperature transport equation is The expression of the humidity transport equation is Where is the fluid velocity vector, obtained by measurement with a sensor; is the air density, determined by referring to the standard air property table or the built-in database of CFD software, p is the air static pressure, obtained by measurement with a sensor, is the air viscosity, by referring to the standard air property table or the built-in database of CFD software, is the spatial coordinate along the air duct x The airflow permeability varying with is obtained by simulation based on the seat material and the air duct layout; is the Forchheimer coefficient, pre-calibrated according to the specific material; T is the air specific heat capacity, determined by referring to the standard air property table or the built-in database of CFD software, is the temperature field, obtained by measurement with a sensor, is the spatial coordinate along the air duct x The heat source term data varying with H is given by measurement or design specifications; D is the humidity field, obtained by measurement with a sensor, is the spatial coordinate along the air duct x The humidity quantity varying with

[0051] Step 404: Iteratively optimize the air duct shape data according to the influencing factors of the comfort physiological information to obtain the ventilation air duct information.

[0052] Among them, the influencing factors can be key variables that directly affect the comfort experience of passengers or the operating performance of the system during the optimization design of the ventilation duct. They mainly include the local temperature requirements, wind speed perception, and humidity adjustment requirements in the comfort physiological information, as well as the heat exchange efficiency, airflow distribution uniformity, and wind resistance related to the duct structure.

[0053] Specifically, based on the duct shape data, various influencing factors of the personalized comfort physiological needs of passengers are further introduced as the constraint conditions of the optimization objective function. These influencing factors include the expected skin temperature range, local wind speed perception, humidity adjustment requirements, heat flux density distribution, etc. Using multi-objective optimization algorithms (such as genetic algorithms, response surface methods, particle swarm optimization, etc.), the geometric parameters of the duct (such as path curvature, cross-sectional dimensions, outlet direction and position) are automatically adjusted, and after each shape update, the response effect of its heat exchange performance on the target area is re-verified through the heat exchange equation set. The iterative process controls the flow resistance and structural complexity while optimizing the thermal efficiency to ensure that the duct not only meets the personalized regulation of thermal comfort but also has engineering feasibility. Through multiple rounds of iteration, it finally converges to a duct structure that achieves an optimal balance among comfort, ventilation uniformity, and energy efficiency, and obtains the ventilation duct information that matches the needs of the passengers.

[0054] In one embodiment, the calculation expression of the ventilation duct information is Among them, is the ventilation duct information, is the temperature weight coefficient, determined by the real-time temperature, is the humidity weight coefficient, determined by the real-time humidity, is the pressure weight coefficient, determined by the real-time pressure, T opt is the target temperature, determined by ergonomics or medical literature, H opt is the target humidity, determined by ergonomics or medical literature, p eff is the target pressure, measured from the seat pressure sensor, p opt is the passenger's body sensation pressure, determined by ergonomics or medical literature, is the regularization coefficient of the duct distribution function, determined according to the simulation of suppressing severe oscillations, is the spatial gradient term of the duct distribution function, determined from the field of variational optimization or topology / shape optimization, is the duct distribution quantity, is the contact surface between the seat and the passenger, obtained from the seat shape or 3D scanning, is the three-dimensional volume domain inside the seat, obtained based on the three-dimensional contour of the seat CAD model or physical measurement. T is the temperature field, obtained by sensor measurement. H is the humidity field, obtained by sensor measurement.

[0055] In this embodiment, by performing a heat exchange shape mapping on the ventilation air duct based on the heat exchange equation set, the air duct shape data is initially obtained, and combined with each key influencing factor (such as local temperature, humidity, and wind feeling requirements) in the comfortable physiological information of the occupant, the shape data is iteratively optimized in multiple rounds, so as to generate ventilation air duct information that highly conforms to the individual heat regulation requirements. It not only fully considers the heat exchange characteristics and air flow response characteristics between the human body and the seat, but also achieves the optimal balance between the efficiency and comfort of the air duct structure, significantly improving the local control accuracy, overall thermal comfort performance, and energy-saving operation ability of the ventilation system, providing a solid structural basis and algorithm support for the personalized and intelligent thermal management of the seat.

[0056] In an exemplary embodiment, as Figure 5 shown, the comfortable physiological information and the ventilation air duct information are input into the fan control model of the automotive seat to obtain the initial fan operating parameters corresponding to each fan in the automotive seat, including steps 502 to 510. Among them: Step 502, according to the comfortable physiological information, partition the automotive seat to obtain each automotive seat partition information.

[0057] Among them, the automotive seat partition information can be a data set formed by dividing the entire seat into multiple relatively independent regions according to the human body contact characteristics and functional requirements. Each partition corresponds to a specific part of the occupant's body, such as the upper back, lower back, waist, buttocks, and thighs, etc., and has independent ventilation control logic and physical position attributes.

[0058] Specifically, based on the three-dimensional contour data of the occupant, identify the main areas in contact with the seat, and combine the layout results of the pressure sensors to establish a contact intensity distribution map between the occupant and the seat; then divide the seat into several thermal regulation control units, usually including areas such as the upper back, lower back, waist, buttocks, and thighs, and each area has a relatively independent air flow circulation path and fan control range. At the same time, referring to the local thermal regulation requirements in the comfortable physiological information (such as the back is more prone to sweating and needs enhanced ventilation, and the waist is sensitive and needs gentle regulation), further refine the area boundaries, so that the partition not only conforms to the ergonomic structure, but also closely corresponds to the thermal comfort regulation target. Finally, generate the geometric, functional, and regulation range data of each seat partition to form the seat partition information.

[0059] Step 504, intercept the partition comfort information corresponding to each automotive seat partition information from the comfortable physiological information.

[0060] Among them, the zone comfort information can be personalized thermal comfort demand data extracted for each seat zone, including the expected skin surface temperature, ideal wind speed, humidity adjustment target and thermal sensitivity of the area.

[0061] Specifically, the overall comfort physiological information is mapped and matched according to the designated seat partitions, and the local comfort demand data corresponding to each area is extracted from the comfort physiological information as the partition comfort information, where each partition comfort information includes parameters such as target skin temperature, ideal wind speed range, humidity adjustment requirements, local thermal sensitivity, etc., reflecting the personalized expectations of the passengers for the thermal environment in different parts of the body. For example, the back area may require a higher ventilation intensity to cope with more sweating, while the waist may need to maintain a more stable temperature to prevent cold and hot stimulation.

[0062] Step 506, for any automobile seat partition information, calculate the pressure amplification information and the local corrected heat load corresponding to the automobile seat partition information according to the partition comfort information.

[0063] Among them, the pressure amplification information can be an indicator calculated based on the seat pressure sensor data, which is used to indicate the degree of influence of the contact pressure of the occupant in a specific seat partition on the ventilation effect. High contact pressure usually means that the airflow into the area is restricted and the heat accumulation phenomenon is obvious. Therefore, the system models this influence through the amplification factor as an important reference for enhancing the local adjustment response, so that the high-pressure area can obtain higher priority and air volume support in the fan control.

[0064] The local corrected heat load can be the amount of heat that needs to be compensated or removed in a specific seat partition to achieve a thermal comfort state consistent with the partition comfort information. It is calculated based on the difference between the current environmental parameters (temperature, humidity), human metabolic rate, clothing thermal resistance, and the expected target value, reflecting the cooling or heating intensity requirements of the area.

[0065] Specifically, for any car seat partition information, based on the partition comfort information of the car seat partition information (such as expected temperature, target wind speed, humidity comfort range, etc.), the gap between the current environment and the ideal state is judged, and the direction of the heat or ventilation intensity that needs to be adjusted in the area is clarified; then, combined with the contact pressure and area data of the area obtained by the seat pressure sensor, the pressure amplification information is calculated. The pressure amplification information is used to indicate the degree to which the airflow is difficult to enter the area due to human body pressure, thereby serving as an enhancement factor for the adjustment intensity. At the same time, the temperature and humidity target values ​​in the partition comfort information are linked with factors such as the current environmental state, the metabolic heat generation rate of the occupant, and the thermal resistance of clothing to calculate the local corrected heat load, that is, the heat or cooling capacity required to compensate for thermal comfort in the area.

[0066] Step 508: Multiply the pressure amplification information by the local correction heat load to obtain the zoning demand information.

[0067] Among them, the zoning demand information can be a comprehensive index obtained by multiplying the pressure amplification information by the local correction heat load, which is used to quantify the ventilation adjustment intensity required for each seat zone under actual working conditions. It comprehensively considers the magnitude of the thermal comfort demand and the actual ventilation difficulty, and represents the priority of the adjustment resources that should be allocated to this area in the fan control.

[0068] Specifically, since the local correction heat load represents the heat adjustment or cooling capacity required for this area due to the difference between the current environment and the target comfort state, and the pressure amplification information reflects the ventilation difficulty or heat accumulation trend caused by physical factors such as large human contact pressure and airflow restriction in this area. By multiplying the two, not only the demand for the "quantity" of adjustment is considered, but also the enhancement factor of the adjustment "difficulty" is introduced, making the final zoning demand information more in line with the actual use scenario, and reflecting the adjustment priority under the superposition of multiple factors such as thermal non-uniformity, local sensitivity, and air flow resistance.

[0069] Step 510: Adjust the operating parameters of each fan of the vehicle seat according to the zoning demand information and the ventilation duct information to obtain the initial fan operating parameters corresponding to each fan.

[0070] Specifically, determine factors such as the geometric shape, flow resistance, air outlet efficiency, and air flow coupling relationship with adjacent areas of the air duct in this area according to the ventilation duct information, and evaluate the ability and response speed of the fan to deliver air to this area during actual operation; then combine the matching degree between the zoning demand information and the air duct capacity obtained above, and dynamically adjust the initial operating parameters of each fan, including rotation speed, output air volume, working duration, start time, etc., so that it can meet the personalized thermal adjustment needs of the zone. At the same time, a global coordination mechanism is also used to avoid air flow interference or resource waste between fans, ensure that the overall ventilation system of the seat operates efficiently while achieving the comfort target, and generate the initial fan operating parameters.

[0071] In this embodiment, by dividing the vehicle seat based on comfort physiological information, extracting the local comfort demand corresponding to each zone, and further combining the pressure distribution and heat load demand, the accurate zoning adjustment intensity, that is, the zoning demand information, is calculated. On this basis, this demand information is combined with the structural characteristics of the ventilation duct to accurately adjust the operating parameters of each fan, and generate the initial fan operating parameters that meet the actual needs. It realizes the transformation of seat ventilation control from "overall adjustment" to "local precise control", not only improving the matching degree of personalized thermal comfort, but also improving the efficiency and responsiveness of fan operation, effectively reducing system energy consumption, and enhancing the intelligent level and user experience of the ventilation system.

[0072] In an exemplary embodiment, as Figure 6 shown, according to the partition demand information and the ventilation duct information, the operating parameters of each blower of the vehicle seat are adjusted to obtain the initial blower operating parameters corresponding to each blower, including steps 602 to 608. Among them: Step 602, calculate the target air volume corresponding to each blower according to the partition demand information and the ventilation duct information.

[0073] Among them, the target air volume can be the volume of air that the blower needs to deliver within a specific time period to meet the thermal comfort requirements of a specific seat partition, usually in cubic meters per hour (m³ / h). It is a key parameter comprehensively calculated based on the heat load demand of the partition, the air temperature and humidity regulation target, and the duct transmission capacity, and is used to guide the blower to output an appropriate air flow intensity, so as to achieve effective cooling, drying, or ventilation adjustment of the local area.

[0074] Specifically, establish the mapping relationship between the duct area controlled by each blower and the seat partition, clarify the target area corresponding to each blower for adjustment, then input the partition demand information of this area as the thermal comfort target, and combine the information of the ventilation duct, such as duct length, cross-sectional area, air flow resistance, outlet efficiency, etc., to evaluate the air delivery capacity required for this area to achieve the desired cooling or ventilation effect; that is, through thermodynamics and fluid mechanics calculations, quantify the minimum effective air volume that the blower needs to provide under the current structural conditions to ensure the achievement of the partition comfort target, and determine the target air volume of this blower. If a blower controls multiple partitions, the target air volume will also be weighted and distributed considering the demand intensity of each partition, so as to obtain the target air volume that each blower should deliver during the current operation cycle.

[0075] Step 604, calculate the initial blower speed corresponding to each blower according to the mapping relationship between the blower speed and the target air volume of each blower.

[0076] Among them, the initial blower speed can be the starting rotation speed set when the ventilation task is first executed, usually in revolutions per minute (RPM). This speed is calculated by mapping through the blower performance curve from the target air volume and is a key control parameter to achieve the expected air flow output.

[0077] Specifically, retrieve the fan performance model or refer to the air volume - rotational speed characteristic curve provided by the fan manufacturer (i.e., the mapping relationship between the fan rotational speed and the target air volume). Since this curve is usually calibrated based on experiments and describes the trend of the air volume change that the fan can output at different rotational speeds, taking the target air volume of each fan as the input, combined with the flow resistance characteristics of the air duct and the efficiency change of the fan under specific loads, inversely solve for the optimal initial rotational speed required to achieve this air volume. If the air volume - rotational speed relationship is non - linear, the target value can be accurately matched through interpolation algorithms or fitting functions (such as polynomial fitting or neural network models). In addition, constraint conditions such as the maximum noise tolerance, rotational speed upper limit, or system response time can be introduced according to actual application requirements to correct or optimize the calculation results, and finally output the initial rotational speed of the fan.

[0078] Step 606: Calculate the target dynamic wind direction corresponding to each fan according to the initial rotational speed of each fan and the ventilation duct information.

[0079] Among them, the target dynamic wind direction can be the air flow direction that is formed under the fan operating state through specific duct structures and wind speed conditions and finally acts on the surface of the occupant's body. It is jointly determined by the operating parameters of the fan (such as wind speed, air volume) and the geometric characteristics of the ventilation duct, representing the actual propagation path of the air flow.

[0080] Specifically, based on the air volume output of each fan at the initial rotational speed of the fan, combined with the duct geometric structure (such as bending angle, branch structure, duct cross - section change, etc.) for air flow path simulation. Air flow path simulation usually uses the computational fluid dynamics (CFD) model to model and dynamically track the propagation behavior of the air flow in the duct, and analyze in which direction the air flow finally acts on each area of the occupant's body after passing through the duct under specific wind speed and duct morphology. Since this directionality not only depends on the end - outlet angle of the duct but is also closely related to the inertia, turbulence formation, pressure distribution, etc. of the air flow under the fan operating state, combined with the three - dimensional human body contour and the seat fitting area, judge whether the wind direction accurately covers the target hot area. If there is an offset, the outlet structure or subsequent fan parameters can be adjusted for correction, and finally the target dynamic wind direction is obtained.

[0081] Step 608: Optimize the ventilation power of the car seat according to the target air volume and target dynamic wind direction of each fan to obtain the initial fan operating parameters corresponding to each fan.

[0082] Among them, the ventilation power can be the electric power actually consumed by the fan to drive the air to flow in the seat duct system, overcome the resistance, and achieve the target air volume and wind direction, usually measured in watts (W).

[0083] Specifically, taking the obtained target air volume of the fan and the dynamic wind direction as strong constraint conditions, a multi-objective optimization model is established to minimize the power consumption of the entire seat ventilation system on the premise of ensuring that the comfort requirements are met. The multi-objective optimization model comprehensively considers the efficiency curve, power consumption, air flow output stability of the fan at different speeds, and the additional load caused by the air duct resistance, and simultaneously evaluates the air flow interference and overlapping effects that may occur when multiple fans operate in coordination. On this basis, an optimization algorithm (such as particle swarm optimization, genetic algorithm or linear programming) is used to solve the multi-objective optimization model, that is, the operating parameters of the fan are iteratively calculated, including the initial speed, operating time, startup rhythm, wind direction adjustment mechanism, etc., to ensure that each fan completes the established air flow task in the most energy-efficient state. The finally output initial fan operating parameters not only meet the precise requirements of each partition for air volume and wind direction, but also achieve an optimized balance in terms of overall energy efficiency, noise control and system response.

[0084] In one embodiment, the calculation expression of the initial fan operating parameters is Wherein, D i is the partition demand information of the i area, i is the seat partition index. When the seat is divided into blocks or meshes, several partitions are delimited and numbered according to the three-dimensional contour of the occupant or the seat design. p i is the contact pressure on the i area, which is obtained by measuring the occupant using a pressure sensor array. p avg is the average contact pressure in all areas, which is the weighted average of the measured contact pressures in all areas. k p is the pressure amplification coefficient, which is calibrated through experiments or simulations. h i is the convective heat transfer coefficient of the i area, which is estimated, looked up in a table or calibrated based on the air duct design, the air permeability of the seat fabric, and laboratory measurements or numerical simulations (CFD). A i is the effective heat dissipation area on the contact surface of the i area, which is determined by the intersection of the three-dimensional contour of the occupant and the seat geometric model. T skin is the skin temperature of the occupant, which is measured using a patch temperature sensor. T seat,i is the surface temperature of the seat in the i area, which is measured using a patch temperature sensor. is the humidity correction factor, which is calculated by combining data such as the physiological state of the occupant (such as heart rate, ambient humidity, real-time sweat detection) and the humidity sensor on the seat surface; J is the initial fan operating parameter, M is the total number of zones, j is the fan identifier, N is the total number of fans, is for the i fan index set for air supply to the zone, j is for the fan i ventilation distribution coefficient for the zone, which is obtained through the internal air duct structure of the seat and actual fluid simulation, measurement or calibration, j is the wind direction of the fan is at the rotational speed of and the wind direction is the actual air volume output at this time, which is given by the fan characteristic curve or calibration function, is for the fan j rotational speed, is for the fan j power consumption at the rotational speed of which is determined by the characteristic curve provided by the fan manufacturer or vehicle measurement and calibration, is the demand balance factor, which is set during the system design or calibration phase and can also be dynamically adjusted during operation, is the wind direction adjustment energy consumption in the wind direction of the fan j which is determined through theoretical calculation or by recording the energy loss curve during wind direction adjustment in the experiment, is the weighting factor of the wind direction adjustment energy consumption, which is determined during system calibration or experiment.

[0085] In this embodiment, through the coupling of the zoning demand information and the ventilation duct information, the target air volume required for each fan is accurately calculated, and the corresponding initial rotational speed is deduced based on the fan characteristic curve. Further, by simulating the air flow path in combination with the duct structure, the target dynamic wind direction of the air flow acting on the human body is determined. Finally, on the premise of ensuring that the air volume and wind direction meet the comfort requirements, the overall power of the ventilation system is optimized to obtain the initial operating parameters corresponding to each fan. It realizes the full-process intelligent conversion from heat demand to fan control parameters, not only improves the accuracy and response efficiency of the fan output, but also significantly reduces the energy consumption, realizes the efficient coordination among comfort, energy conservation and personalized control of the seat ventilation system, and improves the intelligent level and user experience quality of the vehicle thermal management system.

[0086] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other orders.

[0087] Based on the same inventive concept, an embodiment of the present application also provides an automotive seat ventilation parameter determination device for implementing the above-mentioned automotive seat ventilation parameter determination method. As Figure 7 shown, it includes: an information acquisition module 702, an information analysis module 704, an air duct construction module 706, a parameter calculation module 708, a ventilation simulation module 710, a parameter optimization module 712, and a parameter fusion module 714. The implementation solution provided by this device to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the automotive seat ventilation parameter determination device provided below can refer to the limitations on the automotive seat ventilation parameter determination method in the above text, and will not be repeated here.

[0088] In an exemplary embodiment, a computer device is provided. This computer device can be a server, and its internal structure diagram can be as Figure 8 shown. This computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Those skilled in the art can understand that Figure 8 the structure shown in

[0089] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0089] In an embodiment, a computer device is also provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0090] In an embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0091] In an embodiment, a computer program product or a computer program is provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the above method embodiments.

[0092] It should be noted that the user information involved in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0093] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods.

[0094] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0095] The above-described embodiments merely represent several implementation manners of this application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of this application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several modifications and improvements can still be made, and these all belong to the protection scope of this application. Therefore, the protection scope of this application should be subject to the appended claims.

Claims

1. A method for determining the ventilation parameters of an automotive seat, characterized in that, The method includes: Obtaining three-dimensional contour information of a target object on an automotive seat, object physiological information of the target object, and in-vehicle environment information; Performing a comfort analysis on the target object according to the object physiological information and the in-vehicle environment information to determine the comfortable physiological information of the target object; Taking the comfortable physiological information as a target condition, constructing ventilation duct information of the automotive seat according to the three-dimensional contour information; Inputting the comfortable physiological information and the ventilation duct information into a fan control model of the automotive seat to obtain initial fan operating parameters corresponding to each fan in the automotive seat; Performing ventilation simulation on the automotive seat according to the initial fan operating parameters to obtain fan operating information corresponding to each fan; For any one of the fans, performing energy-saving optimization on the initial fan operating parameters according to the fan operating information to obtain target fan operating parameters corresponding to the fan; Fusing the target fan operating parameters to obtain seat ventilation parameters of the automotive seat.

2. The method according to claim 1, characterized in that, The constructing the ventilation duct information of the automotive seat according to the three-dimensional contour information with the comfortable physiological information as a target condition includes: Taking the comfortable physiological information as a target condition, constructing a heat exchange equation set of the automotive seat according to the three-dimensional contour information; According to the heat exchange equation set, performing a heat exchange shape mapping on the ventilation duct of the automotive seat to obtain the ventilation duct information.

3. The method according to claim 2, characterized in that, The performing a heat exchange shape mapping on the ventilation duct of the automotive seat according to the heat exchange equation set to obtain the ventilation duct information includes: Performing a heat exchange shape mapping on the ventilation duct according to the heat exchange equation set to obtain duct shape data; Performing iterative optimization on the duct shape data according to each influencing factor of the comfortable physiological information to obtain the ventilation duct information.

4. The method according to claim 3, wherein The heat exchange equation set includes a fluid continuity equation, an air momentum equation, a temperature transport equation, and a humidity transport equation. The expression of the fluid continuity equation is The expression of the air momentum equation is The expression of the temperature transport equation is The expression of the humidity transport equation is Among them, is the fluid velocity vector; is the air density, p is the air static pressure, is the air viscosity, is the spatial coordinate along the air duct x and is the air flow permeability varying with it, is the Forchheimer coefficient; is the specific heat capacity of air, T is the temperature field, is the equivalent thermal conductivity, is the spatial coordinate along the air duct x and is the heat source term data varying with it; H is the humidity field, D is the equivalent humidity diffusion coefficient, is the spatial coordinate along the air duct x and is the humidity quantity varying with it.

5. The method according to claim 4, characterized in that, The calculation expression of the ventilation duct information is Among them, is the ventilation duct information, is the temperature weight coefficient, is the humidity weight coefficient, is the pressure weight coefficient, T opt is the target temperature, H opt is the target humidity, p eff is the target pressure, p opt is the pressure felt by the occupant, is the regularization coefficient of the duct distribution function, is the spatial gradient term of the duct distribution function, is the contact surface between the seat and the occupant, is the three-dimensional volume domain inside the seat, T is the temperature field, H is the humidity field.

6. The method according to claim 1, wherein The inputting the comfortable physiological information and the ventilation duct information into the fan control model of the automotive seat to obtain the initial fan operating parameters corresponding to each fan in the automotive seat includes: Dividing the automotive seat according to the comfortable physiological information to obtain each automotive seat partition information; Intercepting partition comfort information corresponding to each automotive seat partition information from the comfortable physiological information; For any one of the automotive seat partition information, calculating pressure amplification information and local correction heat load corresponding to the automotive seat partition information according to the partition comfort information; Multiplying the pressure amplification information and the local correction heat load to obtain partition demand information; Adjusting the operating parameters of each fan of the automotive seat according to the partition demand information and the ventilation duct information to obtain the initial fan operating parameters corresponding to each fan.

7. The method according to claim 6, wherein Adjusting the operating parameters of each of the blowers of the vehicle seat according to the partition requirement information and the ventilation duct information to obtain the initial blower operating parameters corresponding to each of the blowers, including: Calculating the target air volume corresponding to each of the blowers according to the partition requirement information and the ventilation duct information; Calculating the initial blower speed corresponding to each of the blowers according to the mapping relationship between the blower speed of each of the blowers and the target air volume; Calculating the target dynamic wind direction corresponding to each of the blowers according to the initial blower speed of each of the blowers and the ventilation duct information; Optimizing the ventilation power of the vehicle seat according to the target air volume and the target dynamic wind direction of each of the blowers to obtain the initial blower operating parameters corresponding to each of the blowers.

8. The method according to claim 7, characterized in that The calculation expression of the initial blower operating parameters is Among them, D i is the zoning requirement information of the i area, i is the seat zoning index, p i is the contact pressure on the i area, p avg is the average contact pressure within all areas, k p is the pressure amplification factor, h i is the i area's convective heat transfer coefficient, A i is the i area's effective heat dissipation area on the contact surface, T skin is the occupant's skin temperature, T seat,i is the seat's surface temperature on the i area, is the humidity correction factor; J is the initial fan operating parameter, M is the total number of areas, j is the fan identification, N is the total number of fans, is the set of fan indices for supplying air to the i area, is the j fan's i area's ventilation distribution coefficient, is the j fan's wind direction at a rotational speed of and a wind direction of is the actual air volume output, is the j fan's rotational speed, j is the fan's power consumption at a rotational speed of is the demand balance factor, is the energy consumption for wind direction adjustment in the wind direction of the j fan, is the weighting factor for the energy consumption of wind direction adjustment.

9. An automobile seat ventilation parameter determination device, characterized in that The device includes: An information acquisition module, configured to acquire three-dimensional contour information of a target object on a vehicle seat, physiological information of the target object, and in-vehicle environment information; An information analysis module, configured to perform a comfort analysis on the target object according to the physiological information of the object and the in-vehicle environment information to determine the comfortable physiological information of the target object; A duct construction module, configured to construct ventilation duct information of the vehicle seat according to the three-dimensional contour information with the comfortable physiological information as a target condition; A parameter calculation module, configured to input the comfortable physiological information and the ventilation duct information into a blower control model of the vehicle seat to obtain initial blower operating parameters corresponding to each blower in the vehicle seat; A ventilation simulation module, configured to perform ventilation simulation on the vehicle seat according to the initial blower operating parameters to obtain blower operating information corresponding to each of the blowers; A parameter optimization module, configured to perform energy-saving optimization on the initial blower operating parameters according to the blower operating information for any one of the blowers to obtain target blower operating parameters corresponding to the blower; A parameter fusion module, configured to fuse the target blower operating parameters to obtain seat ventilation parameters of the vehicle seat.

10. A computer, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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