Method, device and computer for determining vehicle seat ventilation parameters

Abstract

This application relates to a method, device, and computer for determining vehicle seat ventilation parameters. The method includes: obtaining three-dimensional contour information of a target object on a vehicle seat, physiological information of the object, and information about the vehicle's interior environment; performing a comfort analysis based on the physiological information of the object and the interior environment to determine the comfort physiological information; constructing ventilation duct information for the vehicle seat based on the three-dimensional contour information, using the comfort physiological information as a target condition; inputting the comfort physiological information and ventilation duct information into a fan control model to obtain initial fan operating parameters corresponding to each fan; performing a ventilation simulation based on the initial fan operating parameters to obtain fan operating information corresponding to each fan; for any fan, performing energy-saving optimization on the initial fan operating parameters based on the fan operating information to obtain target fan operating parameters; and fusing the target fan operating parameters to obtain seat ventilation parameters for the vehicle seat. This method can improve seat ventilation performance.

Description

Technical Field

[0001] The present application relates to the field of intelligent automobile technology, and in particular to a method, device and computer for determining automobile seat ventilation parameters. Background Art

[0002] Traditional seat ventilation technology relies on users manually adjusting the air volume or ventilation mode. Users can select different air volume levels or ventilation intensities via buttons or touchscreens inside the vehicle, and then combine these with pre-set modes to ventilate different seat areas (such as the back and seat cushion). However, traditional seat ventilation technology cannot automatically optimize ventilation based on factors such as the occupant's physical condition, environmental changes, or driving time, resulting in poor seat ventilation. Summary of the Invention

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

[0004] In a first aspect, the present application provides a method for determining vehicle seat ventilation parameters, comprising:

[0005] Acquiring three-dimensional contour information of a target object on a car seat, physiological information of the target object, and in-car environment information;

[0006] performing a comfort analysis on the target object based on the physiological information of the object and the in-vehicle environment information to determine the comfortable physiological information of the target object;

[0007] Taking the comfort physiological information as a target condition, constructing ventilation duct information of the car seat according to the three-dimensional contour information;

[0008] Inputting the comfort physiological information and the ventilation duct information into a fan control model of the car seat to obtain initial fan operating parameters corresponding to each fan in the car seat;

[0009] Performing ventilation simulation on the car seat according to the initial fan operating parameters to obtain fan operating information corresponding to each fan;

[0010] For any 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;

[0011] The target fan operating parameters are integrated to obtain the seat ventilation parameters of the car seat.

[0012] In a second aspect, the present application further provides a device for determining vehicle seat ventilation parameters, comprising:

[0013] An information acquisition module, configured to acquire three-dimensional contour information of a target object on a car seat, physiological information of the target object, and in-car environment information;

[0014] an information analysis module, configured to perform a comfort analysis on the target object based on the physiological information of the object and the in-vehicle environment information, and determine the comfortable physiological information of the target object;

[0015] an air duct construction module, configured to construct ventilation duct information of the automobile seat according to the three-dimensional contour information, taking the comfort physiological information as a target condition;

[0016] a parameter calculation module, configured to input the comfort physiological information and the ventilation duct information into a fan control model of the car seat to obtain initial fan operating parameters corresponding to each fan in the car seat;

[0017] a ventilation simulation module, configured to perform ventilation simulation on the car seat according to the initial fan operating parameters, and obtain fan operating information corresponding to each fan;

[0018] a parameter optimization module, configured to optimize the initial fan operating parameters for energy saving according to the fan operating information for any of the fans, and obtain target fan operating parameters corresponding to the fan;

[0019] The parameter fusion module is used to fuse the target fan operating parameters to obtain the seat ventilation parameters of the car seat.

[0020] 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.

[0021] The aforementioned method, device, and computer for determining automotive seat ventilation parameters comprehensively acquire the target occupant's three-dimensional seat profile information, individual physiological characteristics (such as body temperature, perspiration, and metabolic rate), and real-time in-vehicle environmental parameters (such as temperature, humidity, and air flow). Based on this information, the system conducts a multi-dimensional comfort analysis to accurately determine the occupant's optimal comfort state in the current environment. This comfort state is then used as the core objective, combining the seat's three-dimensional profile data to intelligently construct personalized ventilation duct structure information. This information, along with the comfort physiological information, is input into a fan control model to obtain initial operating parameters for each fan. Simulations are then used to evaluate ventilation performance, obtaining actual fan operating information. Based on this information, energy-saving optimization is performed on the initial parameters to determine the optimal energy-saving operating parameters for each fan while ensuring comfort. Ultimately, the target parameters of all fans are integrated to form a comprehensive seat ventilation control solution. This solution improves seat ventilation performance and enables intelligent, personalized adjustment of the seat ventilation system, enhancing individual comfort while also balancing energy efficiency. This significantly enhances overall vehicle comfort management and energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 A diagram illustrating an application environment of a method for determining vehicle seat ventilation parameters in one embodiment;

[0024] Figure 2 1 is a flow chart of a method for determining vehicle seat ventilation parameters in one embodiment;

[0025] Figure 3 Schematic diagram of a flow chart of a first ventilation duct information construction method in one embodiment;

[0026] Figure 4 1 is a flow chart of a second ventilation duct information construction method according to an embodiment;

[0027] Figure 5 1 is a flow chart of a method for obtaining the first initial fan operating parameters in one embodiment;

[0028] Figure 6 1 is a flow chart of a second method for obtaining initial fan operating parameters in one embodiment;

[0029] Figure 7This is a structural block diagram of a device for determining vehicle seat ventilation parameters in one embodiment;

[0030] Figure 8 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0032] The embodiment of the present application provides a method for determining vehicle seat ventilation parameters, which can be applied to Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or placed on a cloud or other network server. Server 104 can be implemented as a standalone server or a server cluster consisting of multiple servers.

[0033] In an exemplary embodiment, Figure 2 As shown, a method for determining vehicle seat ventilation parameters is provided, and the method is applied to Figure 1 The server in FIG. 1 is used as an example to illustrate the method, including the following steps 202 to 214. Among them:

[0034] Step 202 : Acquire three-dimensional contour information of the target object on the car seat, physiological information of the target object, and in-car environment information.

[0035] Among them, the three-dimensional contour information can be the surface contact morphology and spatial distribution characteristics of the target object on the car seat obtained through sensors (such as pressure sensor arrays, infrared depth cameras or laser scanning devices), including the concave and convex structures and sitting posture contours of areas such as the back, waist, buttocks and thighs.

[0036] The object physiological information may be various physiological parameters related to the physical condition of the passenger, such as one or more of body temperature, heart rate, skin humidity, sweating amount, metabolic rate, etc.

[0037] The in-vehicle environmental information may be climate and air condition data in the current vehicle cabin, including one or more of air temperature, relative humidity, wind speed, air quality (such as CO2 concentration), light intensity, etc.

[0038] Specifically, through the pressure sensor array, infrared camera or lidar and other equipment installed on the car seat, the three-dimensional contour data of the contact area between the passenger and the seat is collected in real time to reflect their sitting posture and body characteristics; at the same time, the passenger's object physiological information, such as body temperature, heart rate, skin electrical response, sweating amount, etc., is collected through wearable physiological sensing equipment or physiological monitoring modules integrated in the seat; in addition, one or more in-vehicle environmental information such as temperature and humidity, air flow rate, light intensity, etc. is collected through the on-board environmental sensors.

[0039] Step 204 : performing a comfort analysis on the target object based on the physiological information of the object and the in-vehicle environment information to determine the target object's comfortable physiological information.

[0040] Comfort analysis is a process of comprehensively evaluating the passenger's current thermal comfort status based on the subject's physiological information and in-vehicle environmental information. Thermal comfort models (such as the PMV / PPD model and the Fanger model) or intelligent algorithms (such as machine learning classifiers) are usually used to predict the passenger's subjective feelings, determine whether they are in a comfortable range, and identify specific physiological reasons for deviation from comfort (such as local overheating, humidity, etc.).

[0041] The comfort physiological information may be target values ​​of physiological parameters that should be possessed by passengers in order to achieve optimal thermal comfort in a specific in-vehicle environment, such as ideal skin temperature, desired local wind speed, or appropriate humidity level.

[0042] Specifically, the acquired physiological information of passengers (such as body temperature, heart rate, skin humidity, sweat rate, etc.) is integrated with in-vehicle environmental information (including cabin temperature, humidity, air flow rate, CO2 concentration, light intensity, etc.). A thermal comfort assessment model is constructed to analyze the current passenger state for comfort. The thermal comfort assessment model can be based on the PMV / PPD model, the Fanger model, or a multi-parameter regression network trained based on machine learning to assess whether the passenger is currently in the comfort zone. If the current state deviates from the comfort standard, the human body's thermal regulation mechanism is further combined to predict the target physiological parameters required to restore the passenger to thermal equilibrium or optimal perception in the current environment, such as ideal skin temperature, expected local wind speed, and optimal humidity perception value. The resulting comfort physiological information not only reflects the passenger's subjective comfort needs but also provides an objective and quantitative target reference for subsequent ventilation system adjustments.

[0043] Step 206 , taking the comfort physiological information as the target condition, constructing the ventilation duct information of the car seat according to the three-dimensional contour information.

[0044] Among them, the ventilation duct information can be a set of structural parameters of the air circulation path inside the seat constructed based on the three-dimensional contour and comfortable physiological needs, including the direction of the duct, air outlet distribution, duct size, drag coefficient, connection relationship and other contents.

[0045] Specifically, based on the occupant's three-dimensional contour information, a three-dimensional structural model of the seat's contact area is reconstructed, identifying the spatial distribution characteristics of key contact points such as the occupant's back, buttocks, and thighs. Combining established physiological comfort information as target conditions (such as local temperature regulation requirements, desired air velocity, and ventilation uniformity), computer-aided design tools (such as CAD and CFD simulation platforms) are used to model and simulate the seat's internal ventilation structure. The modeling and simulation process comprehensively considers factors such as duct layout, number and location of air outlets, airflow direction, and wind resistance distribution, ensuring that the ventilation system conforms to the human body while efficiently and precisely delivering air to key thermal zones to meet personalized thermal regulation needs. Multiple rounds of modeling and simulation iterations are used to optimize duct patency and structural feasibility, generating personalized ventilation duct information that closely matches the occupant's physiological comfort needs.

[0046] Step 208 : Input the comfort physiological information and ventilation duct information into the fan control model of the car seat to obtain the initial fan operating parameters corresponding to each fan in the car seat.

[0047] 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. It can adopt rule-based control logic, physical modeling, or a neural network structure based on deep learning.

[0048] The initial fan operating parameters may 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.

[0049] Specifically, the constructed ventilation duct information and the occupant's physiological comfort information are combined as inputs into a pre-established fan control model. This fan control model, based on physical modeling and preset control rules, or employs deep learning methods to construct a multi-input, multi-output (MIMO) predictive control network, accurately predicts fan response under different operating conditions. Based on the ventilation duct layout characteristics (such as the distance from each air outlet to the target area, wind resistance, and local ventilation capacity) and the occupant's physiological comfort information (such as back wind speed, hip temperature, and leg humidity), the fan control model calculates the initial operating parameters required for each fan, including fan speed, air volume, operating time, and start-stop rhythm. This initial parameter set strives to achieve distributed and regionalized fan control while meeting the target physiological comfort information.

[0050] Step 210 , performing ventilation simulation on the car seat according to the initial fan operating parameters to obtain fan operating information corresponding to each fan.

[0051] Among them, the fan working information can be the operating status data of each fan under the action of initial parameters obtained through ventilation simulation or actual operation, reflecting the flow of air inside the seat, wind speed distribution, cooling effect, temperature and humidity changes, etc., which is used to evaluate whether the initial settings achieve the expected comfort effect, and at the same time provide a basis for energy-saving optimization.

[0052] Specifically, a vehicle seat ventilation simulation is performed based on initial fan operating parameters. While obtaining fan operating information from the simulation, computational fluid dynamics (CFD) simulation methods are used to dynamically simulate the seat's internal ventilation process, based on the initial operating parameters generated by the fan control model and the constructed ventilation duct structure. This simulation considers physical phenomena such as the airflow path, velocity distribution, pressure drop variations, heat exchange processes, and humidity migration within the complex duct. This simulation accurately reflects the airflow efficiency and distribution uniformity across different areas under the current initial fan configuration. The simulation outputs the airflow temperature and humidity field distribution, velocity field images, and microenvironmental parameters of the human body contact areas corresponding to each air outlet. This output data is then used to analyze the specific operating status of each fan, including its impact on the target comfort zone, cooling or drying effects, and whether there are issues such as over-ventilation or under-ventilation. This provides detailed fan operating information.

[0053] Step 212 : For any wind turbine, perform energy-saving optimization on the initial wind turbine operating parameters according to the wind turbine operating information to obtain target wind turbine operating parameters corresponding to the wind turbine.

[0054] Among them, energy-saving optimization can be the process of calculating and adjusting the operating parameters of the fan while maintaining the comfort of the passengers, aiming to reduce the fan's energy consumption and reduce unnecessary airflow output.

[0055] Among them, the target fan operating parameters can be the optimal operating settings finally determined for each fan after energy-saving optimization, including optimized air volume, speed, operating time, wind direction, etc., which can not only meet the target comfortable physiological information, but also minimize energy consumption.

[0056] Specifically, individual fans may be inefficient or consume high energy under their current operating conditions. Therefore, the current fan operating state is first assessed for energy waste, such as excessive air volume, redundant wind speeds, or cooling ranges outside the target area. Based on the premise of maintaining comfort, an optimization objective function is then set, such as minimizing energy consumption or fan load. Subsequently, an optimization algorithm (such as genetic algorithm, particle swarm optimization, and gradient descent) is used to iteratively adjust the initial operating parameters, while ensuring that the fan maintains the target comfort physiological parameters within its control area. This is done to find the optimal balance point, thereby determining the fan's target operating parameters. These target operating parameters not only meet the occupant's personalized needs for thermal, humidity, and wind sensation, but also minimize energy use.

[0057] Step 214 , integrating the target fan operating parameters to obtain seat ventilation parameters of the car seat.

[0058] Seat ventilation parameters can be integrated into a complete set of seat-level ventilation control configurations by integrating the target operating parameters of all fans. This parameter set guides the overall ventilation system operation strategy, enabling coordinated operation of multiple fans, thereby creating an intelligent seat ventilation system that is adaptive, energy-efficient, and tailored to individual needs.

[0059] Specifically, in the process of fusing the target fan operating parameters to generate seat ventilation parameters, it is necessary to unify the target operating parameters of all fans obtained after energy-saving optimization to construct a coordinated and efficient seat ventilation control strategy. Therefore, the fusion process not only considers the independent operating status of each fan within its control area, but also comprehensively analyzes the mutual influence between fans, such as wind flow superposition, airflow interference, and ventilation overlap in boundary areas, to ensure that the overall ventilation system achieves local and global coordination during operation. At the same time, a real-time feedback mechanism is also combined to uniformly schedule the start-up timing, operating rhythm, and air volume ratio of different fans. This ensures that the entire seat achieves a dynamic balance of thermal management and optimal allocation of ventilation resources while meeting the personalized comfort needs of the occupants. The final seat ventilation parameters will serve as centralized control instructions for the fan group and be input into the execution control system.

[0060] The aforementioned method for determining automotive seat ventilation parameters comprehensively captures the target occupant's three-dimensional seat profile, individual physiological characteristics (such as body temperature, perspiration, and metabolic rate), and real-time in-vehicle environmental parameters (such as temperature, humidity, and air flow). Based on this, a multi-dimensional comfort analysis is conducted to accurately determine the occupant's optimal comfort state in the current environment. This comfort state is then used as the core objective, and personalized ventilation duct structure information is intelligently constructed in conjunction with the seat's three-dimensional profile data. This information, along with the comfort physiological information, is then input into a fan control model to obtain initial operating parameters for each fan. Simulations are then used to evaluate ventilation performance, obtaining actual fan operating information. Based on this information, energy-saving optimization is performed on the initial parameters to determine the optimal energy-saving operating parameters for each fan while ensuring comfort. Ultimately, the target parameters of all fans are integrated to form a comprehensive seat ventilation control solution. This solution improves seat ventilation performance and enables intelligent, personalized adjustment of the seat ventilation system, enhancing individual comfort while also balancing energy efficiency. This significantly enhances vehicle comfort management and energy efficiency.

[0061] In an exemplary embodiment, Figure 3 As shown, taking the comfort physiological information as the target condition, the ventilation duct information of the car seat is constructed according to the three-dimensional contour information, including steps 302 to 304. Among them:

[0062] Step 302 : Taking the comfort physiological information as the target condition, a heat exchange equation group of the car seat is constructed according to the three-dimensional contour information.

[0063] Among them, the heat exchange equations can be a set of mathematical models that describe the air flow and heat transfer process inside the car seat, usually including the energy conservation equation, heat conduction equation, convection heat transfer formula and boundary condition definition, etc.

[0064] Specifically, in constructing a set of heat exchange equations for automotive seats based on three-dimensional contour information, the team first constructs a spatial model that matches the human sitting posture and body shape based on high-precision three-dimensional contour data of the occupant's contact area with the seat. Combined with the occupant's comfort physiological information (such as desired skin surface temperature, ideal heat dissipation rate, and local heat flux density), the contact area between the human body and the seat is considered a heat exchange interface. Taking into account the flow characteristics of air in the air duct, a set of heat exchange equations is established, encompassing multiple heat transfer mechanisms such as conduction, convection, and radiation. The heat exchange equations must include variables such as wind speed, temperature, pressure, contact area, thermal conductivity, and local seating pressure distribution as input parameters to accurately describe the path and intensity of heat energy transfer between the human body and the seat under different positions and conditions.

[0065] Step 304 : performing heat exchange shape mapping on the ventilation duct of the car seat according to the heat exchange equations to obtain ventilation duct information.

[0066] Heat exchange shape mapping is a process that dynamically adjusts and optimizes the geometry of the seat's internal air ducts, building upon a set of heat exchange equations to achieve optimal heat transfer in key areas of contact with the human body. This mapping process combines thermal simulation results with 3D contour data to iteratively design the duct's path, cross-sectional dimensions, and outlet locations, ensuring efficient heat transfer in the desired direction, thereby meeting the occupant's comfort needs in specific areas (such as the back and buttocks).

[0067] Specifically, using the established heat exchange equations as the physical model, and based on the occupant's three-dimensional profile data and comfort physiological information, numerical simulation methods (such as finite element analysis or computational fluid dynamics) are used to perform multiple rounds of geometric transformation and optimization iterations on the seat's internal duct structure. This involves adjusting key parameters such as the duct path, cross-sectional size, and outlet location and angle. This optimizes heat transfer at the seat-to-body interface, achieving efficient cooling or ventilation in localized areas. These calculations also consider engineering constraints such as air flow continuity, windage losses, and airflow uniformity, ensuring that the overall system's energy efficiency and structural feasibility are improved while meeting the occupant's personalized thermal comfort needs. This ultimately generates ventilation duct information.

[0068] In this embodiment, using the occupant's physiological comfort information as the target condition and incorporating their three-dimensional contour information on the seat, a set of heat exchange equations accurately describes the heat transfer process between the human body and the seat. Based on this, heat exchange shape mapping is performed on the seat's internal ventilation ducts, generating ventilation duct information that effectively matches individual thermal comfort needs. This enables the seat ventilation system to fully consider the occupant's personalized thermal regulation needs and actual contact conditions during the structural design phase, resulting in a more rational ventilation path layout, more precise airflow coverage, and higher heat exchange efficiency. This significantly improves the seat's local adjustment capabilities and overall comfort performance, while also providing a precise and structured foundation for subsequent fan control and energy-saving optimization.

[0069] In an exemplary embodiment, Figure 4 As shown, according to the heat exchange equations, heat exchange shape mapping is performed on the ventilation duct of the car seat to obtain ventilation duct information, including steps 402 to 404.

[0070] Step 402: Perform heat exchange shape mapping on the ventilation duct according to the heat exchange equations to obtain duct shape data.

[0071] Among them, heat exchange shape mapping can be an optimization process that maps the spatial distribution results of heat transfer efficiency between the human body and the seat to the geometric structure of the ventilation duct inside the seat under the theoretical guidance of the heat exchange equation group, thereby guiding the design of the duct shape.

[0072] Duct shape data, derived from heat exchange shape mapping, is a set of parameters describing the geometry of the ventilation duct within a car seat. This data includes information such as the duct's three-dimensional path, cross-sectional dimensions, bend angles, and the location and orientation of the air outlet. It serves as the foundation for digitally representing the duct's layout and structural characteristics.

[0073] Specifically, a spatial correspondence between the occupant's three-dimensional contour model and the seat's internal structure is established. Using this geometric foundation, a set of heat exchange equations is combined to simulate the potential ventilation duct layout within the seat. These equations comprehensively consider convective heat transfer generated by air flowing through the duct, conductive heat transfer between the duct walls and the body's contact areas, and any heat energy from radiation effects. Using CFD (computational fluid dynamics) simulation tools to solve the heat exchange equations, the thermal response of various duct layouts is simulated. The efficiency and uniformity of heat exchange achieved by different configurations in key contact areas (such as the back, waist, and legs) are analyzed, and the heat exchange performance is mapped to specific duct shapes. Ultimately, a preliminary duct structure that meets the heat exchange requirements is extracted, including parameters such as duct direction, width variation, and outlet location and angle, generating duct shape data.

[0074] In one embodiment, the heat exchange equations include the fluid continuity equation, the air momentum equation, the temperature transfer equation, and the humidity transfer equation.

[0075] The expression of the fluid continuity equation is,

[0076]

[0077] The expression of the air momentum equation is,

[0078]

[0079] The expression of the temperature transfer equation is,

[0080]

[0081] The expression of the humidity transfer equation is,

[0082]

[0083] in, is the fluid velocity vector, measured by the sensor; The air density is determined by referring to the standard air properties table or the built-in database of the CFD software. p is the static pressure of air, measured by the sensor, For air viscosity, refer to the standard air properties table or the built-in database of CFD software. is the spatial coordinate of the wind channel x The varying airflow permeability is simulated based on seat material and duct layout. is the Forchheimer coefficient, which is pre-calibrated according to the specific material; The specific heat capacity of air is determined by consulting the standard air properties table or the built-in database of the CFD software. T is the temperature field, measured by the sensor, Is the equivalent thermal conductivity, measured according to the mixed heat transfer coefficient of "air + seat sponge". If it is pure air, it is determined by checking the standard table. is the spatial coordinate of the wind channel x The varying heat source data are given by measurements or design indicators; H is the humidity field, measured by the sensor, D The equivalent humidity diffusion coefficient is obtained by looking up the table and correcting it by combining the porous diffusion characteristics of "air + foam". is the spatial coordinate of the wind channel x The amount of humidity that changes, based on the distribution assumptions of sweat gland secretion rate (depending on temperature / exercise status) or material test data.

[0084] Step 404 : Iteratively optimize the duct shape data based on various influencing factors of the comfort physiological information to obtain ventilation duct information.

[0085] Among them, the influencing factors can be the key variables that directly affect the passenger's comfort experience or system operation performance during the ventilation duct optimization design process, mainly including local temperature requirements, wind speed perception, humidity adjustment requirements in comfort physiological information, as well as heat exchange efficiency, airflow distribution uniformity, wind resistance size, etc. related to the duct structure.

[0086] Specifically, based on duct shape data, various factors influencing the occupants' personalized physiological comfort needs are further incorporated as constraints in the optimization objective function. These factors include desired skin temperature range, local wind speed perception, humidity regulation requirements, and heat flux density distribution. Multi-objective optimization algorithms (such as genetic algorithms, response surface methods, and particle swarm optimization) are used to automatically adjust the duct's geometric parameters (such as path curvature, cross-sectional dimensions, and outlet orientation and location). After each shape update, the heat exchange equations are re-simulated to verify its response to the target area's heat exchange performance. This iterative process optimizes thermal efficiency while controlling flow resistance and structural complexity to ensure that the duct meets personalized thermal comfort requirements while maintaining engineering feasibility. Through multiple rounds of iteration, the system converges to a duct structure that achieves the optimal balance between comfort, ventilation uniformity, and energy efficiency, yielding ventilation duct information tailored to occupant needs.

[0087] In one embodiment, the calculation expression of the ventilation duct information is:

[0088]

[0089] in, For 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 through ergonomics or medical literature, H opt The target humidity is determined by ergonomics or medical literature. p eff is the target pressure, measured from the seat pressure sensor, p opt The pressure felt by the occupants is determined through ergonomics or medical literature. is the regularization coefficient of the duct distribution function, determined based on the simulation of suppressed violent oscillations, is the spatial gradient term of the wind duct distribution function, determined from the field of variational optimization or topology / shape optimization, is the air duct distribution, The contact surface between the seat and the occupant is obtained from the seat shape or 3D scanning. The three-dimensional volume domain inside the seat is obtained by measuring the three-dimensional contour of the seat according to the CAD model or physical object. T is the temperature field, measured by the sensor, H is the humidity field, measured by the sensor.

[0090] In this embodiment, heat exchange shape mapping of the ventilation ducts is performed based on a set of heat exchange equations to initially obtain duct shape data. This shape data is then iteratively optimized through multiple rounds, taking into account key factors influencing the occupant's physiological comfort information (such as local temperature, humidity, and wind sensation requirements). This generates ventilation duct information that is highly tailored to individual thermal regulation needs. This approach not only fully considers the heat exchange characteristics and airflow response characteristics between the human body and the seat, but also achieves an optimal balance between efficiency and comfort in the duct structure. This significantly improves the ventilation system's local control accuracy, overall thermal comfort performance, and energy-saving operation, providing a solid structural foundation and algorithmic support for personalized and intelligent seat thermal management.

[0091] In an exemplary embodiment, Figure 5 As shown, the comfort physiological information and ventilation duct information are input into the fan control model of the car seat to obtain the initial fan operating parameters corresponding to each fan in the car seat, including steps 502 to 510.

[0092] Step 502: partition the car seats according to the comfort physiological information to obtain the partition information of each car seat.

[0093] Seat zoning information can be a data set that divides the entire seat into multiple relatively independent zones based on human contact characteristics and functional requirements. Each zone corresponds to a specific part of the occupant's body, such as the upper back, lower back, waist, buttocks, and thighs, and has independent ventilation control logic and physical location attributes.

[0094] Specifically, the primary areas of contact with the seat are identified based on the occupant's three-dimensional profile data. Combined with the pressure sensor placement results, a contact intensity distribution map between the occupant and the seat is created. The seat is then divided into several thermal control units, typically encompassing the upper back, lower back, waist, buttocks, and thighs. Each area has a relatively independent airflow path and fan control range. Furthermore, the regional boundaries are further refined, taking into account the local thermal regulation needs reflected in physiological comfort information (e.g., a more sweaty back requires increased ventilation, while a sensitive waist requires gentle adjustment). This ensures that the zones are not only ergonomically designed but also closely align with thermal comfort control objectives. Ultimately, the geometry, functionality, and control range data for each seat zone are generated, forming the seat zone information.

[0095] Step 504 , extracting the zone comfort information corresponding to each car seat zone information from the comfort physiological information.

[0096] 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.

[0097] Specifically, the overall comfort physiological information is mapped to the designated seat zones. Local comfort requirement data corresponding to each zone is extracted from the comfort physiological information as zoned comfort information. Each zoned comfort information includes parameters such as target skin temperature, ideal air speed range, humidity adjustment requirements, and local thermal sensitivity, reflecting the occupant's personalized thermal environment expectations for different body parts. For example, the back area may require higher ventilation intensity to cope with excessive sweating, while the waist area may need to maintain a more stable temperature to prevent hot and cold stimulation.

[0098] Step 506 : For any car seat partition information, calculate the pressure amplification information and the local corrected thermal load corresponding to the car seat partition information according to the partition comfort information.

[0099] Pressure amplification information, calculated from seat pressure sensor data, represents the degree to which occupant contact pressure in a specific seat zone affects ventilation. High contact pressure typically indicates restricted airflow and significant heat accumulation in that area. The system models this effect through an amplification factor, serving as a key factor for enhancing localized control response. This gives higher priority and increased airflow support to high-pressure areas in fan control.

[0100] The local corrected heat load is the amount of heat required to compensate or remove within a specific seat zone to achieve a thermal comfort state consistent with the zone's comfort information. It is calculated based on the difference between current environmental parameters (temperature, humidity), human metabolic rate, clothing thermal resistance, and the desired target value, reflecting the cooling or heating intensity required for that area.

[0101] Specifically, for each car seat zone, the system determines the difference between the current environment and the ideal state based on the zone comfort information (such as desired temperature, target wind speed, and humidity comfort range) for that zone, and determines the required heat or ventilation intensity adjustment for that zone. It then combines the contact pressure and area data for that zone acquired by the seat pressure sensor to calculate pressure amplification information. This pressure amplification information indicates the degree to which airflow is hindered from entering that zone due to human pressure, thus serving as a factor in enhancing the adjustment intensity. Furthermore, the system utilizes the target temperature and humidity values ​​in the zone comfort information, combined with factors such as the current environmental conditions, the occupant's metabolic heat generation rate, and the thermal resistance of clothing, to calculate the local corrected thermal load—the amount of heat or cooling capacity required to achieve thermal comfort in that zone.

[0102] Step 508: Multiply the pressure amplification information and the local corrected heat load to obtain the zone demand information.

[0103] Among them, the partition demand information can be a comprehensive indicator obtained by multiplying the pressure amplification information with the local corrected heat load, which is used to quantify the ventilation adjustment intensity required for each seat partition under actual working conditions. It comprehensively considers the size of thermal comfort demand and the actual ventilation difficulty, and represents the priority of adjustment resources that should be allocated to the area in fan control.

[0104] Specifically, the localized corrected heat load represents the amount of heat regulation or cooling required due to the difference between the current environment and the target comfort state, while the pressure amplification information reflects the ventilation difficulty or heat accumulation tendency in the area caused by physical factors such as high human contact pressure and restricted airflow. By multiplying the two, not only the required "amount" of regulation is considered, but also the "difficulty" of regulation is introduced as a reinforcement factor. This makes the final zone demand information more accurate in real-world usage scenarios, reflecting the regulation priority under the combined influence of multiple factors such as thermal heterogeneity, local sensitivity, and airflow resistance.

[0105] Step 510 : adjusting the operating parameters of each fan of the car seat according to the partition requirement information and the ventilation duct information to obtain the initial fan operating parameters corresponding to each fan.

[0106] Specifically, based on ventilation duct information, the system determines factors such as the duct's geometry, flow resistance, airflow efficiency, and airflow coupling with adjacent areas within the area. This evaluates the fan's ability to deliver air to that area and its response speed during actual operation. Then, based on the matching between the zone's demand information and the duct's capacity, the system dynamically adjusts each fan's initial operating parameters, including speed, output volume, operating hours, and start-up time, to meet the zone's personalized thermal regulation needs. A global coordination mechanism also prevents airflow interference or resource waste between fans, ensuring efficient operation of the overall seat ventilation system while achieving comfort goals. Initial fan operating parameters are then generated.

[0107] In this embodiment, car seats are divided into zones based on physiological comfort information, and the local comfort requirements corresponding to each zone are extracted. This is further combined with pressure distribution and thermal load requirements to calculate precise zone adjustment intensity, or zone demand information. This demand information is then combined with the structural characteristics of the ventilation duct to precisely adjust the operating parameters of each fan, generating initial fan operating parameters that meet actual requirements. This shift in seat ventilation control from "global adjustment" to "local precision control" not only improves personalized thermal comfort matching but also enhances fan operation efficiency and responsiveness, effectively reducing system energy consumption and improving the intelligence of the ventilation system and user experience.

[0108] In an exemplary embodiment, Figure 6As shown, according to the partition requirement information and the ventilation duct information, the operating parameters of each fan of the car seat are adjusted to obtain the initial fan operating parameters corresponding to each fan, including steps 602 to 608.

[0109] Step 602: Calculate the target air volume corresponding to each fan according to the partition demand information and ventilation duct information.

[0110] The target air volume is the volume of air that the fan needs to deliver within a specific timeframe to meet the thermal comfort requirements of a specific seating zone, typically measured in cubic meters per hour (m³ / h). This key parameter is calculated based on the zone's heat load requirements, air temperature and humidity control targets, and the air duct's transport capacity. It guides the fan's output of appropriate airflow intensity to achieve effective cooling, drying, or ventilation in that area.

[0111] Specifically, a mapping relationship is established between the duct area controlled by each fan and the seat partition, clarifying the target area for each fan's adjustment. The partition demand information of the area is then input as the thermal comfort target. Combined with ventilation duct information, such as duct length, cross-sectional area, airflow resistance, and outlet efficiency, the air delivery capacity required to achieve the desired cooling or ventilation effect in the area is evaluated. That is, through thermodynamic and fluid mechanics calculations, the minimum effective air volume that the fan needs to provide under the current structural conditions is quantified to ensure the achievement of the partition comfort target and determine the target air volume for the fan. If a fan controls multiple partitions, the demand intensity of each partition is also comprehensively considered, and the target air volume is weighted and allocated, thereby deriving the target air volume that each fan should deliver during the current operating cycle.

[0112] Step 604 : Calculate the initial fan speed corresponding to each fan according to the mapping relationship between the fan speed of each fan and the target air volume.

[0113] Among them, the initial fan speed can be the starting rotation speed set when the ventilation task is first performed, usually in revolutions per minute (RPM). The speed is calculated by mapping the target air volume through the fan performance curve and is a key control parameter for achieving the expected airflow output.

[0114] Specifically, retrieve the fan performance model or consult the air volume-speed characteristic curve provided by the fan manufacturer (i.e., the mapping relationship between the fan speed and the target air volume). Since this curve is usually based on experimental calibration, it describes the trend of the air volume change that the fan can output at different speeds. The target air volume of each fan is used as input, combined with the flow resistance characteristics of the air duct and the efficiency change of the fan under a specific load, and the optimal initial speed required to achieve the air volume is reversely solved. If the air volume-speed relationship is nonlinear, the target value can be accurately matched through an interpolation algorithm or a fitting function (such as a polynomial fitting or a neural network model). In addition, according to the actual application requirements, restrictions can be introduced, such as maximum noise tolerance, speed upper limit or system response time, etc., to correct or optimize the calculation results and finally output the initial speed of the fan.

[0115] Step 606 : Calculate the target dynamic wind direction corresponding to each fan according to the initial rotation speed of each fan and the ventilation duct information.

[0116] The target dynamic wind direction is the direction of airflow that ultimately impacts the passenger's body, as determined by the specific duct structure and wind speed conditions when the fan is operating. It is determined by the fan's operating parameters (such as wind speed and air volume) and the geometric characteristics of the ventilation duct, representing the actual propagation path of the airflow.

[0117] Specifically, based on the air volume output of each fan at the initial fan speed, combined with the duct geometry (such as bending angles, branch structures, duct cross-sectional changes, etc.), airflow path simulation is performed. The airflow path simulation usually uses a computational fluid dynamics (CFD) model to model and dynamically track the propagation behavior of the airflow in the duct, and analyzes the direction in which the airflow will eventually act on various areas of the passenger's body after passing through the duct under the action of specific wind speed and duct shape. Because this directionality depends not only on the terminal outlet angle of the duct, but is also closely related to the inertia of the airflow, turbulence formation, and pressure distribution under the operation of the fan, it also combines the three-dimensional human body contour and the seat fit area to determine whether the wind direction accurately covers the target hot zone. If there is a deviation, the outlet structure or subsequent fan parameters can be adjusted to make corrections, and finally the target dynamic wind direction is obtained.

[0118] Step 608 optimizes the ventilation power of the car seat according to the target air volume and target dynamic wind direction of each fan, and obtains the initial fan operating parameters corresponding to each fan.

[0119] Among them, ventilation power can be the actual electrical power consumed by the fan to drive air to flow in the seat duct system, overcome resistance and achieve the target air volume and wind direction, usually in watts (W).

[0120] Specifically, the obtained fan target air volume and dynamic wind direction are used as strong constraints to establish a multi-objective optimization model to minimize the power consumption of the entire seat ventilation system while ensuring that comfort requirements are met. The multi-objective optimization model comprehensively considers the fan efficiency curve at different speeds, power consumption, airflow output stability, and the additional load caused by duct resistance. It also evaluates the airflow interference and overlap effects that may arise from the coordinated operation of multiple fans. Based on this, an optimization algorithm (such as particle swarm optimization, genetic algorithm, or linear programming) is used to solve the multi-objective optimization model. This involves iteratively calculating the fan operating parameters, including the fan's initial speed, operating time, startup rhythm, and wind direction adjustment mechanism. This ensures that each fan completes its specified airflow task in the most energy-efficient manner. The final output of the initial fan operating parameters not only meets the precise air volume and wind direction requirements of each zone, but also achieves an optimal balance in overall energy efficiency, noise control, and system response.

[0121] In one embodiment, the calculation expression of the initial fan operating parameters is:

[0122]

[0123]

[0124] in, D i For the i Information on the zoning requirements of the area, i It is the seat partition index. When dividing the seat into blocks or grids, several partitions are defined and numbered according to the occupant's three-dimensional profile or seat design. p i For the i The contact pressure on the area is measured by the pressure sensor array on the occupant. p avg The average contact pressure in the entire area is the weighted average of the contact pressures measured in all areas. k p is the pressure amplification factor, and the parameters are calibrated through experiments or simulations. h i For the i The convective heat transfer coefficient of the area 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 simulation (CFD). A i For the i The effective heat dissipation area of ​​the area on the contact surface is determined by the intersection of the occupant's three-dimensional contour and the seat geometry model. T skin The skin temperature of the occupant is measured using a patch temperature sensor. T seat,iFor the seat i The surface temperature of the area is measured using a patch temperature sensor. is the humidity correction factor, which is calculated based on the occupant's physiological status (such as heart rate, ambient humidity, real-time sweat detection) and data from the seat surface humidity sensor; J are the initial fan operating parameters, M is the total number of regions, j For the fan identification, N is the total number of fans, For the i The index collection of fans that supply air to the area. For fans j For the first i The ventilation distribution coefficient of the area is obtained by simulating, measuring or calibrating the internal air duct structure of the seat and the actual flow. For fans j The wind direction, For the speed And the wind direction is The actual air volume output at the time is given by the fan characteristic curve or calibration function. For fans j The rotation speed, For fans j At a speed of The power consumption is determined by the characteristic curve provided by the fan manufacturer or by vehicle measurement and calibration. It is the demand balancing factor, which is set during the system design or calibration phase and can also be dynamically adjusted during operation. For the fan j The energy consumption of wind direction adjustment is determined by theoretical calculation or by recording the energy loss curve when the wind direction is adjusted in the test. It is the weighting factor for wind direction regulation energy consumption, which is determined during system calibration or experiments.

[0125] In this embodiment, by coupling zone demand information with ventilation duct information, the target air volume required for each fan is accurately calculated. The corresponding initial speed is derived based on the fan characteristic curve. The airflow path is further simulated using the duct structure to determine the target dynamic direction of the airflow acting on the human body. Ultimately, while ensuring that the air volume and direction meet comfort requirements, the overall ventilation system power is optimized to obtain the corresponding initial operating parameters for each fan. This achieves a fully intelligent conversion process from thermal demand to fan control parameters, improving the accuracy and response efficiency of fan output while significantly reducing energy consumption. This enables efficient coordination between comfort, energy conservation, and personalized control for the seat ventilation system, enhancing the intelligence level of the vehicle's thermal management system and the quality of the user experience.

[0126] It should be understood that although the steps in the flowcharts of the various embodiments described above are shown sequentially as indicated by the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be executed in other orders.

[0127] Based on the same inventive concept, the embodiment of the present application also provides a vehicle seat ventilation parameter determination device for implementing the above-mentioned vehicle seat ventilation parameter determination method. Figure 7 As shown, it includes: an information acquisition module 702, an information analysis module 704, a 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 for solving the problem provided by the device is similar to the implementation solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of a vehicle seat ventilation parameter determination device provided below can be found in the above limitations on a vehicle seat ventilation parameter determination method, and will not be repeated here.

[0128] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure 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 shown in the figure, or combine certain components, or have a different component arrangement.

[0129] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0130] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0131] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of each of the above-described method embodiments.

[0132] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0133] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related 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-mentioned methods.

[0134] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, 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, they should be considered to be within the scope of this specification.

[0135] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining vehicle seat ventilation parameters, characterized in that: The method comprises: Acquiring three-dimensional contour information of a target object on a car seat, physiological information of the target object, and in-car environment information; performing a comfort analysis on the target object based on the physiological information of the object and the in-vehicle environment information to determine the comfortable physiological information of the target object; Taking the comfort physiological information as a target condition, ventilation duct information of the car seat is constructed according to the three-dimensional contour information; the ventilation duct information is obtained by solving a heat exchange equation group of the car seat using computational fluid dynamics; the heat exchange equation group includes a fluid continuity equation, an air momentum equation, a temperature transfer equation, and a humidity transfer equation. The calculation expression of the ventilation duct information is: in, For 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 For passengers to feel the pressure, is the regularization coefficient of the air duct distribution function, is the spatial gradient term of the wind duct distribution function, It is the contact surface between the seat and the passenger. is the three-dimensional volume domain inside the seat, T is the temperature field, and H is the humidity field; The expression of the fluid continuity equation is, ， The expression of the air momentum equation is, ， The expression of the temperature transfer equation is, ， The expression of the humidity transfer equation is, in, is the fluid velocity vector; is the air density, p is the air static pressure, is the air viscosity, is the airflow permeability that changes with the spatial coordinate x of the air duct, is the Forchheimer coefficient; is the specific heat capacity of air, T is the temperature field, is the equivalent thermal conductivity, is the heat source data that changes with the spatial coordinate x of the air duct; H is the humidity field, D is the equivalent humidity diffusion coefficient, is the humidity that changes with the spatial coordinate x of the air duct; Inputting the comfort physiological information and the ventilation duct information into a fan control model of the car seat to obtain initial fan operating parameters corresponding to each fan in the car seat; Performing ventilation simulation on the car seat according to the initial fan operating parameters to obtain fan operating information corresponding to each fan; For any 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; The target fan operating parameters are integrated to obtain the seat ventilation parameters of the car seat.

2. The method according to claim 1, characterized in that The method of constructing the ventilation duct information of the automobile seat based on the three-dimensional contour information and taking the comfortable physiological information as a target condition includes: Taking the comfort physiological information as a target condition, constructing a heat exchange equation group of the car seat according to the three-dimensional contour information; According to the heat exchange equations, heat exchange shape mapping is performed on the ventilation duct of the car seat to obtain the ventilation duct information.

3. The method according to claim 2, characterized in that The step of performing heat exchange shape mapping on the ventilation duct of the automobile seat according to the heat exchange equations to obtain the ventilation duct information includes: According to the heat exchange equations, heat exchange shape mapping is performed on the ventilation duct to obtain duct shape data; The duct shape data is iteratively optimized according to various influencing factors of the comfort physiological information to obtain the ventilation duct information.

4. The method according to claim 1, wherein The step of inputting the comfort physiological information and the ventilation duct information into a fan control model of the car seat to obtain initial fan operating parameters corresponding to each fan in the car seat includes: Partitioning the car seats according to the comfort physiological information to obtain partition information of each car seat; intercepting the zone comfort information corresponding to each of the car seat zone information from the comfort physiological information; For any of the automobile seat partition information, calculating the pressure amplification information and the local corrected heat load corresponding to the automobile seat partition information according to the partition comfort information; multiplying the pressure amplification information and the local corrected heat load to obtain zone demand information; According to the partition requirement information and the ventilation duct information, the operating parameters of each fan of the car seat are adjusted to obtain the initial fan operating parameters corresponding to each fan.

5. The method according to claim 4, characterized in that The step of adjusting the operating parameters of the fans of the car seat according to the partition requirement information and the ventilation duct information to obtain the initial fan operating parameters corresponding to the fans includes: Calculating the target air volume corresponding to each fan according to the partition demand information and the ventilation duct information; Calculating the initial fan speed corresponding to each fan according to the mapping relationship between the fan speed and the target air volume of each fan; Calculating the target dynamic wind direction corresponding to each of the fans according to the initial speed of each of the fans and the ventilation duct information; The ventilation power of the car seat is optimized according to the target air volume and target dynamic wind direction of each of the fans, and the initial fan operating parameters corresponding to each of the fans are obtained.

6. The method according to claim 5, characterized in that The calculation expression of the initial fan operating parameters is: ， Among them, D i is the partition demand information of the i-th area, i is the seat partition index, p i is the contact pressure on the i-th region, p avg is the average contact pressure in the entire area, k p is the pressure amplification factor, h i is the convective heat transfer coefficient of region i, A i is the effective heat dissipation area of ​​the i-th region on the contact surface, T skin is the occupant's skin temperature, T seat,i is the surface temperature of the seat in area i, is the humidity correction factor; J is the initial fan operating parameter, M is the total number of regions, j is the fan identifier, N is the total number of fans, is the index set of fans supplying air to the i-th area, is the ventilation distribution coefficient of fan j to the i-th area, is the wind direction of fan j, For the speed And the wind direction is The actual air volume output when is the speed of fan j, The fan j is at a speed of The power consumption, is the demand balancing factor, is the energy consumption for wind direction regulation at wind turbine j, The weighting factor for adjusting energy consumption according to wind direction.

7. A device for determining vehicle seat ventilation parameters, characterized in that: The device comprises: An information acquisition module, configured to acquire three-dimensional contour information of a target object on a car seat, physiological information of the target object, and in-car environment information; an information analysis module, configured to perform a comfort analysis on the target object based on 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 is used to construct ventilation duct information of the car seat based on the three-dimensional contour information, taking the comfort physiological information as a target condition; the ventilation duct information is obtained by solving the heat exchange equations of the car seat using computational fluid dynamics; the heat exchange equations include a fluid continuity equation, an air momentum equation, a temperature transfer equation, and a humidity transfer equation. The calculation expression of the ventilation duct information is: in, For 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 For passengers to feel the pressure, is the regularization coefficient of the air duct distribution function, is the spatial gradient term of the wind duct distribution function, It is the contact surface between the seat and the passenger. is the three-dimensional volume domain inside the seat, T is the temperature field, and H is the humidity field; The expression of the fluid continuity equation is, ， The expression of the air momentum equation is, ， The expression of the temperature transfer equation is, ， The expression of the humidity transfer equation is, in, is the fluid velocity vector; is the air density, p is the air static pressure, is the air viscosity, is the airflow permeability that changes with the spatial coordinate x of the air duct, is the Forchheimer coefficient; is the specific heat capacity of air, T is the temperature field, is the equivalent thermal conductivity, is the heat source data that changes with the spatial coordinate x of the air duct; H is the humidity field, D is the equivalent humidity diffusion coefficient, is the humidity that changes with the spatial coordinate x of the air duct; a parameter calculation module, configured to input the comfort physiological information and the ventilation duct information into a 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, configured 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, configured to optimize the initial fan operating parameters for energy saving according to the fan operating information for any of the fans, and 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 car seat.

8. A computer comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

Images