Seat ventilation control method for new energy automobile

Abstract

The invention discloses a new energy automobile seat ventilation control method which comprises the following steps: S1, monitoring the use state of a seat in real time through a passenger sensing module, and taking the use state as an activation triggering condition of a ventilation function; s2, collecting temperature and humidity data of the surface of the seat in real time, and intelligently switching an air suction mode and an air blowing mode based on the temperature and humidity data; and S3, a learning mechanism is introduced to record preference parameters of the user for the ventilation mode and the wind speed, and a personalized configuration library is formed. According to the new energy automobile seat ventilation control method, the seat ventilation mode and the wind speed are intelligently selected by monitoring the seat use state and the environment temperature and humidity data in real time and combining the user preference and the feedback information of the vehicle-mounted association system. According to the self-adaptive control mechanism, the comfort of seat ventilation is improved, the wind speed can be dynamically optimized according to different environments and user requirements, and it is ensured that a user always enjoys the optimal seat ventilation experience.

Description

Technical Field

[0001] This invention relates to the field of automotive seat ventilation control, and more specifically, to a seat ventilation control method for new energy vehicles. Background Technology

[0002] With the increasing popularity of new energy vehicles, car owners are demanding greater comfort during driving. Seat ventilation, as an important in-car comfort feature, can effectively alleviate discomfort caused by seat temperature and humidity during long drives. Currently, most seat ventilation systems on the market rely on simple fan speed adjustment modes, failing to fully consider seat usage, environmental factors, and individual user needs, resulting in insufficient system comfort and energy efficiency.

[0003] Traditional seat ventilation systems typically rely on fixed mode switching and simple fan speed adjustments, lacking intelligent responses to users' personalized needs. They cannot automatically adjust ventilation parameters based on different driving environments, seat conditions, and user preferences, resulting in high energy consumption and poor comfort. Furthermore, existing seat ventilation control systems generally lack adaptive capabilities, failing to dynamically optimize and adjust energy efficiency through real-time data feedback, leading to significant variations in seat ventilation performance across different driving scenarios.

[0004] To improve the comfort and energy efficiency of seat ventilation, intelligent control systems based on sensor data and user preferences are gradually becoming a research trend, especially the need to introduce learning mechanisms and linkage with in-vehicle systems to achieve more precise control. Summary of the Invention

[0005] The purpose of this invention is to provide a seat ventilation control method for new energy vehicles, which solves the problems of traditional seat ventilation systems that usually rely on fixed mode switching and simple wind speed adjustment, lack intelligent response to the personalized needs of users, and cannot automatically adjust ventilation parameters according to different driving environments, seat conditions and user preferences, resulting in high energy consumption and poor comfort.

[0006] This invention achieves the above objective through the following technical solution: a method for controlling seat ventilation in a new energy vehicle, comprising the following steps: S1. The seat usage status is monitored in real time through the occupant sensing module, and the usage status is used as the activation trigger condition for the ventilation function. S2. Collect temperature and humidity data of the seat surface in real time, and intelligently switch between suction mode and blowing mode based on the temperature and humidity data; S3. Introduce a learning mechanism to record users' preferences for ventilation modes and wind speeds, forming a personalized configuration library; S4. Establish linkage with the vehicle-mounted system and dynamically adjust the start-up timing and operating parameters of the ventilation function based on the environmental prediction information and operating status fed back by the system. S5. Based on real-time monitoring data, user preference parameters, and feedback from the linkage system, dynamically optimize ventilation output to achieve adaptive and energy-saving seat ventilation control.

[0007] Furthermore, the step of monitoring the seat usage status in real time through the occupant sensing module includes: The occupant sensing module uses a dual sensing mechanism that combines pressure sensing and infrared detection to collect data on the seat's load pressure and infrared sensing intensity. Set the load pressure threshold, infrared sensing intensity threshold, and duration threshold, and construct usage status judgment rules; Based on the comparison results of the bearing pressure data, infrared sensing intensity data and various thresholds, a ventilation function activation permission signal or shutdown signal is generated in combination with timing logic. The usage status determination rules include the determination conditions for active status, closed status, and maintaining the status of the previous moment.

[0008] Furthermore, the usage status determination rule is specifically as follows: When the detected bearing pressure data is not less than the bearing pressure threshold, the infrared sensing intensity data is not less than the infrared sensing intensity threshold, and the preset duration threshold is met, it is determined to be in an active state. When the detected bearing pressure data is less than the bearing pressure threshold or the infrared sensing intensity data is less than the infrared sensing intensity threshold, and the interruption timer duration reaches the preset interruption threshold, it is determined to be in the off state. Except for the two situations mentioned above, maintain the seat usage status from the previous moment.

[0009] Furthermore, the step of real-time collection of temperature and humidity data of the seat surface and intelligent switching of ventilation modes includes: Multiple temperature and humidity sensors are installed in the seat cushion and backrest area of ​​the seat, and temperature and humidity data of each sensor are collected according to a preset sampling period. The average values ​​of the collected temperature and humidity data were calculated to obtain the average temperature and average humidity values ​​of the seat surface. A preset temperature threshold range and humidity threshold are used to construct a mode switching judgment coefficient, which is calculated by combining temperature weight and humidity weight. Based on the comparison results of average temperature value, average humidity value and threshold, and the mode switching judgment coefficient, the system intelligently selects the suction mode or the blowing mode and matches the corresponding wind speed level to achieve a smooth transition between mode and wind speed.

[0010] Furthermore, the wind speed levels include high, medium, and low wind speeds, and the wind speed adjustment logic is as follows: When the average temperature is higher than the first temperature threshold and the average humidity is not lower than the humidity threshold, the blowing mode is activated and matched with a high fan speed. The fan speed value is dynamically adjusted based on the mode switching judgment coefficient. When the average temperature value is between the first temperature threshold and the second temperature threshold, switch to the suction mode and match the medium fan speed. The fan speed value is linearly adjusted according to the mode switching judgment coefficient. When the average temperature value is lower than the second temperature threshold and the average humidity value is lower than the humidity threshold, a low wind speed is used. The wind speed value is adjusted in the opposite direction based on the absolute value of the mode switching judgment coefficient, and the wind speed change rate does not exceed the preset limit.

[0011] Furthermore, the step of introducing a learning mechanism to form a personalized configuration library includes: Record relevant data of the user's manual adjustment operation, including ambient temperature at the time of adjustment, average seat temperature, average seat humidity, ventilation mode after adjustment, wind speed parameter after adjustment, and user identification. We perform weighted learning on users' historical operation data, introduce a time decay weight factor, give priority to the impact of recent operation data, and calculate the user's preference weight for ventilation mode in different scenarios. A similarity measurement model is built based on Gaussian function, and the user's preferred wind speed in the current scenario is calculated by combining the similarity of ambient temperature and seat temperature and humidity. Establish a personalized configuration library associated with user identity identifiers, support the binding of multiple user identities, and automatically match the preference parameters of the optimal scenario when the corresponding user identity is detected to be seated.

[0012] Furthermore, the step of establishing linkage with the vehicle-mounted system includes: The in-vehicle system includes at least a navigation system and an in-vehicle air conditioning system. It receives ambient temperature prediction data for a future preset time period transmitted by the navigation system and calculates the average predicted temperature. The seat ventilation function is activated in advance based on the average predicted temperature, and the preset ventilation mode and initial airflow are activated before the vehicle is started or before the user sits down. The set temperature and operating status of the vehicle's air conditioning system are obtained, and combined with the vehicle's remaining battery power data, air conditioning linkage adjustment coefficient and energy-saving adjustment coefficient are constructed respectively. Based on the air conditioning linkage adjustment coefficient and the energy-saving adjustment coefficient, the basic wind speed is dynamically corrected to obtain the ventilation wind speed after linkage adjustment. The corrected wind speed does not exceed the maximum wind speed limit and is not lower than the minimum wind speed limit.

[0013] Furthermore, the logic for determining the advance start time is as follows: When the average predicted temperature is not lower than the preset high temperature threshold, the advance start time is calculated based on the difference between the average predicted temperature and the high temperature threshold, and the advance start time shall not exceed the preset maximum advance time. When the average predicted temperature is lower than the preset high temperature threshold, the pre-ventilation function will not be activated until the ventilation activation conditions are met.

[0014] Furthermore, the step of dynamically optimizing ventilation output includes: A comprehensive decision-making index is constructed by integrating the mode switching judgment coefficient corresponding to real-time monitoring data, the proportion of preferred wind speed corresponding to user preference parameters, and the comprehensive adjustment coefficient corresponding to the feedback from the linkage system. The index is calculated according to a preset weight allocation rule, in which real-time monitoring data has the highest weight, and the weights of user preference and linkage feedback are evenly distributed. Based on the numerical range of the comprehensive decision-making index, optimize the selection of ventilation mode and wind speed adjustment: when the comprehensive decision-making index is not lower than the first decision threshold, prioritize the blowing mode and appropriately increase the wind speed. When the comprehensive decision-making index is between the first decision threshold and the second decision threshold, maintain the current ventilation mode and dynamically adjust the wind speed according to the index value; When the comprehensive decision-making index is lower than the second decision-making threshold, the suction mode should be selected first and the wind speed should be reduced appropriately. If a user performs a manual adjustment, the system will respond to the manual command immediately, update the adjustment data to the personalized configuration library, and increase the weight of the data from this operation in the weighted learning process.

[0015] Furthermore, it also includes the dynamic update steps for the personalized configuration library: Historical data in the personalized configuration library is filtered according to a preset period, and invalid data with a weight lower than a preset threshold is removed. Based on the difference between the average ambient temperature within the cycle and the average ambient temperature throughout the year, the temperature threshold benchmark is dynamically adjusted to adapt ventilation control to seasonal temperature changes. We continuously iterate and update the user preference weight and preference wind speed calculation model to improve the accuracy and adaptability of personalized configurations.

[0016] The beneficial effects of this invention are as follows: 1. By monitoring the seat usage status and ambient temperature and humidity data in real time, and combining user preferences and feedback information from the vehicle's related systems, the system intelligently selects the seat ventilation mode and airflow speed. The adaptive control mechanism not only improves the comfort of seat ventilation, but also dynamically optimizes the airflow speed according to different environments and user needs, ensuring that users always enjoy the best seat ventilation experience.

[0017] 2. By dynamically adjusting the start-up timing and operating parameters of the ventilation function based on real-time monitoring data and environmental prediction information, this invention can effectively reduce energy consumption, avoid excessive ventilation, improve the energy efficiency of the seat ventilation system, and enable it to achieve a more energy-saving control strategy in different driving environments.

[0018] 3. A learning mechanism has been introduced. By recording and analyzing users' preferences for ventilation modes and air speeds, a personalized configuration library has been established. When the car owner uses the seat again, the system can automatically match the ventilation mode and air speed settings that best suit personal habits, thereby improving user comfort and user experience.

[0019] 4. By linking with the vehicle navigation system and air conditioning system, this invention can activate the seat ventilation function and adjust the fan speed in advance based on the predicted ambient temperature and the operating status of the vehicle air conditioning, so that the driver can enjoy the preset comfortable environment before getting into the car, and optimize the ventilation speed according to the settings of the vehicle air conditioning to improve overall energy efficiency.

[0020] 5. By combining real-time monitoring data, user preference parameters, and feedback information from the vehicle system, dynamic optimization is performed using comprehensive decision indicators to ensure that the seat ventilation function achieves optimal energy efficiency while ensuring comfort, thus avoiding energy waste. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the seat usage status monitoring process of the present invention; Figure 2 This is a diagram illustrating the temperature and humidity data acquisition and mode switching of this invention. Figure 3 This is a flowchart of the linkage control process of the vehicle system of the present invention. Detailed Implementation

[0022] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0023] Example 1: Please see Figure 1-3 This invention provides a technical solution: a method for controlling seat ventilation in new energy vehicles, the method comprising: S1. The seat usage status is monitored in real time through the occupant sensor, and the usage status is used as the trigger condition for activating the ventilation function. Among them, the occupant sensor is a sensor device that can detect whether there is an occupant in the seat. It determines the usage status of the seat by detecting changes in signals such as pressure, infrared, and capacitance, and provides a trigger for activating the ventilation function. The seat usage status refers to whether the seat is currently being used by an occupant, including both occupied and unoccupied states, which is the key condition for triggering the seat ventilation function to turn on or off. Ventilation function activation is when specific conditions are met, such as when the seat is being used by an occupant, the seat ventilation system is activated to start working and provide ventilation for the occupant. S2. Real-time collection of temperature and humidity data on the seat surface, and intelligent switching between suction mode and blowing mode based on the temperature and humidity data. The suction mode improves comfort through stable and gentle airflow, while the blowing mode is used for rapid cooling. Among them, temperature and humidity data are collected in real time by specific sensors to collect temperature and humidity information of the seat surface. This data reflects the environmental conditions of the seat surface and is an important basis for deciding on the ventilation mode switching. The suction mode is a working mode of the seat ventilation system. It draws the air around the seat into the seat to form a stable and gentle airflow, making the occupants feel comfortable. It mainly focuses on improving the comfort of the ride. The blowing mode is another working mode of the seat ventilation system. It blows air out onto the seat surface to quickly remove heat and achieve a rapid cooling effect. It is suitable for scenarios that require a rapid reduction in seat temperature. S3. Introduce a learning mechanism to record users' preferences for ventilation modes and wind speeds, forming a personalized configuration library; The learning mechanism is an intelligent algorithm or program logic that can record and analyze users' operating habits and preferences when using the seat ventilation function, such as the selection of ventilation mode and wind speed. User preference parameters are the personal preference settings that users show when using the seat ventilation function, including preferred ventilation mode, suction or blowing, and wind speed. These parameters are used to form a personalized configuration library. The personalized configuration library is a database that stores user preference parameters. The system can provide users with seat ventilation settings that match their personal habits based on the information in the library, thereby achieving personalized ventilation control. S4. Establish linkage with the vehicle air conditioning system and navigation system, and dynamically adjust the start timing and operating parameters of the ventilation function based on the ambient temperature information predicted by the navigation system and the operating status of the vehicle air conditioning system. The vehicle's air conditioning system, installed inside the car, regulates the temperature, humidity, and air quality, providing a comfortable driving environment for passengers. The navigation system plans routes and provides navigation information; besides basic navigation, it predicts ambient temperatures and other information the vehicle might encounter during travel. Ambient temperature information, predicted by the navigation system based on the vehicle's route and weather forecasts, indicates the future ambient temperature of the vehicle's location, providing valuable information for the dynamic adjustment of the seat ventilation function. The vehicle's air conditioning operating status refers to its current mode, such as cooling, heating, or ventilation, as well as operating parameters like temperature settings and fan speed. The seat ventilation system adjusts accordingly based on this status. The ventilation function's activation timing is determined by the navigation system's predicted ambient temperature and the vehicle's air conditioning operating status, ensuring optimal ventilation and energy efficiency. Operating parameters are the various settings of the seat ventilation system during operation, such as ventilation mode and fan speed, which are dynamically adjusted based on feedback from the linkage system. S5. Based on real-time monitoring data, user preference parameters, and feedback from the linkage system, dynamically optimize ventilation output to achieve adaptive and energy-saving seat ventilation control; The real-time monitoring data includes seat usage status monitored by occupant sensors and seat surface temperature and humidity data collected by temperature and humidity sensors, reflecting the current actual condition of the seat. User preference parameters are user preference settings for ventilation modes, fan speed, etc., obtained from the personalized configuration library. The linkage system feedback is relevant data and suggestions fed back to the seat ventilation system by the vehicle's air conditioning system and navigation system based on their own operating conditions and predictive information, which guides the adjustment of ventilation functions. Dynamically optimized ventilation output is achieved by the seat ventilation system automatically adjusting operating parameters such as ventilation mode and fan speed based on real-time monitoring data, user preference parameters, and linkage system feedback, realizing adaptive ventilation control while achieving energy saving. Adaptive and energy-saving seat ventilation control is an intelligent control method that can automatically adjust the ventilation function according to the actual condition of the seat, user needs, and the overall vehicle environment, reducing energy consumption while meeting the comfort needs of occupants.

[0024] It should be noted that when in use, the ventilation function is triggered based on the seat's usage status, enabling precise and on-demand activation to avoid energy waste. Based on the seat surface temperature and humidity data, it intelligently switches between suction and blowing modes. The suction mode provides a stable and gentle airflow to enhance comfort, while the blowing mode can quickly cool the seat, meeting the needs of different scenarios. A learning mechanism is incorporated to record user preference parameters, forming a personalized configuration library to provide users with a customized ventilation experience. It also works in conjunction with the vehicle's air conditioning and navigation system, dynamically adjusting the ventilation activation timing and parameters based on predicted ambient temperature and air conditioning operating status, enhancing overall coordination. It dynamically optimizes ventilation output based on various data points, achieving adaptive control and flexibly adjusting according to actual conditions. While ensuring passenger comfort, it effectively reduces energy consumption and improves the range and user experience of new energy vehicles.

[0025] In one embodiment, the seat usage status is monitored in real time via an occupant sensor, including: The occupant sensor (SBR) collects the seat's load pressure values ​​through a dual mechanism of pressure sensing and infrared detection. (Unit: N) Infrared sensing intensity value (Unit: lux) Set bearing pressure threshold 50N, infrared sensing intensity threshold 10 lux and duration threshold It lasts for 5 seconds; When detected ≥ and ≥ When the timer starts, if the continuous timing duration t≥t0, a ventilation function activation permission signal is generated; If detected < or < Start the interrupt timer, and when the interrupt timer duration is reached... The ventilation function will automatically shut off after 15 seconds. Interruption timer duration <15 seconds and recover ≥ , ≥ At that time, continue to maintain the original ventilation status; Use the state determination formula:

[0026] in =1 indicates an active state. =0 indicates the off state. This indicates the state at the previous moment.

[0027] This design utilizes a dual mechanism of pressure sensing and infrared detection, combining load pressure, infrared intensity, and duration thresholds to determine the seat's usage status. This allows for accurate and reliable determination of whether the seat is occupied. The dual detection mechanism avoids potential misjudgments that can occur with a single detection method. For example, pressure sensing alone may lead to misjudgments due to the placement of objects, while infrared detection alone may be affected by ambient light interference. The timing and interruption logic allows for flexible responses to situations such as brief absences of personnel, preventing frequent start-stop of the ventilation function. This ensures that the ventilation function is activated as needed, while also improving ease of use and energy efficiency, providing an accurate basis for subsequent activation of the ventilation function.

[0028] In one embodiment, real-time temperature and humidity data of the seat surface are collected, and the suction mode and blowing mode are intelligently switched based on the temperature and humidity data, including: Three temperature and humidity sensors were installed on both the seat cushion and the backrest to collect temperature values ​​from each sensor. Humidity value Calculate the average:

[0029] The sampling period is 1 second; Preset temperature threshold For 30℃, 25℃ and humidity thresholds (60%), Define the mode switching judgment coefficient:

[0030] in =0.6、 =0.4 is the weighting coefficient, which is determined based on the general understanding that the influence of temperature on perceived comfort has a higher priority than that of humidity; when and When K≥1, activate the blowing mode, with the following wind speed: (upscale); when When 0 ≤ K < 1, switch to suction mode, fan speed: (Mid-range); when and When K < 0, the wind speed is: (Low-end); Recalculated every 3 seconds , and Value, execution mode and wind speed adjustment, wind speed change rate not exceeding 0.5m / s 2 This achieves a smooth transition.

[0031] This design incorporates temperature and humidity sensors at multiple locations on the seat to calculate average values. Based on preset thresholds and mode switching coefficients, it intelligently switches between suction and blowing modes and dynamically adjusts the airflow speed. This comprehensive and accurate acquisition of temperature and humidity information from the seat surface avoids localized data deviations from affecting the judgment. By comprehensively considering both temperature and humidity, with a higher weight given to temperature, it aligns with the principles of human comfort. Different airflow speeds and modes are set according to different temperature and humidity ranges, precisely meeting the ventilation needs of the human body in different environments. This achieves rapid cooling or stable and comfortable ventilation, and the smooth transition of airflow speed enhances the user experience, effectively improving the comfort and practicality of seat ventilation.

[0032] In one embodiment, a learning mechanism is introduced to record users' preferences for ventilation modes and wind speeds, forming a personalized configuration library, including: Record user manual adjustment data, including the ambient temperature at the time of adjustment. Average seat temperature Average humidity of seats Adjusted mode (1 = suction, 2 = blowing), adjusted wind speed and user identification ; We perform weighted learning on user action data to calculate preference weights for different scenarios:

[0033] in =1,2, corresponding to two modes respectively. For indicator functions, when hour =1, otherwise =0, For time decay weight, This refers to the historical operation time. The current time; Preferred wind speed calculation:

[0034] in =5 (Temperature unit: °C, Humidity unit: %) Establish a user-customized configuration library It supports binding up to 8 user identities, and automatically matches the preference parameters of the optimal scenario when the corresponding ID user is detected to be seated.

[0035] This design records user manual adjustment data and uses weighted learning to calculate user preferences for ventilation modes and fan speeds in different scenarios. It establishes a personalized configuration library, fully considering individual differences and usage habits. Based on user operations in various environments, including ambient temperature and seat humidity, it accurately learns user preferences. The time decay weighting makes recent operations have a greater impact on preference judgment, better aligning with actual user needs. By establishing a configuration library, it automatically matches the optimal parameters when the user is seated, providing personalized and considerate ventilation services, improving user satisfaction and product competitiveness, and meeting diverse market demands.

[0036] In one embodiment, establishing linkage with the vehicle's air conditioning system and navigation system includes: Receive ambient temperature forecast values ​​for the next 1-3 hours transmitted by the navigation system. , Calculate the average predicted temperature for the predicted time point:

[0037] like ℃, calculate the advance start time:

[0038] Unit: minutes, maximum advance notice 5 minutes; After the vehicle start signal is triggered or before the user sits down Minutes later, activate suction mode, initial fan speed. Maximum ; Get the vehicle air conditioning set temperature Operating status (1 = On, 0 = Off), calculate the linkage adjustment coefficient: ; Based on the vehicle's remaining battery power (Unit: %), Energy saving coefficient ;

[0039] Final linkage wind speed adjustment: ,in This is the base wind speed without any linkage, and , .

[0040] This design receives the navigation system's predicted ambient temperature, calculates the average predicted temperature, and determines the advance start time and initial wind speed. It also obtains the vehicle's air conditioning set temperature and operating status, calculates the linkage adjustment coefficient and energy-saving coefficient based on the vehicle's remaining battery power, and finally adjusts the linkage wind speed. By fully utilizing information from other vehicle systems, it enables multi-system collaborative work. By starting ventilation in advance based on the navigation's predicted temperature, it can create a comfortable environment for users. By adjusting the wind speed based on the air conditioning status and battery power, it ensures both the ventilation effect and the compatibility with the air conditioning system, while also considering energy-saving needs. This improves user comfort, optimizes energy utilization, extends vehicle range, and enhances overall vehicle performance and user experience.

[0041] In one embodiment, the ventilation output is dynamically optimized based on real-time monitoring data, user preference parameters, and feedback from the linkage system, including: Integrating multi-source data to construct comprehensive decision indicators:

[0042] in =0.4、 =0.3、 =0.3 is the weighting coefficient; Weight allocation logic: For real-time monitoring, the weight is set to 0.4. User preference weight = 0.3 The linkage feedback weight is set to 0.3 to prioritize real-time environment adaptability while also considering personalization and system collaboration. Optimize ventilation mode and air velocity based on D value: When D≥1.2, the blowing mode should be selected first. ; When 0.8 ≤ D < 1.2, maintain the current mode. ; When D < 0.8, the suction mode should be selected first. ; If the user performs a manual adjustment, the system will respond to the manual command immediately. , And update the personalized configuration library:

[0043] Simultaneously adjust learning weights ; The configuration library is updated weekly, and weights are removed. Historical data was used, and the seasonal temperature threshold baseline was recalculated:

[0044] in This represents the difference between the weekly average ambient temperature and the annual average ambient temperature.

[0045] This design integrates real-time monitoring data, user preference parameters, and feedback from the linkage system to construct comprehensive decision indicators. Based on these indicator values, it optimizes ventilation modes and wind speeds, while responding to manual adjustments and updating the configuration library. It also periodically updates the configuration library and temperature threshold benchmarks. By comprehensively considering multiple factors, it makes ventilation control more scientific, rational, intelligent, and adaptive. The weight allocation logic prioritizes real-time environmental adaptability, balancing personalization and system collaboration. It can accurately adjust ventilation according to different situations, responding to manual adjustments and updating the configuration library, reflecting respect for and learning from user actions. Regular updates to the configuration library and temperature thresholds adapt to seasonal changes and evolving user habits, continuously improving the accuracy and effectiveness of ventilation control and providing users with a consistently high-quality ventilation experience.

[0046] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A new energy vehicle seat ventilation control method, characterized in that, The method comprises the following steps: S1, real-time monitoring of seat usage state by passenger sensing module, using the usage state as the activation trigger condition of the ventilation function; S2, real-time collection of temperature and humidity data on the seat surface, intelligent switching of air suction mode and air blowing mode based on the temperature and humidity data; S3, introducing a learning mechanism to record user preferences for ventilation mode and wind speed, forming a personalized configuration library; S4, linkage with the vehicle-mounted association system, dynamic adjustment of the start time and operating parameters of the ventilation function based on the environmental prediction information and operating state feedback from the association system; S5, dynamic optimization of ventilation output based on real-time monitoring data, user preference parameters, and linkage system feedback, realizing adaptive and energy-saving seat ventilation control.

2. The new energy vehicle seat ventilation control method of claim 1, wherein, The step of real-time monitoring of seat usage state by passenger sensing module comprises: Using the passenger sensing module to collect seat load pressure data and infrared intensity data through a dual sensing mechanism combining pressure sensing and infrared detection; Setting load pressure threshold, infrared intensity threshold, and duration threshold to construct usage state judgment rules; Based on the comparison results of the load pressure data, infrared intensity data, and each threshold, combining timing logic to generate ventilation function activation permission signals or shutdown signals; The usage state judgment rules include activation state, shutdown state, and judgment conditions for maintaining the state at the previous time.

3. The new energy vehicle seat ventilation control method of claim 2, wherein, The usage state judgment rules are as follows: When the detected load pressure data is not less than the load pressure threshold, the infrared intensity data is not less than the infrared intensity threshold, and the preset duration threshold is met, it is determined to be in the activation state; When the detected load pressure data is less than the load pressure threshold or the infrared intensity data is less than the infrared intensity threshold, and the interrupted timing length reaches the preset interruption threshold, it is determined to be in the shutdown state; Except for the above two cases, the seat usage state at the previous time is maintained.

4. The new energy vehicle seat ventilation control method of claim 1, wherein, The step of real-time collection of temperature and humidity data on the seat surface and intelligent switching of ventilation mode comprises: Multiple temperature and humidity sensors are arranged in the seat cushion and backrest area, and temperature and humidity data of each sensor are collected at a preset sampling period; The collected multiple sets of temperature and humidity data are respectively subjected to mean value calculation to obtain the average temperature and humidity values of the seat surface; A temperature threshold interval and a humidity threshold are preset to construct a mode switching judgment coefficient, which is calculated based on temperature weight and humidity weight; Based on the comparison results of the average temperature and humidity values and the thresholds, and the mode switching judgment coefficient, the air suction mode or air blowing mode is intelligently selected, and the corresponding wind speed level is matched to realize smooth transition of mode and wind speed.

5. The new energy vehicle seat ventilation control method of claim 4, wherein, The wind speed level includes high, medium, and low wind speed, and the wind speed adjustment logic is as follows: When the average temperature value is higher than the first temperature threshold and the average humidity value is not lower than the humidity threshold, the air blowing mode is started and the high wind speed is matched, and the wind speed value is dynamically adjusted based on the mode switching judgment coefficient; When the average temperature value is between the first temperature threshold and the second temperature threshold, the air suction mode is switched to and the medium wind speed is matched, and the wind speed value is linearly adjusted with the mode switching judgment coefficient. When the average temperature value is lower than the second temperature threshold and the average humidity value is lower than the humidity threshold, a low-grade wind speed is adopted, the wind speed value is reversely adjusted based on the absolute value of the mode switching judgment coefficient, and the wind speed change rate does not exceed a preset limit value.

6. The new energy vehicle seat ventilation control method of claim 1, wherein, The step of introducing the learning mechanism to form the personalized configuration library comprises: Recording relevant data of the user's manual adjustment operation, the data comprising the ambient temperature, the average seat temperature, the average seat humidity, the adjusted ventilation mode, the adjusted wind speed parameter and the user identity at the time of adjustment; Performing weighted learning on the user's historical operation data, introducing a time decay weight factor to preferentially consider the influence of recent operation data, and calculating the user's preference weight for the ventilation mode in different scenarios; Based on the Gaussian function, a similarity measurement model is constructed, the similarity of the ambient temperature, the seat temperature and humidity is calculated, and the user's preferred wind speed in the current scenario is calculated; A personalized configuration library associated with the user identity is established, multiple user identities are bound, and when a user corresponding to the identity is detected to be seated, the preferred parameters of the optimal scenario are automatically matched.

7. The new energy vehicle seat ventilation control method of claim 1, wherein, The step of establishing linkage with the vehicle-mounted association system comprises: The vehicle-mounted association system at least comprises a navigation system and a vehicle-mounted air conditioning system, receives the predicted ambient temperature data of the future preset time period transmitted by the navigation system, and calculates the average predicted temperature; Based on the average predicted temperature, the advance start time of the seat ventilation function is determined, and the preset ventilation mode and the initial wind speed are started before the vehicle starts or the user sits down; The set temperature and operating state of the vehicle-mounted air conditioning system are obtained, combined with the remaining power data of the vehicle, the air conditioning linkage adjustment coefficient and the energy-saving adjustment coefficient are respectively constructed; Based on the air conditioning linkage adjustment coefficient and the energy-saving adjustment coefficient, the basic wind speed is dynamically corrected to obtain the linkage adjusted ventilation wind speed, and the corrected wind speed does not exceed the maximum wind speed limit and is not lower than the minimum wind speed limit. 8.The new energy vehicle seat ventilation control method of claim 7, characterized in that, The determination logic of the advance start time is: When the average predicted temperature is not lower than the preset high temperature threshold, the advance start time is calculated according to the difference between the average predicted temperature and the high temperature threshold, and the advance start time does not exceed the preset maximum advance time; When the average predicted temperature is lower than the preset high temperature threshold, the advance ventilation function is not started, and is started again after the ventilation activation condition is met.

9. The new energy vehicle seat ventilation control method of claim 1, wherein, The step of dynamically optimizing the ventilation output comprises: Fusing the mode switching judgment coefficient corresponding to the real-time monitoring data, the preferred wind speed proportion corresponding to the user preference parameter, and the comprehensive adjustment coefficient corresponding to the linkage system feedback, constructing a comprehensive decision index, and calculating the index according to a preset weight distribution rule, wherein the real-time monitoring data has the highest weight, and the user preference and the linkage feedback have balanced weights; Based on the numerical range of the comprehensive decision index, the ventilation mode selection and the wind speed adjustment are optimized: when the comprehensive decision index is not lower than the first decision threshold, the blowing mode is preferentially selected and the wind speed is appropriately increased; When the comprehensive decision index is between the first decision threshold and the second decision threshold, the current ventilation mode is maintained and the wind speed is dynamically adjusted according to the index value; When the comprehensive decision index is lower than the second decision threshold, the suction mode is preferentially selected and the wind speed is appropriately reduced; If the user performs a manual adjustment operation, the system responds to the manual instruction in real time and updates the current adjustment data to the personalized configuration library, while increasing the weight of the current operation data in the weighted learning. 10.The new energy vehicle seat ventilation control method of claim 9, characterized in that, It also includes a dynamic updating step of the personalized configuration library: Filtering the historical data in the personalized configuration library according to a preset period, and eliminating invalid data with a weight lower than a preset threshold; Based on the difference between the average ambient temperature in the period and the average ambient temperature throughout the year, dynamically adjusting the temperature threshold reference to make the ventilation control adapt to seasonal temperature changes; Continuously updating the user preference weight and the preferred wind speed calculation model to improve the accuracy and adaptability of the personalized configuration.

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