Intelligent control method, system and equipment for automobile seat and medium

Abstract

The invention relates to an intelligent control method, system and device for an automobile seat and a medium, and belongs to the field of automobile seat adjustment control. The intelligent control method comprises the steps that a control instruction data packet from a mobile terminal is received and converted into a vehicle CAN bus protocol data frame; analyzing an operation mode identifier in a vehicle CAN bus protocol data frame, and matching a corresponding target attitude parameter set; based on the real-time temperature data in the vehicle, dynamic compensation calculation is executed on the target attitude parameter set, and an after-compensation execution instruction set is generated; a motor control signal is sent to a seat executing mechanism; calculating a deviation value between the feedback signal data and the compensated execution instruction set, and if any deviation value exceeds a preset deviation threshold value, generating a mechanism calibration instruction; and acquiring final execution state data of the seat execution mechanism, and feeding back the final execution state data to the mobile terminal. Intelligent seat adjustment based on real-time feedback can be achieved, and it is ensured that a driver obtains the best comfortable experience in different scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automobile seat adjustment control, in particular to an intelligent control method, system, device and medium for automobile seat. BACKGROUND

[0002] With the continuous progress of modern automobile technology, intelligent and automated technology has been widely applied in various aspects of automobiles, especially in the field of seat adjustment. Automobile seats are no longer just a single comfort device, but have developed into an important part that integrates various adjustment functions, comfort enhancement functions and safety functions. Today's automobile seats not only have basic mechanical adjustment functions such as forward and backward, backrest angle, etc., but also combine various automated and intelligent comfort enhancement functions such as seat heating, seat ventilation, seat massage, etc. In addition, with the development of autonomous driving technology, more and more cars begin to have seat adjustment systems to meet the needs of different users and complex driving environment conditions.

[0003] At present, the continuous development of seat adjustment systems enables the seats of vehicles to be adjusted according to the personalized needs of drivers to improve comfort and riding experience. Today's seat adjustment systems usually adopt an electric drive mode, which cooperates with sensors and control modules to realize automated adjustment. With the support of various sensors such as pressure sensors and temperature sensors, the seat can provide optimal sitting posture support. However, common seat adjustment systems mostly rely on manual or basic electric adjustment, lack sufficient real-time sensing and dynamic adjustment functions, and the comfort needs of drivers in different environments and changes in the vehicle interior environment cannot be fully automatically responded, and intelligent adjustment based on real-time feedback cannot be realized. SUMMARY

[0004] In order to realize intelligent adjustment based on real-time feedback, the present application provides an intelligent control method, system, device and medium for automobile seat.

[0005] In a first aspect, the present application provides an intelligent control method for automobile seat, which adopts the following technical solution: An intelligent control method for automobile seat, the intelligent control method comprises: receiving a control instruction data packet from a mobile terminal; the control instruction data packet comprises an operation mode identifier and a user identity identifier; converting the control instruction data packet into a vehicle CAN bus protocol data frame through a wireless communication module, and adding a data check code in the conversion process; The operation mode identifier in the vehicle CAN bus protocol data frame is parsed, and a corresponding target posture parameter set is matched according to a preset strategy mapping table; the target posture parameter set includes a slide rail target displacement value, a backrest target angle value, a shoulder target angle value, an inclination target angle value, and a leg support target state value; Based on real-time temperature data in the vehicle, dynamic compensation calculation is performed on the target posture parameter set to generate a set of post-compensation execution instructions; According to the set of post-compensation execution instructions, a motor control signal is sent to the seat actuator through the vehicle CAN bus; Real-time feedback signal data of the seat actuator is obtained; The deviation value of the feedback signal data and the set of post-compensation execution instructions is calculated, and if any deviation value exceeds a preset deviation threshold, an actuator calibration instruction is generated and re-sent to the corresponding seat actuator; The final execution state data of the seat actuator is obtained and packaged into a wireless transmission format for feedback to the mobile terminal.

[0006] By adopting the above technical solution, based on wireless communication and real-time feedback mechanism, the seat posture is accurately adjusted, and the seat adjustment is optimized according to the real-time temperature data in the vehicle. Through individualization and environmental adaptability adjustment, the driver can obtain the best comfortable experience in different scenes, and finally through the calibration mechanism and feedback mechanism, the accuracy of the seat adjustment is ensured, so that the intelligentization, comfort and safety of the automobile seat are comprehensively improved.

[0007] Optionally, the step of performing dynamic compensation calculation on the target posture parameter set based on real-time temperature data in the vehicle includes: Determine whether the real-time temperature data is higher than a preset upper temperature limit; If yes, add a power level parameter of a seat ventilation device to the target posture parameter set; If no, determine whether the real-time temperature data is lower than a preset upper temperature limit; If lower, add a target temperature parameter of a seat heating device to the target posture parameter set.

[0008] By adopting the above technical solution, the seat adjustment parameters are dynamically compensated based on real-time temperature data in the vehicle, which can adjust the ventilation and heating functions of the seat in real time according to the change of the temperature in the vehicle, thereby providing a more comfortable driving experience. When the temperature is too high, the seat ventilation device will automatically strengthen ventilation to help the people in the vehicle to keep comfortable; and when the temperature is too low, the seat heating device will be enabled to ensure warm and comfortable. Through this intelligent adjustment mechanism, the system can effectively respond to the change of the environmental temperature and automatically perform dynamic adjustment to ensure that the vehicle owner can enjoy the best seat comfort experience in hot or cold environments. The present application improves the intelligence and comfort of the vehicle seat, makes it have stronger environmental adaptability, and enhances the comfort of the vehicle owner in various temperature conditions.

[0009] Optionally, after the step of parsing the operating mode identifier in the vehicle CAN bus protocol data frame and matching the corresponding target posture parameter set according to the preset strategy mapping table, the method further comprises: obtaining a leg rest target state value in the target posture parameter set; in response to the leg rest target state value being a leg rest unfolding state, extracting a user parameter database according to the user identity identifier; reading user height data stored in the user parameter database, and calculating a personalized leg rest unfolding angle value based on a preset formula; optimizing and compensating the target posture parameter set according to the personalized leg rest unfolding angle value.

[0010] By adopting the above technical solution, by combining vehicle CAN bus data analysis, user identity verification, personalized height parameter calculation and accurate adjustment compensation, customized seat adjustment solutions can be provided for different users. This method is particularly suitable for multi-user shared environment and has wide adaptability, which can automatically adjust the seat configuration according to the needs of different users, and improves the intelligent level of seat adjustment and user experience.

[0011] Optionally, the control method further comprises: real-time acquisition of driver eye image data and heart rate sensor data; calculating eyelid closure frequency according to the eye image data; calculating heart rate variability coefficient according to the heart rate sensor data; when the eyelid closure frequency continuously exceeds the preset frequency threshold and the heart rate variability coefficient decreases by more than the first preset percentage compared with the reference value, a primary fatigue trigger marker signal is generated; in response to the primary fatigue trigger marker signal, real-time acquisition of body pressure distribution data of the driver seat backrest and seat cushion and driving posture inclination angle data; calculating a body pressure distribution deviation rate between a body pressure distribution mean and a preset body pressure distribution reference value based on the body pressure distribution data, and outputting a body pressure abnormality signal when the body pressure distribution deviation rate is greater than a second preset percentage; Calculating a posture angle deviation rate between the driving posture angle and a preset posture angle reference value based on the driving posture inclination angle data, and outputting a posture abnormality signal when the posture angle deviation rate is greater than a third preset percentage; When the abnormal body pressure signal and the abnormal posture signal exist at the same time, a fatigue confirmation signal is generated; generating an intervention instruction including vibration control parameters and audio playback parameters in response to the fatigue confirmation signal; The intervention instruction is sent to the seat vibration module and the vehicle audio module via the vehicle CAN bus.

[0012] By employing this technical solution, the system accurately identifies driver fatigue by monitoring the driver's physiological state (eye image data and heart rate data) in real time, combining it with body pressure and posture data. Vibration and audio intervention mechanisms provide a timely response. This multi-dimensional fatigue detection and intervention effectively improves driving safety and significantly reduces the risk of accidents caused by fatigued driving.

[0013] Optionally, when either the abnormal body pressure signal or the abnormal posture signal exists, and the duration of the primary fatigue trigger mark signal exceeds a preset threshold, a fatigue confirmation signal is generated.

[0014] In the above-mentioned implementation, the primary fatigue trigger signal itself indicates that the driver may be showing signs of fatigue. The presence of abnormal body pressure or posture signals further confirms this fatigue state. In particular, if the primary fatigue trigger signal persists for a period of time without changing, the system further determines that the driver may be experiencing prolonged fatigue, and this accumulated fatigue signal becomes increasingly stronger. Therefore, even if either the body pressure or posture signal fails to trigger, the system will generate a fatigue confirmation signal based on the duration of the fatigue signs and the existing physiological change signals, ensuring a timely response to the driver's potential fatigue state.

[0015] Optionally, the step of generating an intervention instruction including vibration frequency parameters and audio playback parameters in response to the fatigue confirmation signal includes: In response to the fatigue confirmation signal, acquiring vehicle ignition cumulative duration data; Determining the corresponding driving duration according to the vehicle ignition cumulative duration data, and determining a target strategy identifier based on a preset strategy index table; Based on the target strategy identifier, extracting corresponding vibration control parameters and audio playback parameters from a parameter database; The vibration control parameters are converted into control instruction frames of the CAN bus protocol, and the audio playback parameters are encapsulated into audio bus protocol data packets, and the intervention instructions are obtained by combining them.

[0016] By adopting this technical solution, the system responds to fatigue trigger marker signals in real time and comprehensively utilizes multiple data inputs, including vehicle ignition cumulative duration data, driving time, and a strategy index table, to provide timely and effective intervention measures for driver fatigue. Through dual intervention methods of vibration control and audio playback, the system intelligently selects intervention strategies based on varying driving durations, precisely adjusting vibration intensity and audio warning volume levels to enhance driver alertness and reduce the risk of fatigue driving. Through the coordination of the CAN bus protocol and the audio bus protocol, intervention commands are accurately and quickly transmitted to the seat vibration module and the vehicle audio system, achieving efficient fatigue response control.

[0017] Optionally, the control method further includes: Real-time acquisition of vehicle control command sequences, real-time temperature data, and feedback signal data from seat actuators; wherein the feedback signal data includes motor encoder signals and CAN bus error frames; Parsing the flag bit data of the CAN bus error frame and generating an error type tag according to a predefined error type mapping rule; wherein the error type includes communication timeout, motor overload and voltage fluctuation; The error type mark is associated with the vehicle control instruction sequence of the corresponding timestamp, the real-time temperature data and the feedback signal data and encapsulated into an enhanced log structure; Selecting an independent storage sector or a circular storage area according to the severity level of the error type mark, and writing the enhanced log structure into a non-volatile memory; The status register of the non-volatile memory is read to verify the integrity of the log data written, and if the verification fails, the data rewriting process is triggered.

[0018] By adopting the above-mentioned technical solution, based on the CAN communication protocol and integrating electrical signal analysis, environmental condition perception and actuator feedback, the entire process from fault behavior perception to storage management is automated and structured, greatly improving the operational monitorability, traceability and fault response efficiency of the vehicle seat control system. It is suitable for scenarios such as smart cars and autonomous driving systems that have extremely high requirements for safety and data integrity.

[0019] In a second aspect, the present application provides an intelligent control system for a car seat, which adopts the following technical solutions: An intelligent control system for a car seat, comprising: The data receiving module is configured to receive a control instruction data packet from the mobile terminal, wherein the control instruction data packet comprises an operation mode identifier and a user identity identifier. The data conversion module is configured to convert the control instruction data packet into a vehicle CAN bus protocol data frame through the wireless communication module and add a data check code in the conversion process. The parameter matching module is configured to parse the operation mode identifier in the vehicle CAN bus protocol data frame and match a corresponding target posture parameter set according to a preset strategy mapping table, wherein the target posture parameter set comprises a target displacement value of a slide rail, a target angle value of a backrest, a target angle value of a shoulder, a target angle value of an inclination, and a target state value of a leg rest. The dynamic compensation module is configured to perform dynamic compensation calculation on the target posture parameter set based on real-time temperature data in the vehicle to generate a set of compensated execution instructions. The motor control module is configured to send motor control signals to the seat actuating mechanism through the vehicle CAN bus according to the set of compensated execution instructions. The feedback acquisition module is configured to acquire feedback signal data of the seat actuating mechanism in real time. The deviation calibration module is configured to calculate deviation values of the feedback signal data and the set of compensated execution instructions, and generate mechanism calibration instructions and resend them to the corresponding seat actuating mechanism if any deviation value exceeds a preset deviation threshold. The data packaging module is configured to acquire final execution state data of the seat actuating mechanism and package it into a wireless transmission format feedback to the mobile terminal.

[0020] In a third aspect, the present application provides a computer device, which adopts the following technical solution: A computer device comprises a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to the first aspect.

[0021] In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical solution: A computer readable storage medium stores a computer program that can be loaded and executed by a processor to implement any one of the methods according to the first aspect.

[0022] In summary, the present application has at least one of the following beneficial technical effects: 1. The present application can not only intelligently adjust the seat position according to the user's needs and environmental conditions, but also accurately optimize it according to individualized parameters to ensure that each user can obtain the most comfortable sitting posture.

[0023] 2. The application also combines ergonomic principles and uses zero-gravity posture automatic adjustment technology to adjust the seat at the optimal angle and position, minimizing the physical stress caused by long driving or riding, thereby improving the comfort and health of driving and riding.

[0024] 3. The application also introduces a fatigue monitoring and intelligent temperature control system that can monitor the driver's fatigue state in real time and automatically adjust the seat posture and the temperature in the car to effectively prevent fatigue driving and ensure that passengers can enjoy the most suitable temperature and comfort in the car regardless of cold or hot environments.

[0025] The integration of these innovative technologies not only greatly improves the comfort, health, and safety of driving and riding, but also makes important technical breakthroughs in the intelligentization and humanization of driving experience, further optimizing the intelligent seat and vehicle environment, and meeting the high requirements of modern consumers for car comfort, convenience, and safety. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 is the first flowchart of the intelligent control method of the car seat according to an embodiment of the application.

[0027] Figure 2 is the second flowchart of the intelligent control method of the car seat according to an embodiment of the application.

[0028] Figure 3 is the third flowchart of the intelligent control method of the car seat according to an embodiment of the application.

[0029] Figure 4 is the fourth flowchart of the intelligent control method of the car seat according to an embodiment of the application.

[0030] Figure 5 is the fifth flowchart of the intelligent control method of the car seat according to an embodiment of the application.

[0031] Figure 6 is the sixth flowchart of the intelligent control method of the car seat according to an embodiment of the application. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the application clearer, the following will combine the drawings and embodiments to further describe the application in detail. It should be understood that the specific embodiments described herein are only used to explain the application and not to limit the application. Figures 1-6

[0033] The embodiments of the application disclose an intelligent control method of a car seat. ​

[0034] Reference Figure 1 , an intelligent control method for a car seat, the intelligent control method comprising: Step S101, receiving a control instruction data packet from a mobile terminal; The control instruction data packet includes an operation mode identifier and a user identity identifier; Specifically, the system receives control command data packets from a mobile terminal (such as a mobile phone or in-vehicle tablet) via a wireless communication module. The operating mode identifier determines the target seat adjustment mode, such as "driving mode," "zero gravity mode," or "resting mode," while the user identifier identifies the current user. This step is crucial for the system to receive and confirm input commands, ensuring they are recognized and ready for subsequent adjustments.

[0035] Step S102, converting the control instruction data packet into a vehicle CAN bus protocol data frame through the wireless communication module, and adding a data check code during the conversion process; After receiving the control command data packet, the system needs to convert it into the vehicle's internal CAN bus protocol data frame. The CAN bus protocol is a widely used communication standard in vehicle electronic control systems, enabling data exchange between the vehicle's various control modules. During this process, the control command data packet is converted into a data format that complies with the CAN protocol via the wireless communication module, allowing the seat control system to understand and execute the command.

[0036] It should be noted that to ensure the accuracy and reliability of data transmission, a data checksum is added during the conversion process to prevent signal loss or tampering during transmission. This conversion ensures that remote control commands can be smoothly transmitted to the seat controller and executed in real-time operation.

[0037] Step S103, parsing the operation mode identifier in the vehicle CAN bus protocol data frame, and matching the corresponding target posture parameter set according to a preset strategy mapping table; The target posture parameter set includes but is not limited to the slide rail target displacement value, the backrest target angle value, the shoulder target angle value, the inclination target angle value and the leg support target state value; Specifically, after the converted CAN bus data frame is transmitted to the seat control system, the system parses the operating mode identifier to determine which seat adjustment mode the user is currently requesting. This step is crucial for the system to further interpret the data frame content and involves obtaining the target posture parameters. Based on a pre-set strategy mapping table, the system matches the operating mode identifier with the corresponding set of target posture parameters to ensure that each mode automatically adjusts the seat parameters according to the preset requirements.

[0038] It should be noted that the rest adjusting system also includes an electric shoulder adjusting device and an inclination adjusting mechanism. The shoulder target angle value is used to control the forward and backward displacement amplitude of the electric shoulder adjusting device, and the inclination target angle value is used to realize the linkage inclination adjustment of the seat cushion and the backrest through the inclination adjusting mechanism (such as a seat skeleton inclination motor).

[0039] Exemplarily, in the "driving mode", the operation mode identifier will be mapped to the slide rail displacement value 130mm, the backrest angle value 105°, the shoulder forward adjustment 5°, the inclination 0°, and the leg rest retracted state, which means that the system will perform the adjustment for the driving posture after receiving this instruction; in the "zero gravity mode", the operation mode identifier is mapped to the slide rail displacement value 230mm, the backrest angle value 125°, the shoulder forward adjustment 10°, the inclination 15°, and the leg rest extended state, which provides a more relaxed and comfortable seat posture; in the "rest mode", the system will keep the parameter configuration of the "zero gravity mode", and additionally add massage intensity, soothing music, and ventilation level and other parameters to enhance the rest experience.

[0040] Step S104, based on the real-time temperature data in the vehicle, performing dynamic compensation calculation on the target posture parameter set to generate a compensated execution instruction set; After obtaining the target posture parameter set, the system performs dynamic compensation calculation on the target posture parameters based on the data collected by the real-time temperature sensor in the vehicle. This step is very important because the ambient temperature in the vehicle can affect the comfort of the seat. For example, in a higher temperature, the seat may need to increase the ventilation function to enhance the comfort; while in a low temperature environment, the heating function needs to be started.

[0041] Specifically, when the temperature data in the vehicle exceeds the preset upper limit, the system will increase the power level of the ventilation device in the target posture parameter set to improve air circulation; when the temperature is lower than the preset lower limit, the system will adjust the heating device of the seat to keep it within a comfortable temperature range. This compensation function ensures that the seat can always provide the best comfort in different environmental conditions.

[0042] Step S105, according to the compensated execution instruction set, sending motor control signals to the seat actuator through the vehicle CAN bus; The compensated execution instruction set will be used to send motor control signals to the seat actuator through the CAN bus. The seat actuator includes a slide rail drive motor, a backrest adjusting motor, and a leg rest telescopic motor. Each motor is responsible for a specific adjustment part of the seat, for example, the slide rail drive motor adjusts the forward and backward position of the seat, the backrest adjusting motor controls the angle of the backrest, and the leg rest telescopic motor adjusts the extension state of the leg rest. Through the coordinated action of these motors, the seat can accurately adjust to the predetermined position and angle according to the instruction.

[0043] Exemplarily, in the "driving mode", the slide rail motor can push the seat forward or backward to a position of 130mm, the backrest motor can adjust the backrest to an angle of 105°, and the legrest motor can retract the legrest to the initial state. Correspondingly, in the "zero gravity mode", the slide rail motor can move the seat slide rail to 230mm, the backrest motor can adjust the backrest to an angle of 125°, and the legrest motor can expand the legrest, providing a more relaxed posture.

[0044] Step S106, real-time acquisition of feedback signal data of the seat actuator; Wherein, after receiving the motor control signal, the actuator of the seat will adjust according to the instruction. At this time, the system will acquire the feedback signal data of the actuator in real time, including the actual slide rail displacement, the actual backrest angle and the actual legrest position. These feedback signals are important basis to ensure the accuracy of seat adjustment, which can help the system to detect whether the seat has executed the instruction as expected.

[0045] It can be understood that the real-time acquisition of feedback signals enables the system to monitor the effect of seat adjustment, ensuring that each adjustment is consistent with the user's needs. This feedback mechanism is the core part of intelligent control of the seat, which can provide high-precision feedback in the dynamic adjustment process.

[0046] Step S107, calculating the deviation value between the feedback signal data and the compensated execution instruction set, and if any deviation value exceeds the preset deviation threshold, generating an actuator calibration instruction and re-sending it to the corresponding seat actuator; Wherein, the deviation between the feedback signal data and the compensated execution instruction set is the key to the accuracy of seat adjustment. The system will calculate these deviation values and compare them with the preset tolerance threshold. If any deviation value exceeds the preset deviation threshold, the system will automatically generate a calibration instruction and re-send it to the corresponding seat actuator for necessary adjustment. This mechanism ensures the accuracy of seat adjustment and avoids the reduction of comfort due to execution errors. For example, if the actual backrest angle is 104°, but the target angle after compensation is 105°, the system will adjust the backrest motor until it reaches the accurate 105° angle.

[0047] Step S108, acquiring the final execution state data of the seat actuator and packaging it into a wireless transmission format feedback to the mobile terminal.

[0048] The system encapsulates the final status data of the seat actuators (such as slide rail displacement, backrest angle, and leg rest status) into a wireless transmission format and transmits it to the mobile terminal. This step ensures that users can view the results of seat adjustments in real time and further enhances user interactivity. For example, the mobile terminal might display "Slide rail position: 130mm, Backrest angle: 105°, Leg rest status: Retracted," providing users with an intuitive understanding of the seat's current status.

[0049] In the above-mentioned embodiment, the seat posture is precisely adjusted based on wireless communication and real-time feedback mechanisms, and the seat adjustment is optimized according to the real-time temperature data in the vehicle. Through personalized and environmentally adaptive adjustments, it is ensured that the driver can obtain the best comfort experience in different scenarios. Finally, the accuracy of seat adjustment is ensured through calibration and feedback mechanisms, which comprehensively improves the intelligence, comfort and safety of car seats.

[0050] Reference Figure 2 As an implementation of step S104, the step of performing dynamic compensation calculation on the target posture parameter set based on the real-time temperature data in the vehicle includes: Step S201, determine whether the real-time temperature data is higher than the preset temperature upper limit; if so, jump to step S202; if not, jump to step S203; The system first obtains real-time temperature data from the vehicle interior. This data is typically provided by an in-vehicle temperature sensor and reflects the ambient temperature inside the vehicle. The system compares this real-time temperature data with a preset upper temperature limit to determine whether the current in-vehicle environment exceeds the comfortable temperature range.

[0051] Step S202, adding a power level parameter of the seat ventilation device to the target posture parameter set; Specifically, if the vehicle interior temperature exceeds a preset upper limit, the system adjusts the seat ventilation function to provide a better comfort experience. At this point, the system adds the seat ventilation power level to the target posture parameter set. This parameter controls the seat ventilation intensity, helping occupants better cope with high temperatures and maintain comfort.

[0052] For example, if the temperature inside the car is 28°C and the preset temperature upper limit is 25°C, the system will determine that the temperature is too high. It will add the seat ventilation function to the target posture parameter set and set the power level to "strong" to enhance air circulation and help users lower their body temperature.

[0053] Step S203, determining whether the real-time temperature data is lower than the preset temperature upper limit; if so, skipping to step S204; if not, not performing any operation; If the temperature inside the vehicle does not exceed the preset upper limit, the system will then determine whether the temperature inside the vehicle is lower than the preset lower limit, to further optimize the logic of seat adjustment. The preset lower limit is usually to avoid the discomfort caused by the low temperature inside the vehicle, especially in cold environments. By obtaining real-time temperature data and comparing it with the lower limit, the system can determine whether to start the seat heating device to increase the seat temperature.

[0054] Step S204, adding the target temperature parameter of the seat heating device in the target posture parameter set.

[0055] Specifically, when the temperature inside the vehicle is determined to be lower than the preset lower limit, the system will dynamically adjust the target temperature parameter of the seat heating device. The target temperature parameter determines the working intensity of the seat heating device, ensuring that in cold environments, the seat can provide sufficient heating effect to improve the comfort of the ride.

[0056] For example, if the temperature inside the vehicle is 16°C and the preset lower limit is 18°C, the system determines that the temperature is too low, and the target temperature parameter of the seat heating function is added in the target posture parameter set, and the target temperature is set to 30°C to ensure that the seat surface reaches a comfortable warm state.

[0057] In the above embodiment, the seat adjustment parameters are dynamically compensated based on real-time temperature data inside the vehicle, which can adjust the ventilation and heating functions of the seat in real time according to the change of the temperature inside the vehicle, thereby providing a more comfortable driving experience. When the temperature is too high, the seat ventilation device will automatically strengthen the ventilation to help the people inside the vehicle to maintain comfort; when the temperature is too low, the seat heating device will be enabled to ensure warm and comfortable. Through this intelligent adjustment mechanism, the system can effectively respond to changes in environmental temperature and automatically make dynamic adjustments to ensure that the vehicle owner can enjoy the best seat comfort experience in hot or cold environments. This application improves the intelligence and comfort of the vehicle seat, making it more environmentally adaptable and enhancing the comfort of the vehicle owner in various temperature conditions.

[0058] Reference Figure 3 As an embodiment of step S103, after the operation mode identifier in the vehicle CAN bus protocol data frame is parsed and the corresponding target posture parameter set is matched according to the preset strategy mapping table, the following steps are further included: Step S301, obtaining the leg rest target state value in the target posture parameter set; The leg rest target state value indicates whether the leg rest is in an expanded state or a stowed state. In some seat adjustment systems, the leg rest state is dynamically changed and may be adjusted according to the driving mode, comfort requirements or personal needs of the driver.

[0059] Step S302, in response to the leg rest target state value being the leg rest unfolded state, extracting user parameter database according to user identity identifier; When the leg rest target state value is "unfolded", the system extracts the corresponding personalized parameters from the user parameter database according to the user's identity identifier (such as user ID). The user identity identifier is a unique identifier that identifies different car owners or drivers. In the personalized adjustment of car seats, each user may have different needs, such as the unfolding angle of the leg rest, the inclination of the seat, etc., which are usually closely related to the user's height, weight, seat preference, etc. physiological parameters. Therefore, the system needs to obtain these personalized parameters from the database according to the user's identity identifier, to ensure that each user can obtain a customized seat adjustment experience.

[0060] Step S303, read the user height data stored in the user parameter database, and calculate the personalized leg rest unfolding angle value based on a preset formula; According to the user height data, the personalized leg rest unfolding angle is calculated using a preset formula. Height is one of the important factors that determine the unfolding angle of the leg rest, because users of different heights have different leg comfort needs when driving. The system reads the user height data stored in the database and combines a set of preset formulas to calculate the specific angle at which the leg rest should be unfolded.

[0061] Specifically, the preset formula is: target angle = base angle + (height - reference height) x compensation coefficient. For example, the base angle is 35 degrees, the reference height is 170 cm, and the compensation coefficient is 0.5 degrees per centimeter. If the user's height is 180 cm, the calculated leg rest unfolding angle is 40 degrees.

[0062] Step S304, optimizing compensation to the target posture parameter set according to the personalized leg rest unfolding angle value.

[0063] After calculating the personalized leg rest unfolding angle, further optimization compensation is performed on the target posture parameter set. The purpose of optimization compensation is to ensure that the system can make subtle adjustments to the target parameters according to the calculated personalized angle, so as to meet the user's comfort needs.

[0064] For example, when the leg rest unfolding angle is calculated to be 40 degrees, the system may also need to adjust the inclination of the seat or adjust the angle of other parts of the seat to maintain the overall comfort and functionality of the seat. Through optimization compensation, the system can ensure that the best personalized adjustment effect is achieved without affecting the overall state of the seat.

[0065] It should be noted that the unfolding angle of the leg rest may affect the posture of other seat components, so the leg rest unfolding angle needs to be considered in the overall posture optimization to avoid imbalance of the overall seat posture caused by adjusting the leg rest angle alone.

[0066] In the above embodiments, by combining vehicle CAN bus data analysis, user identity verification, personalized height parameter calculation, and precise adjustment compensation, customized seat adjustment solutions can be provided for different users. This method is particularly suitable for multi-user shared environments and has wide adaptability, enabling automatic adjustment of seat configurations according to the needs of different users, thereby improving the intelligent level of seat adjustment and user experience.

[0067] With reference to Figure 4 , as a further embodiment of the intelligent control method of the automobile seat, the control method further comprises: Step S401, acquiring real-time driver eye image data and heart rate sensor data; Wherein, the eye state of the driver is monitored in real time by the image acquisition device (such as camera) installed in the vehicle, and the heart rate of the driver is monitored by the vehicle-mounted heart rate sensor. These two data sources provide important physiological indicators for judging the fatigue of the driver. The eye image data provides information such as eyelid closure and eye movement, while the heart rate data reflects the physiological state of the driver, especially the correlation between heart rate variability (HRV) and fatigue.

[0068] It can be understood that by acquiring real-time eye image data and heart rate data of the driver, the system can continuously monitor the physiological state of the driver during the entire driving process, providing data support for fatigue detection and intervention. This real-time data acquisition system improves the monitoring accuracy of the driver's state, enabling the system to respond to the driver's fatigue in a timely manner.

[0069] Step S402, calculating the eyelid closure frequency according to the eye image data; Wherein, based on the obtained eye image data, the closure frequency of the eyelid of the driver is analyzed, that is, the speed and frequency of eyelid closure. The eye closure frequency is an important indicator of driver fatigue, because when the driver feels tired, the eyelid closure frequency usually increases, and the eye closure time also extends. When the eyelid closure frequency exceeds a certain threshold, it often means that the driver's alertness decreases and may enter a state of fatigue. By monitoring this indicator in real time, the system can capture signs of driver fatigue, especially frequent blinking or closing of the eyes, and provide an alarm signal to the system in a timely manner, providing effective data for subsequent fatigue judgment.

[0070] Step S403, calculating the heart rate variability coefficient according to the heart rate sensor data; The system calculates the heart rate variability (HRV) of the driver based on real-time heart rate sensor data. HRV is the standard deviation of heart rate changes and is used to measure the autonomic nervous system state of the heart. Lower heart rate variability is usually associated with fatigue, stress, or health problems. The system analyzes the heart rate data through an algorithm to calculate the HRV value and compare it with the baseline value to determine whether the driver is in a fatigue state. If the driver's heart rate fluctuates less over time, the HRV value will be lower, reflecting a decrease in the body's stress response, which usually means the driver is in a fatigue state.

[0071] It can be understood that heart rate variability is an important physiological indicator of fatigue. By calculating and monitoring heart rate variability in real time, the system can accurately capture changes in the driver's physical health and fatigue state. A decrease in HRV reflects the gradual deterioration of the driver's physiological function into an unhealthy state, providing an important basis for subsequent fatigue triggering mechanisms.

[0072] Step S404, when the eyelid closure frequency continues to exceed the preset frequency threshold and the heart rate variability coefficient decreases by more than the first preset percentage compared with the baseline value, a primary fatigue trigger signal is generated; The system analyzes the changes in eyelid closure frequency and heart rate variability coefficient. When the eyelid closure frequency continues to exceed the set frequency threshold and the heart rate variability coefficient decreases by more than the preset percentage compared with the baseline value, the system will determine that the driver may be in a fatigue state, and then generate a primary fatigue trigger signal, which is the initial trigger condition for the subsequent fatigue verification process.

[0073] For example, assume that the system's preset eyelid closure frequency threshold is 4 times per minute, and the system's set HRV baseline value is 50. If the eyelid closure frequency continues to exceed 4 times per minute, and the HRV value decreases by more than 10% compared with the baseline value, the system will generate a primary fatigue trigger signal, indicating that the driver may be fatigued and needs further verification.

[0074] Step S405, in response to the primary fatigue trigger signal, real-time acquisition of body pressure distribution data of the driver's seat back and seat cushion and driving posture inclination angle data; Specifically, after detecting the primary fatigue signal, the system further acquires body pressure distribution data of the seat back and seat cushion, and the driver's seat angle data, which can help determine whether the driver's sitting posture has changed in relation to fatigue.

[0075] Step S406, calculating the body pressure distribution deviation rate of the body pressure distribution mean value and the preset body pressure distribution baseline value according to the body pressure distribution data, and outputting a body pressure abnormal signal when the body pressure distribution deviation rate is greater than the second preset percentage; The body pressure distribution of the seat back and the seat cushion is analyzed, the deviation rate from the reference value is calculated, and if the deviation rate exceeds the preset percentage, the system determines that the body pressure is abnormal and generates a corresponding signal. By monitoring the change of body pressure, it is ensured that the driver's seat posture is in a healthy state to avoid fatigue caused by improper posture.

[0076] In step S407, the posture angle deviation rate of the driving posture angle from the preset posture angle reference value is calculated according to the driving posture inclination angle data, and a posture abnormal signal is output when the posture angle deviation rate is greater than a third preset percentage; The posture angle deviation rate between the driver's posture inclination angle data and the preset posture angle reference value is calculated, and if the deviation rate exceeds the preset percentage, a posture abnormal signal is output to prompt the driver to correct the posture. For example, if the driver's back is excessively forward, the posture deviation exceeds the preset range, and the system outputs a posture abnormal signal.

[0077] In step S408, when the body pressure abnormal signal and the posture abnormal signal exist at the same time, a fatigue confirmation signal is generated; When the body pressure abnormal signal and the posture abnormal signal exist at the same time, the system considers that the driver's fatigue signs are more obvious, which indicates that the driver may unconsciously change the posture due to fatigue. At this time, the system considers that the fatigue state of the driver is confirmed, and therefore generates a fatigue confirmation signal. This signal is the trigger condition for subsequent intervention measures, which aims to prompt the driver of the fatigue state to reduce the risk of traffic accidents caused by fatigue.

[0078] As another embodiment, when either the body pressure abnormal signal or the posture abnormal signal exists, and the primary fatigue trigger marker signal lasts for more than a preset threshold, a fatigue confirmation signal is generated.

[0079] Specifically, the primary fatigue trigger marker signal itself indicates that the driver may have fatigue signs, and when the body pressure or posture abnormal signal appears, it further verifies the fatigue state. In particular, when the primary fatigue trigger marker signal lasts for a period of time and does not change, the system further judges that the driver may be in a fatigue state for a long time, and this cumulative fatigue signal is even stronger. Therefore, even if one of the body pressure or posture signals does not trigger, the system will generate a fatigue confirmation signal based on the duration of the fatigue signs and the existing physiological change signals to ensure a timely response to the possible fatigue state of the driver.

[0080] In step S409, an intervention instruction including vibration control parameters and audio playback parameters is generated in response to the fatigue confirmation signal; Among them, after generating a fatigue confirmation signal, the system will respond to the signal and generate an intervention instruction containing vibration control parameters and audio playback parameters. The vibration control parameters determine the vibration intensity and pattern of the seat vibration module to remind the driver to pay attention. The audio playback parameters control the vehicle audio module to play warning sounds, prompt sounds or soothing music to further awaken the driver's attention or help them relax. For example, the system may set the vibration control parameters to medium-intensity vibration, while the audio playback parameters may be set to play a "fatigue warning" voice or play light music to relieve the driver's stress.

[0081] In this embodiment, the generation of intervention instructions effectively combines vibration and audio stimulation to provide the driver with multiple stimuli and awaken their alertness. This combination of vibration and audio enables the driver to respond quickly and take necessary safety measures, thereby reducing the potential dangers of fatigued driving.

[0082] Step S410: Sending an intervention instruction to the seat vibration module and the vehicle audio module via the vehicle CAN bus.

[0083] The generated intervention command is transmitted via the vehicle's CAN bus to the seat vibration module and the onboard audio module, which then executes the vibration and audio intervention measures. The seat vibration module controls the seat vibration intensity and pattern, while the onboard audio module plays the specified audio signal according to the command. This allows the system to take swift action and alert the driver.

[0084] For example, after fatigue is detected, the system sends a signal to the seat vibration module via the CAN bus, causing the seat to vibrate. At the same time, the audio system plays a warning sound or light music to remind the driver.

[0085] In this implementation, real-time monitoring of the driver's physiological state (eye image data and heart rate data) combined with body pressure and posture data accurately identifies driver fatigue and provides a timely response through vibration and audio intervention mechanisms. This multi-dimensional fatigue detection and intervention effectively improves driving safety and significantly reduces the risk of accidents caused by fatigued driving.

[0086] Reference Figure 5 As an implementation of step S405, the step of generating an intervention instruction including vibration frequency parameters and audio playback parameters in response to the fatigue confirmation signal includes: Step S501, in response to the fatigue confirmation signal, obtaining vehicle ignition cumulative duration data; When the system detects signs of driver fatigue (such as abnormal eyelid closure frequency, too low heart rate variability, etc.), a fatigue confirmation signal is triggered. This signal serves as the trigger condition for intervention, and the system needs to further obtain vehicle ignition cumulative duration data. This data can reflect the duration of the driver's driving, which is a key indicator for determining whether the driver has been driving for a long time and whether fatigue has occurred. Through the cumulative ignition duration data, the system can determine whether the driver's driving duration exceeds the time threshold for safe driving, thereby deciding whether to intervene in fatigue.

[0087] Step S502, determine the corresponding driving duration according to the vehicle ignition cumulative duration data, and determine the target strategy identifier based on the preset strategy index table; Among them, the strategy index table includes the vibration curve identifier and the audio curve identifier corresponding to different driving duration intervals; Specifically, after obtaining the ignition cumulative duration, the system needs to determine the current driving duration according to the data. The driving duration data will be compared with the preset strategy index table, so as to select the appropriate intervention strategy. The strategy index table contains vibration curve identifiers and audio curve identifiers corresponding to different driving duration intervals (such as 0-1 hour, 1-2 hours, 2 hours or more, etc.). This mechanism enables the system to select the most appropriate vibration and audio intervention parameters according to the driving duration.

[0088] For example, assuming the driving duration is 4 hours, the strategy index table will look up the corresponding vibration curve and audio curve identifier according to this duration. For example, for a driving duration of 4 hours, the strategy index table may return a stronger vibration curve and warning audio.

[0089] Step S503, based on the target strategy identifier, extract the corresponding vibration control parameters and audio playback parameters from the parameter database; Among them, the vibration control parameters include vibration frequency value, duration and waveform mode, and the audio playback parameters include file path and volume level; Specifically, after determining the target strategy identifier, the system extracts the corresponding vibration control parameters and audio playback parameters from the pre-stored parameter database. These parameters will determine the vibration intensity and mode of the seat vibration module, as well as the audio content and volume played by the car audio system.

[0090] For example, for a driving duration of 4 hours, the system extracts a set of vibration control parameters (such as vibration frequency of 2Hz, duration of 5 seconds, and waveform mode of sine wave) and a set of audio playback parameters (such as audio file path "warning.wav" and volume level 80%) from the parameter database.

[0091] Step S504, convert the vibration control parameters into control instruction frames of CAN bus protocol, and package the audio playback parameters into audio bus protocol data packets, and combine to obtain the intervention instruction.

[0092] Wherein, the vibration control parameters and the audio playback parameters need to be transmitted to the vehicle control system through a suitable protocol. The vibration control parameter set will be converted into a control instruction frame conforming to the CAN bus protocol, and the audio playback parameter set will be packaged into a data packet of the audio bus protocol. These two data packets will be sent to the seat vibration module and the car audio system respectively to perform the corresponding vibration and audio intervention operation.

[0093] It should be noted that through this protocol conversion and data packaging method, the system can accurately transmit the intervention instruction to each module of the vehicle, ensuring timely and accurate execution of the vibration and audio intervention signal. The standardization and protocolization of the data packet make the entire system more efficient and stable.

[0094] In the above embodiment, the real-time response fatigue confirmation signal is used to comprehensively utilize multiple data inputs such as vehicle ignition cumulative time data, driving time, strategy index table, etc. to provide timely and effective intervention measures for the driver's fatigue driving. The system can intelligently select intervention strategies according to different driving times through dual intervention means of vibration control and audio playback, accurately adjust the vibration intensity and the volume level of the audio warning, thereby improving the driver's alertness and reducing the risk of fatigue driving. Through the cooperation of CAN bus protocol and audio bus protocol, the intervention instruction can be accurately and quickly transmitted to the seat vibration module and the car audio system, realizing efficient fatigue response control.

[0095] Reference Figure 6 As a further embodiment of the intelligent control method, the control method further comprises: Step S601, real-time acquisition of vehicle control instruction sequence, real-time temperature data and feedback signal data of seat actuator; wherein the feedback signal data includes motor encoder signal and CAN bus error frame; Specifically, the control instruction sequence refers to the adjustment instruction log obtained from the data buffer of the vehicle CAN bus, which is usually in the form of a structure containing a timestamp, a function command code (cmd) and a corresponding actuator. These commands represent the target operation intention of the master control unit to the seat actuator in the control layer, have clear timing and instruction type, and are the prerequisite data for subsequent fault location.

[0096] Meanwhile, ambient temperature as a key parameter of external working conditions is sampled by temperature sensors arranged in the interior of the vehicle (e.g. the bottom of the seat, the cabin module) through analog-to-digital conversion (ADC), and the sampling frequency is usually set to 1 Hz to balance the response speed and computing resources. Temperature data plays an important reference role in the interpretation of the running state of the seat actuator, for example, whether the motor current fluctuation is a normal phenomenon at low temperature.

[0097] The feedback signal data of the seat actuator mainly includes motor encoder signals and CAN bus error frames. The motor encoder signal is the basic signal of motor displacement or speed feedback, usually represented as the cumulative value of an incremental or absolute pulse counter; the CAN bus error frame is generated by the underlying driver layer in the case of transmission failure, abnormal interference, node timeout, etc., indicating abnormal events in the system communication process. These error frames provide direct evidence of abnormal behavior at the network protocol stack level and are the key data source for distinguishing communication abnormalities from physical mechanism failures.

[0098] In step S602, the flag bit data of the CAN bus error frame is parsed, and an error type label is generated according to a predefined error type mapping rule; wherein the error type includes communication timeout, motor overload and voltage fluctuation; Specifically, in CAN bus communication, the error frame is a special frame type automatically broadcast by the bus node when a communication error is detected, which interrupts the error data stream and notifies other nodes in the network of the current communication anomaly. The core of this step is to abstract the communication failure of the underlying physical layer or data link layer into an error type label that can be understood at a higher level by parsing the error flag bits in the error frame.

[0099] In the embodiments of the present application, the low three bits of the error frame correspond to three specific fault types: bit 0 represents communication timeout, which is logically related to ACK (Acknowledge) response failure, which can be determined by whether the ACK missing counter in the controller exceeds the set threshold (e.g. 3 times); bit 1 represents motor overload, which is determined by whether the current peak value detected by the encoder or current sensor exceeds 120% of the rated current, which can be obtained in real time by a Hall current detector or a MOS drive chip; bit 2 represents voltage fluctuation, mainly focusing on whether the voltage has a mutation of more than ±0.5V in a short time (e.g. 10ms), reflecting the transient stability problem of the power supply system.

[0100] It can be understood that through the judgment mechanism of combining bits, the system can identify complex fault types, for example, communication timeout and motor overload occurring at the same time will be mapped to flag bit 0x03, and the system will generate multiple error labels accordingly. The entire mapping process is based on an error type rule dictionary, which is usually implemented as a lookup table logic in actual deployment, ensuring efficient and reliable extraction of fault semantics from underlying abnormal states.

[0101] Step S603, encapsulate the error type label, the corresponding time-stamped vehicle control instruction sequence, real-time temperature data, and feedback signal data into an enhanced log structure; After obtaining and parsing all the key fields, the system enters the data structure reorganization phase. All information is unified and aligned on the time axis, and encapsulated into an enhanced log structure. This structure not only contains basic control behavior information and abnormal type, but also embeds the current temperature working condition, motor feedback value, and original error frame flag code, forming a multi-dimensional information composite record. The log structure design generally adopts a structured data format, such as C language structure (struct) or JSON object, which facilitates subsequent machine storage, query, and visualization.

[0102] Step S604, according to the severity level of the error type label, select independent storage sectors or circular storage areas, and write the enhanced log structure into the non-volatile memory; Among them, based on the importance of error type, the log information is implemented with differentiated storage strategy, so as to realize the maximization of data value under limited storage resources. Specifically, the system sets a severity level threshold for error type: if the log contains "communication timeout" or "motor overload" which may cause control system paralysis or safety risk, high priority fault, the log will be written into the reserved independent emergency storage sector; while only involving "voltage fluctuation" which is an occasional disturbance event, it is written into the circular buffer (circular buffer), which is limited in space and runs in the form of covering old data.

[0103] In addition, the non-volatile memory is usually NOR / NAND Flash or EEPROM, which has the feature of power failure saving, and the write operation needs to control the address pointer, page boundary alignment, and select the page / block erase strategy according to the Flash structure.

[0104] Step S605, read the status register of the non-volatile memory to verify the integrity of the log data writing, and if the verification fails, trigger the data rewriting process.

[0105] Specifically, after writing in the flash memory, the system checks whether the write command is completed by reading the status register, and to prevent data damage caused by voltage fluctuations, interruptions, etc. during storage, the system adds a CRC (Cyclic Redundancy Check) redundancy check code in the log structure. The CRC of the log body is calculated before writing and stored at the tail of the structure, and after writing, the CRC is recalculated through a read-back operation and compared. If the CRC is found to be inconsistent, it means that the writing is not complete or the data is damaged, and the system will immediately perform a retry-write process and maintain a failure counter. If the consecutive failures exceed the threshold, a bad block marking mechanism will be executed, the physical block will be marked as unusable, and address remapping will be completed in the spare block.

[0106] In the above embodiment, based on the CAN communication protocol, the electrical signal analysis, environmental working condition perception and actuator feedback are integrated, the whole process automation and structuring from fault behavior perception to storage management are realized, and the operation monitorability, traceability and fault response efficiency of the automobile seat control system are greatly improved. The application is suitable for intelligent vehicles, autonomous driving systems and other scenes with high requirements for safety and data integrity.

[0107] The application also discloses an automobile seat intelligent control system An automobile seat intelligent control system, the intelligent control system comprising: A data receiving module configured to receive a control instruction data packet from a mobile terminal, the control instruction data packet comprising an operation mode identifier and a user identity; A data conversion module configured to convert the control instruction data packet into a vehicle CAN bus protocol data frame through a wireless communication module and add a data check code in the conversion process; A parameter matching module configured to parse the operation mode identifier in the vehicle CAN bus protocol data frame, and match a corresponding target posture parameter set according to a preset strategy mapping table, the target posture parameter set comprising a target displacement value of a slide rail, a target angle value of a backrest and a target state value of a leg rest; A dynamic compensation module configured to perform dynamic compensation calculation on the target posture parameter set based on real-time temperature data in the vehicle, and generate a compensated execution instruction set; A motor control module configured to send a motor control signal to a seat actuator through the vehicle CAN bus according to the compensated execution instruction set; A feedback acquisition module configured to acquire feedback signal data of the seat actuator in real time; The bias calibration module is configured to calculate bias values of the feedback signal data and the compensated execution instruction set, and generate mechanism calibration instructions and resend the mechanism calibration instructions to corresponding seat execution mechanisms if any bias value exceeds a preset bias threshold. The data packaging module is configured to obtain final execution state data of the seat execution mechanisms and package the final execution state data into a wireless transmission format for feedback to the mobile terminal.

[0108] The automobile seat intelligent control system of the embodiments of the present application can implement any of the automobile seat intelligent control methods described above, and the specific working processes of the various modules in the automobile seat intelligent control system can refer to the corresponding processes in the method embodiments described above.

[0109] In several embodiments provided in the present application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative; for example, the division of a certain module is only a logical functional division, and actual implementation can have another division manner, for example, a plurality of modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0110] The embodiments of the present application also disclose a computer device.

[0111] The computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the automobile seat intelligent control method as described above when executing the computer program.

[0112] The embodiments of the present application also disclose a computer readable storage medium.

[0113] The computer readable storage medium stores a computer program capable of being loaded and executed by a processor to implement any of the automobile seat intelligent control methods as described above.

[0114] The computer readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device or apparatus; the program code contained in the computer readable medium can be transmitted by any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any appropriate combination of the above.

[0115] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can refer to the related description of other embodiments.

[0116] The above are only preferred embodiments of the present application, not intended to limit the protection scope of the present application, any one feature disclosed in the specification (including the abstract and the drawings) can be replaced by other equivalent or similar features, unless specifically stated otherwise. That is, unless specifically stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A method for intelligent control of a car seat, characterized in that: The intelligent control method comprises: receiving a control instruction data packet from a mobile terminal; the control instruction data packet includes an operation mode identifier and a user identity identifier; Converting the control instruction data packet into a vehicle CAN bus protocol data frame through a wireless communication module, and adding a data check code during the conversion process; parsing the operation mode identifier in the vehicle CAN bus protocol data frame and matching the corresponding target posture parameter set according to a preset strategy mapping table; the target posture parameter set includes a slide rail target displacement value, a backrest target angle value, a shoulder target angle value, a tilt target angle value, and a leg support target state value; Based on real-time temperature data in the vehicle, dynamic compensation calculation is performed on the target posture parameter set to generate a post-compensation execution instruction set; sending a motor control signal to a seat actuator via a vehicle CAN bus according to the post-compensation execution instruction set; acquiring feedback signal data of the seat actuator in real time; Calculating the deviation between the feedback signal data and the compensated execution instruction set, and if any deviation exceeds a preset deviation threshold, generating a mechanism calibration instruction and resending it to the corresponding seat actuator; The final execution status data of the seat actuator is obtained, packaged into a wireless transmission format, and fed back to the mobile terminal.

2. The intelligent control method for a car seat according to claim 1, characterized in that: The step of performing dynamic compensation calculation on the target posture parameter set based on real-time temperature data in the vehicle includes: Determining whether the real-time temperature data is higher than a preset temperature upper limit; If yes, then adding a power level parameter of the seat ventilation device to the target posture parameter set; If not, determining whether the real-time temperature data is lower than a preset temperature upper limit; If it is lower, the target temperature parameter of the seat heating device is added to the target posture parameter set.

3. The intelligent control method for a car seat according to claim 1, characterized in that: After parsing the operation mode identifier in the vehicle CAN bus protocol data frame and matching the corresponding target posture parameter set according to the preset strategy mapping table, the following steps are further included: Obtaining a leg support target state value in the target posture parameter set; In response to the leg rest target state value being the leg rest expanded state, extracting a user parameter database according to the user identity identifier; Reading the user's height data stored in the user parameter database, and calculating the personalized leg support deployment angle value based on a preset formula; The target posture parameter set is optimized and compensated according to the personalized leg rest expansion angle value.

4. The intelligent control method for a car seat according to claim 1, characterized in that: The control method further includes: Acquire driver's eye image data and heart rate sensor data in real time; calculating an eyelid closure frequency based on the eye image data; Calculating the heart rate variability coefficient based on the heart rate sensor data; When the eyelid closure frequency continuously exceeds a preset frequency threshold and the heart rate variability coefficient decreases by more than a first preset percentage compared to the baseline value, a primary fatigue trigger mark signal is generated; In response to the primary fatigue trigger mark signal, real-time acquisition of body pressure distribution data of the driver's seat back and seat cushion and driving posture inclination data; calculating a body pressure distribution deviation rate between a body pressure distribution mean and a preset body pressure distribution reference value based on the body pressure distribution data, and outputting a body pressure abnormality signal when the body pressure distribution deviation rate is greater than a second preset percentage; Calculating a posture angle deviation rate between the driving posture angle and a preset posture angle reference value based on the driving posture inclination angle data, and outputting a posture abnormality signal when the posture angle deviation rate is greater than a third preset percentage; When the abnormal body pressure signal and the abnormal posture signal exist at the same time, a fatigue confirmation signal is generated; generating an intervention instruction including vibration control parameters and audio playback parameters in response to the fatigue confirmation signal; The intervention instruction is sent to the seat vibration module and the vehicle audio module via the vehicle CAN bus.

5. The intelligent control method for a car seat according to claim 4, characterized in that: The control method further includes: generating a fatigue confirmation signal when either the abnormal body pressure signal or the abnormal posture signal exists and the duration of the primary fatigue trigger mark signal exceeds a preset threshold.

6. The intelligent control method for a car seat according to any one of claims 4 or 5, characterized in that: The step of generating an intervention instruction including vibration frequency parameters and audio playback parameters in response to the fatigue confirmation signal includes: In response to the fatigue confirmation signal, acquiring vehicle ignition cumulative duration data; Determining the corresponding driving duration according to the vehicle ignition cumulative duration data, and determining a target strategy identifier based on a preset strategy index table; Based on the target strategy identifier, extracting corresponding vibration control parameters and audio playback parameters from a parameter database; The vibration control parameters are converted into control instruction frames of the CAN bus protocol, and the audio playback parameters are encapsulated into audio bus protocol data packets, and the intervention instructions are obtained by combining them.

7. The intelligent control method for a car seat according to claim 1, characterized in that: The control method further includes: Real-time acquisition of vehicle control command sequences, real-time temperature data, and feedback signal data from seat actuators; wherein the feedback signal data includes motor encoder signals and CAN bus error frames; Parsing the flag bit data of the CAN bus error frame and generating an error type tag according to a predefined error type mapping rule; wherein the error type includes communication timeout, motor overload and voltage fluctuation; The error type mark is associated with the vehicle control instruction sequence of the corresponding timestamp, the real-time temperature data and the feedback signal data and encapsulated into an enhanced log structure; Selecting an independent storage sector or a circular storage area according to the severity level of the error type mark, and writing the enhanced log structure into a non-volatile memory; The status register of the non-volatile memory is read to verify the integrity of the log data written, and if the verification fails, the data rewriting process is triggered.

8. An intelligent control system for automobile seats, characterized in that: The intelligent control system includes: A data receiving module, configured to receive a control instruction data packet from a mobile terminal; the control instruction data packet includes an operation mode identifier and a user identity identifier; A data conversion module, configured to convert the control instruction data packet into a vehicle CAN bus protocol data frame via the wireless communication module, and to add a data check code during the conversion process; a parameter matching module, configured to parse the operation mode identifier in the vehicle CAN bus protocol data frame and match the corresponding target posture parameter set according to a preset strategy mapping table; the target posture parameter set includes a slide rail target displacement value, a backrest target angle value, a shoulder target angle value, a tilt target angle value, and a leg support target state value; A dynamic compensation module, configured to perform dynamic compensation calculations on the target attitude parameter set based on real-time temperature data within the vehicle, and generate a post-compensation execution instruction set; a motor control module, configured to send a motor control signal to a seat actuator via a vehicle CAN bus according to the compensated execution instruction set; A feedback acquisition module, used for acquiring feedback signal data of the seat actuator in real time; a deviation calibration module, configured to calculate a deviation between the feedback signal data and the compensated execution instruction set, and generate a mechanism calibration instruction and resend it to the corresponding seat actuator if any deviation value exceeds a preset deviation threshold; The data encapsulation module is used to obtain the final execution status data of the seat actuator, encapsulate it into a wireless transmission format, and feed it back to the mobile terminal.

9. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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