Vehicle steering wheel temperature control method, vehicle and computer readable storage medium

Abstract

The embodiment of the application provides a vehicle steering wheel temperature control method, a vehicle and a computer readable storage medium, the method comprises the following steps: acquiring multi-source perception state data of the vehicle, wherein the multi-source perception state data comprises hand physiological state data associated with the steering wheel, vehicle running state data and vehicle body environment data; determining a steering wheel holding area of a target user and a vehicle driving scene based on the multi-source perception state data; determining a target temperature corresponding to the steering wheel holding area according to a preset comfort temperature model corresponding to the vehicle driving scene and the target user, wherein the preset comfort temperature model is used to represent the mapping relationship between the skin temperature of the user's hand and the thermal comfort; and performing temperature control on the steering wheel holding area according to the target temperature. The application solves the technical problems of the related vehicle steering wheel temperature control method, such as extensive and passive control, lack of personalization and scene adaptability.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more specifically, to a method for controlling the temperature of a vehicle steering wheel, a vehicle, and a computer-readable storage medium. Background Technology

[0002] Heated steering wheels are a common feature for improving driving comfort in winter. Most solutions use resistance wires or carbon fiber for overall heating, or divide the wheel rim into several fixed areas for independent control. However, these technologies still have some shortcomings: First, the control mode is crude and passive, unable to dynamically adjust according to the driver's physiological state, often resulting in delayed heating or overheating and sweating. Furthermore, these technologies lack personalization and scenario adaptability, failing to recognize specific scenarios such as aggressive driving or individual differences in body temperature.

[0003] There is currently no good solution to the above problems. Summary of the Invention

[0004] This application provides a vehicle steering wheel temperature control method, a vehicle, and a computer-readable storage medium to at least solve the technical problems of the related steering wheel temperature control system, such as its crude and passive control, lack of personalization, and lack of scenario adaptability.

[0005] According to one aspect of the embodiments of this application, a method for controlling the temperature of a vehicle steering wheel is provided, comprising: acquiring multi-source sensing state data of the vehicle, wherein the multi-source sensing state data includes: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle body environment data; determining the steering wheel grip area of ​​a target user and the vehicle driving scenario based on the multi-source sensing state data; determining a target temperature corresponding to the steering wheel grip area according to the vehicle driving scenario and a preset comfort temperature model corresponding to the target user, wherein the preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort; and controlling the temperature of the steering wheel grip area according to the target temperature.

[0006] Optionally, the hand physiological state data includes pressure distribution data, and the vehicle operating state data includes steering wheel angle data. Determining the target user's steering wheel grip area based on multi-source sensing state data includes: performing cluster analysis based on pressure distribution data to obtain candidate grip areas, wherein the pressure distribution value of the candidate grip areas is greater than a preset pressure threshold; and determining the steering wheel grip area based on the steering wheel angle data and the candidate grip areas.

[0007] Optionally, determining the steering wheel grip area based on steering wheel angle data and candidate grip areas includes: in response to determining that the vehicle is in a straight-line cruising state based on steering wheel angle data, determining the candidate grip area within a preset standard grip range as the steering wheel grip area; in response to determining that the vehicle is in a turning state based on steering wheel angle data, determining the steering wheel grip area based on the turning angle size, turning direction, and candidate grip areas of the steering wheel angle data.

[0008] Optionally, determining the vehicle driving scenario based on multi-source perception state data includes: determining an environmental judgment result based on vehicle environment data, wherein the environmental judgment result is used to characterize the vehicle's external thermal load state; determining a driving behavior judgment result based on vehicle operating state data, wherein the driving behavior judgment result is used to characterize the vehicle's dynamic driving conditions; and determining the vehicle driving scenario based on the environmental judgment result and the driving behavior judgment result.

[0009] Optionally, the hand physiological state data also includes: average hand skin temperature and hand humidity. Determining the target temperature corresponding to the steering wheel grip area based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user includes: determining the baseline comfort temperature range corresponding to the target user's hands based on the preset comfort temperature model; determining comfort deviation data using the average hand skin temperature, hand humidity, and baseline comfort temperature range; obtaining temperature control strategy parameters from a preset strategy library based on the vehicle driving scenario; and determining the target temperature corresponding to the steering wheel grip area based on the comfort deviation data using the temperature control strategy parameters.

[0010] Optionally, temperature control of the steering wheel grip area based on the target temperature includes: generating a zone control command based on the target temperature, wherein the zone control command is used to determine the current direction and current amplitude of the thermoelectric semiconductor module in the steering wheel grip area; and performing temperature control of the steering wheel grip area based on the zone control command.

[0011] Optionally, the vehicle steering wheel temperature control method further includes: re-identifying the current steering wheel grip area in response to a change in the position of the steering wheel grip area, and updating the zone control command based on the current steering wheel grip area.

[0012] Optionally, the vehicle steering wheel temperature control method further includes: acquiring temperature preference data of the target user, wherein the temperature preference data is used to represent the target user's preferred hand temperature range under different ambient temperatures, and the target user's preference for temperature control response speed; and constructing a preset comfort temperature model based on the temperature preference data.

[0013] According to another aspect of the embodiments of this application, a vehicle steering wheel temperature control device is also provided, comprising: a first acquisition module, configured to acquire multi-source sensing state data of the vehicle, wherein the multi-source sensing state data includes: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle body environment data; a first determination module, configured to determine the steering wheel grip area of ​​a target user and the vehicle driving scenario based on the multi-source sensing state data; a second determination module, configured to determine a target temperature corresponding to the steering wheel grip area according to the vehicle driving scenario and a preset comfort temperature model corresponding to the target user, wherein the preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort; and a control module, configured to perform temperature control on the steering wheel grip area according to the target temperature.

[0014] Optionally, the hand physiological state data includes pressure distribution data, and the vehicle operating state data includes steering wheel angle data. The first determining module is also used to: perform cluster analysis based on the pressure distribution data to obtain candidate gripping areas, wherein the pressure distribution value of the candidate gripping areas is greater than a preset pressure threshold; and determine the steering wheel gripping area based on the steering wheel angle data and the candidate gripping areas.

[0015] Optionally, the first determining module is further configured to: in response to determining that the vehicle is in a straight-line cruising state based on the steering wheel angle data, determine the candidate grip area within the preset standard grip range as the steering wheel grip area; in response to determining that the vehicle is in a turning state based on the steering wheel angle data, determine the steering wheel grip area according to the turning angle size, turning direction and candidate grip area of ​​the steering wheel angle data.

[0016] Optionally, the first determining module is further configured to: determine an environmental determination result based on vehicle environmental data, wherein the environmental determination result is used to characterize the vehicle's external thermal load state; determine a driving behavior determination result based on vehicle operating status data, wherein the driving behavior determination result is used to characterize the vehicle's dynamic driving conditions; and determine the vehicle driving scenario based on the environmental determination result and the driving behavior determination result.

[0017] Optionally, the hand physiological state data also includes: average hand skin temperature and hand humidity. The second determining module is further used to: determine the baseline comfort temperature range corresponding to the target user's hand based on a preset comfort temperature model; determine comfort deviation data using the average hand skin temperature, hand humidity, and baseline comfort temperature range; obtain temperature control strategy parameters from a preset strategy library based on the vehicle driving scenario; and determine the target temperature corresponding to the steering wheel grip area based on the comfort deviation data using the temperature control strategy parameters.

[0018] Optionally, the control module is further configured to: generate zone control commands based on the target temperature, wherein the zone control commands are used to determine the current direction and current amplitude of the thermoelectric semiconductor module within the steering wheel grip area; and perform temperature control on the steering wheel grip area according to the zone control commands.

[0019] Optionally, the vehicle steering wheel temperature control device further includes: an update module, used to re-identify the current steering wheel grip area in response to a change in the position of the steering wheel grip area, and to update the zone control command based on the current steering wheel grip area.

[0020] Optionally, the vehicle steering wheel temperature control device further includes: a second acquisition module for acquiring temperature preference data of the target user, wherein the temperature preference data represents the target user's preferred hand temperature range under different ambient temperatures, and the target user's preference for temperature control response speed; and a construction module for constructing a preset comfort temperature model based on the temperature preference data.

[0021] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0022] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0023] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0024] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0025] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0026] In this embodiment, a dynamic zoned temperature control method is adopted. This method acquires multi-source sensing state data of the vehicle, including: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data. Based on this multi-source sensing state data, the steering wheel grip area of ​​the target user and the vehicle driving scenario are determined. Then, according to the vehicle driving scenario and the target user's corresponding preset comfort temperature model, the target temperature corresponding to the steering wheel grip area is determined. The preset comfort temperature model represents the mapping relationship between the user's hand skin temperature and thermal comfort. Finally, the temperature of the steering wheel grip area is controlled according to the target temperature, achieving the goal of dynamically controlling the steering wheel temperature. This realizes the technical effect of precise, personalized, and scenario-based intelligent temperature control, thereby solving the technical problems of crude and passive control, lack of personalization, and lack of scenario adaptability in related steering wheel temperature control systems. Attached Figure Description

[0027] 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:

[0028] Figure 1 This is a flowchart of an optional vehicle steering wheel temperature control method according to an embodiment of this application;

[0029] Figure 2 This is a schematic diagram of an optional vehicle steering wheel temperature control system according to an embodiment of this application;

[0030] Figure 3 This is a schematic diagram of an optional vehicle steering wheel temperature control method according to an embodiment of this application;

[0031] Figure 4 This is a schematic diagram of another optional vehicle steering wheel temperature control method according to an embodiment of this application;

[0032] Figure 5 This is an embodiment of an optional vehicle steering wheel temperature control device according to an embodiment of this application. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] With the continuous improvement of automotive intelligence and comfort, steering wheel heating has become a common feature in mid-to-high-end models, aiming to improve the driving experience in winter and enhance hand comfort.

[0036] Currently, the relevant steering wheel temperature control technology solutions are mainly divided into two categories: the first category is the overall heating solution, which usually embeds resistance wires or carbon fiber heating wires inside the steering wheel rim, and heats the entire steering wheel through constant current. It also uses temperature sensor feedback to perform simple on / off or pulse width modulation control to keep the overall temperature of the steering wheel at a fixed value set by the user.

[0037] The second type is the zone heating scheme. Some technologies physically divide the steering wheel rim into 2 to 4 fixed zones, such as the 3 o'clock, 9 o'clock and 6 o'clock directions, allowing users to independently control the on / off status of each zone. However, the zone positions of this type of scheme are fixed and the control logic is relatively simple. For example, it can only select front heating or rear heating, lacking dynamic adaptability.

[0038] In addition, some related technologies include gesture-interactive steering wheels based on electronic skin technology or biosensors. These steering wheels utilize a biomimetic sensor array consisting of temperature, humidity, and pressure biosensors on the outer rim to recognize driver gestures and control vehicle functions or switch driving modes. Other climate control systems adjust the temperature by monitoring hand temperature and humidity and detect when the hand is removed to issue an alarm. Alternatively, they may combine facial recognition with the driver's identification and read preset comfort temperature data, using hand temperature detection for closed-loop temperature control.

[0039] While the aforementioned technologies offer some degree of temperature control or interactive functionality, they still suffer from the following significant drawbacks: First, the control mode is crude and passive. Most temperature control systems operate based on "on / off" logic or fixed temperature settings, failing to dynamically adjust according to the driver's real-time physiological state, such as cold, sweaty, or dry hands. Users often report slow heating or overheating leading to sweating, requiring frequent manual adjustments and failing to achieve a transition from "setting the temperature" to "maintaining a comfortable feeling."

[0040] Secondly, the lack of personalization and scenario adaptability means that a single temperature setting cannot meet the varying sensitivities of different individuals to temperature changes. Furthermore, the systems struggle to recognize complex driving scenarios, such as the need for cooling to keep hands dry during aggressive driving or the need for rapid, localized, strong heating during cold starts in winter. These technologies often treat environmental factors and driving behavior in isolation, or rely on a single dimension for control, resulting in a disconnect between temperature control strategies and actual needs.

[0041] Secondly, the zoning is fixed and cannot dynamically adapt to real-time grip posture. The zoning of the relevant zoning heating solutions is physically fixed, but the driver's actual grip position, grip strength, and contact area are dynamically changing. Fixed heating areas may result in insufficient heating of the actual grip area, while the non-grip area wastes energy heating. The relevant technology lacks dynamic grip area recognition technology based on real-time pressure distribution, and cannot achieve precise temperature control.

[0042] Finally, the functions are limited, lacking proactive health care and all-season adaptability. Most related technical solutions only have heating functions, lacking active cooling capabilities in summer, and often use hand physiological data only for simple gesture recognition or hand removal detection, failing to fully utilize continuous monitoring data of hand skin temperature, humidity, and pressure to reflect the driver's tension, fatigue, and other states. They also lack the ability to extend health care by combining the temperature control system with driver status monitoring.

[0043] In summary, the relevant technologies still suffer from problems such as extensive and passive control, lack of personalization, and inability to adapt to different scenarios.

[0044] According to an embodiment of this application, a method embodiment for controlling the temperature of a vehicle steering wheel is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0045] This embodiment provides a method for controlling the temperature of a vehicle steering wheel. Figure 1 This is a flowchart of an optional vehicle steering wheel temperature control method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0046] Step S11: Obtain multi-source perception state data of the vehicle, including: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data.

[0047] Step S12: Determine the target user's steering wheel grip area and vehicle driving scenario based on multi-source perception state data;

[0048] Step S13: Determine the target temperature corresponding to the steering wheel grip area based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user. The preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort.

[0049] Step S14: Control the temperature of the steering wheel grip area according to the target temperature.

[0050] The aforementioned multi-source perception state data represents a comprehensive set of information collected through sensors and system interfaces across different dimensions. Specifically, it includes hand physiological state data associated with the steering wheel, vehicle operating status data, and vehicle environment data. This data set provides comprehensive foundational information support for subsequent intelligent decision-making.

[0051] The aforementioned steering wheel-related hand physiological state data refers to data reflecting the driver's hand physiological characteristics, collected in real time by a flexible sensor array inside the multi-dimensional sensing steering wheel rim. Specifically, this includes data on hand skin temperature, hand humidity, and grip pressure distribution. This data directly reflects the driver's immediate physiological sensations and contact with the steering wheel.

[0052] The aforementioned vehicle operating status data represents a comprehensive set of information collected in real time through the Controller Area Network (CAN) bus and onboard sensors, reflecting the vehicle's current operating conditions, driving mode, and driver's operational behavior. This data specifically includes, but is not limited to, ambient temperature, sunlight intensity, driving mode, time information, vehicle startup status, and driver's operational command signals. For example, driving modes may include Sport, Comfort, and Eco modes; time information may include early morning or late night; and vehicle startup status may include cold start, warm-up operation, and restarting after engine shutdown. This data provides crucial external environmental and behavioral information for determining the vehicle's driving scenario, enabling the temperature control system to adjust its temperature control strategy according to different operating states.

[0053] The aforementioned vehicle environmental data refers to data collected by onboard environmental sensors reflecting the microclimate environment outside the vehicle and inside the cabin, mainly including ambient temperature and sunlight intensity. This data is used to assist in judging driving scenarios, such as determining whether it is necessary to cope with direct sunlight or extreme temperatures.

[0054] The aforementioned steering wheel grip area represents the region where the driver actually makes effective contact with the steering wheel rim surface, as identified by the pressure sensor array. This area is not a physically fixed partition, but a dynamic region generated based on real-time pressure distribution clustering analysis, reflecting the driver's current actual grip posture and contact position.

[0055] The aforementioned vehicle driving scenarios represent the specific driving situation determined by the intelligent decision-making and control unit after comprehensively considering hand physiological state, vehicle operating status, and vehicle environment data. Examples include cold start scenarios on a winter morning, scenarios after prolonged exposure to direct sunlight in summer, aggressive driving scenarios, and high-speed cruising scenarios. Different scenarios correspond to different temperature control strategies.

[0056] The aforementioned preset comfort temperature model represents an algorithmic model stored in the intelligent decision and control unit, used to establish a mapping relationship between the user's hand skin temperature and subjective thermal comfort. This model is generated based on user preferences and defines a hand skin temperature range that makes a specific user feel comfortable, along with the corresponding target heat flux density, thus achieving a shift from setting a temperature to maintaining a comfortable physical sensation.

[0057] The target temperature mentioned above represents the ideal temperature value calculated based on the vehicle driving scenario and a preset comfort temperature model for the currently identified steering wheel grip area. This temperature aims to bring the skin temperature of the hands towards and maintain it within the personalized optimal comfort range. This temperature serves as the control reference for driving the thermoelectric semiconductor temperature controller.

[0058] The aforementioned temperature control refers to the process by which the intelligent decision-making and control unit independently drives the modules in the corresponding thermoelectric semiconductor temperature control actuator array to work according to the target temperature, thereby achieving heating or cooling by switching the current direction and adjusting the power density to make the actual temperature of the steering wheel grip area approach the target temperature.

[0059] For example, multi-source sensing state data can also include eye-tracking data to help determine the focus of the gaze, such as the dashboard and the road surface, thereby indirectly predicting hand movements. For instance, when the driver's gaze shifts from the road surface to the dashboard or central control screen, the system can predict that the driver may be about to release the steering wheel or change their grip, thereby adjusting the temperature control strategy in advance or preparing to enter a non-grip state monitoring, achieving more proactive intelligent control.

[0060] For example, when controlling the temperature of the steering wheel grip area, multi-source sensing state data of the vehicle is first acquired. In this embodiment, a flexible sensor composite layer within the multi-dimensional sensing steering wheel rim collects physiological signals from the hand, while simultaneously acquiring vehicle operation and environmental signals via the vehicle's CAN bus and onboard environmental sensors. Furthermore, the temperature, humidity, and pressure of the hand contact area are monitored in real time, and ambient temperature, sunlight intensity, driving mode, and vehicle status information are read. This data is then aggregated into the intelligent decision-making and control unit to form multi-source sensing state data for decision-making.

[0061] Secondly, the steering wheel grip area and vehicle driving scenario of the target user are determined based on multi-source sensing state data. This embodiment first performs threshold filtering and cluster analysis on the collected pressure data to identify the primary grip area and secondary contact areas, generating a dynamic grip area heat map. For example, the primary grip area can be the high-pressure area at the 3 o'clock and 9 o'clock positions. Simultaneously, combining information such as ambient temperature, driving mode, and time, a scenario judgment engine is used to analyze the specific driving scenario, such as cold start or aggressive driving, thereby clarifying the current temperature control target and strategy background.

[0062] Then, based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user, the target temperature for the steering wheel grip area is determined. In this embodiment, the average hand skin temperature within the identified dynamic grip area is compared with the personal comfort temperature range in the preset comfort temperature model to calculate the temperature deviation. Combining the current vehicle driving scenario and hand humidity and pressure data, a specific target temperature or target heat flux value is calculated for each thermoelectric module within the grip area to compensate for environmental heat dissipation or quickly adjust hand temperature.

[0063] Finally, the temperature of the steering wheel grip area is controlled according to the target temperature. In this embodiment, based on the calculated target temperature, control commands are output to the intelligent decision and control unit. The control unit independently drives the corresponding thermoelectric semiconductor temperature control actuator module, which determines the heating or cooling mode by switching the direction of the DC current and adjusts the current magnitude to control the power density. The modules in the non-grip area remain off or in a low-power state, thereby achieving precise and dynamic temperature adjustment only for the actual grip area.

[0064] Based on the above steps S11 to S14, this embodiment of the application adopts a dynamic zoned temperature control method. By acquiring multi-source sensing state data of the vehicle, including: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data, the steering wheel grip area and vehicle driving scenario of the target user are determined based on the multi-source sensing state data. Then, the target temperature corresponding to the steering wheel grip area is determined according to the vehicle driving scenario and the preset comfort temperature model corresponding to the target user. The preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort. Finally, the temperature of the steering wheel grip area is controlled according to the target temperature, thereby achieving the purpose of dynamically controlling the steering wheel temperature. This achieves the technical effect of precise, personalized, and scenario-based intelligent temperature control, and solves the technical problems of crude and passive control, lack of personalization, and lack of scenario adaptability in related steering wheel temperature control systems.

[0065] Optionally, the hand physiological state data includes pressure distribution data, and the vehicle operating state data includes steering wheel angle data. Determining the target user's steering wheel grip area based on multi-source sensing state data includes: performing cluster analysis based on pressure distribution data to obtain candidate grip areas, wherein the pressure distribution value of the candidate grip areas is greater than a preset pressure threshold; and determining the steering wheel grip area based on the steering wheel angle data and the candidate grip areas.

[0066] The pressure distribution data described above represents gridded data collected by a flexible pressure sensor array integrated into the surface of the steering wheel rim, reflecting the magnitude of force at different contact points of the hand. This data can present the force distribution pattern when the hand grips the steering wheel, including the pressure center, contact area, and pressure gradient, and is the core basis for identifying the actual grip position.

[0067] The steering wheel angle data mentioned above represents data collected by the steering wheel angle sensor, reflecting the current rotation angle and rotation trend of the steering wheel. This data is used to determine whether the driver is performing a steering operation, thereby helping to infer changes in the driver's grip posture, such as a cross grip posture.

[0068] The clustering analysis described above represents a data processing algorithm for spatially grouping pressure distribution data acquired from discrete sensor nodes. By setting distance metrics and density thresholds, adjacent sensor nodes with high pressure values ​​are grouped into the same group, thereby separating effective grip signals from complex background noise. For example, the clustering analysis in this application can employ one of the following algorithms: K-Means clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), or Gaussian Mixture Model (GMM).

[0069] The aforementioned candidate gripping areas represent a set of potential gripping areas whose pressure values ​​exceed a preset threshold, obtained through preliminary screening and cluster analysis based on pressure distribution data. This area is not yet fully determined and needs to be refined by incorporating other vehicle status data.

[0070] The aforementioned preset pressure threshold represents a pre-defined pressure value limit used to distinguish between effective grip contact and ineffective contact, such as clothing friction or slight touch. When the pressure distribution value in a certain area exceeds this threshold, that area is identified as a potential grip area. The preset pressure threshold can be adaptively calibrated based on the sensitivity of the flexible pressure sensor actually used and the vehicle's driving vibration environment. In an optional embodiment, the preset pressure threshold can be set to 10% of the sensor's full scale.

[0071] For example, when determining the steering wheel grip area of ​​a target user based on multi-source sensing state data, cluster analysis is performed based on pressure distribution data to obtain candidate grip areas. In this embodiment, pressure distribution data from a flexible pressure sensor array is first received, and the data is spatially grouped using a clustering algorithm. The system identifies continuous areas where pressure values ​​are clustered and exceed a preset pressure threshold, marking these areas as candidate grip areas. This process eliminates invalid contact points with pressure values ​​below the threshold, initially screening out locations where hand gripping is likely to occur.

[0072] The steering wheel grip area is determined based on steering wheel angle data and candidate grip areas. In this embodiment, the current steering wheel angle data is read to determine whether the vehicle is turning. If a significant change in steering wheel angle occurs, the system combines the position information of the candidate grip area with the turning trend to make a logical judgment. For example, if a left turn is detected and the candidate grip area is mainly located on the right side, the system may determine that the driver has adopted a cross-grip posture, thereby adjusting the identification range or key monitoring area of ​​the candidate grip area, and finally generating and outputting the steering wheel grip area for the target user.

[0073] Based on the above optional embodiments, this application embodiment obtains candidate gripping areas through cluster analysis based on pressure distribution data, and determines the steering wheel gripping area based on steering wheel angle data and candidate gripping areas. This achieves accurate identification and real-time tracking of the driver's dynamic gripping position, ensuring that the temperature control energy only acts on the actual gripping area, avoiding energy waste in non-grip areas. At the same time, it can adaptively adjust the gripping area identification results in complex driving scenarios such as turning, ensuring the accuracy and timeliness of the temperature control strategy, and improving the overall energy efficiency and response speed of the system.

[0074] Optionally, determining the steering wheel grip area based on steering wheel angle data and candidate grip areas includes: in response to determining that the vehicle is in a straight-line cruising state based on steering wheel angle data, determining the candidate grip area within a preset standard grip range as the steering wheel grip area; in response to determining that the vehicle is in a turning state based on steering wheel angle data, determining the steering wheel grip area based on the turning angle size, turning direction, and candidate grip areas of the steering wheel angle data.

[0075] The aforementioned straight-line cruising state refers to a driving condition where the vehicle is traveling in a roughly straight line and the steering wheel remains relatively stationary or undergoes minor adjustments. In this state, the driver's grip position is usually fixed, often located near the 3 o'clock and 9 o'clock positions on the steering wheel.

[0076] The aforementioned preset standard grip range refers to a pre-defined grip position area that conforms to the habitual grip position of most drivers when driving straight. This range typically covers a certain angle interval between the left (9 o'clock) and right (3 o'clock) sides of the steering wheel rim, used to quickly lock the grip area during straight-line cruising.

[0077] The aforementioned turning state indicates a driving condition where the vehicle is performing a steering operation and the steering wheel is rotated significantly. In this state, the driver's grip position may shift with the steering action, or a cross grip may be adopted, causing the actual grip area to deviate from the preset standard grip range.

[0078] The aforementioned steering angle represents the angle by which the steering wheel has rotated from its initial position to its current position. This value reflects the degree of steering; a larger angle indicates a sharper steering or a greater steering range.

[0079] The aforementioned steering direction refers to the axial direction of the steering wheel rotation, typically divided into left and right turns, i.e., counterclockwise and clockwise directions. This direction determines the direction of the driver's center of gravity shift and the possible trend of changes in grip position.

[0080] For example, when determining the steering wheel grip area based on steering wheel angle data and candidate grip areas, the system determines that the vehicle is in a straight-line cruising state based on the steering wheel angle data, and identifies the candidate grip areas within a preset standard grip range as the steering wheel grip area. Specifically, this embodiment first analyzes the steering wheel angle data. If an extremely low rate of change in steering wheel angle is detected and the total angle is within a small threshold, the system determines that the vehicle is in a straight-line cruising state. Subsequently, the system reads the preset standard grip range, filters out candidate grip areas within this range, and directly determines the filtered areas as the final steering wheel grip area. The above process simplifies the calculation logic and ensures the stability of grip recognition under normal driving conditions.

[0081] The system determines that the vehicle is turning based on steering wheel angle data, and determines the steering wheel grip area based on the angle size, direction, and candidate grip areas. Specifically, in this embodiment, if a significant change in steering wheel angle data is detected, the system determines that the vehicle is turning. The system further analyzes the angle size and direction, and calculates the offset of the grip center of gravity based on the distribution of candidate grip areas. For example, if a left turn with a large angle is detected, the system may shift the key monitored candidate grip area to the left or upper part of the steering wheel, i.e., the cross grip position, based on the leftward turning trend. Finally, the system dynamically generates and determines the current steering wheel grip area by integrating the angle information and the candidate area distribution.

[0082] Based on the above optional embodiments, this application embodiment determines the candidate grip area within a preset standard grip range as the steering wheel grip area when the vehicle is determined to be in a straight-line cruising state based on steering wheel angle data, and determines the steering wheel grip area based on the steering wheel angle data, the angle size, the angle direction, and the candidate grip area when the vehicle is determined to be in a turning state based on steering wheel angle data. This achieves dynamic and accurate identification of the driver's grip position, ensuring that the actual grip area can be accurately locked in different scenarios such as straight driving and turning, avoiding energy waste in non-grip areas, and improving the response speed, recognition accuracy, and overall energy efficiency of the temperature control system.

[0083] Optionally, determining the vehicle driving scenario based on multi-source perception state data includes: determining an environmental judgment result based on vehicle environment data, wherein the environmental judgment result is used to characterize the vehicle's external thermal load state; determining a driving behavior judgment result based on vehicle operating state data, wherein the driving behavior judgment result is used to characterize the vehicle's dynamic driving conditions; and determining the vehicle driving scenario based on the environmental judgment result and the driving behavior judgment result.

[0084] The above environmental assessment results represent logical judgments of the vehicle's external thermal load status, obtained through algorithmic processing of vehicle body environmental data. These results are used to quantify the degree of thermal impact of the external environment on the vehicle's interior and the driver's hands, for example, distinguishing between high-temperature exposure environments, low-temperature cold environments, or suitable temperature environments.

[0085] The aforementioned external heat load status refers to the external heat input to the vehicle and driver's hands caused by external environmental factors, such as solar radiation and air temperature. This status directly affects the temperature reference of the steering wheel surface and the heat dissipation rate of the hands.

[0086] The driving behavior judgment results mentioned above represent logical judgments of the vehicle's dynamic driving conditions, obtained through algorithmic processing of vehicle operating status data. These results are used to distinguish different driving behavior modes, such as smooth cruising, aggressive driving, congested following, or waiting in a stop, thereby reflecting the driver's level of physiological stress and the risk of hand sweating.

[0087] The dynamic driving conditions described above reflect the real-time characteristics of the vehicle and driver's current motion state and operational intensity. Different dynamic driving conditions correspond to different thermal comfort and safety requirements. For example, aggressive driving may cause sweaty palms, requiring active cooling.

[0088] For example, when determining a vehicle driving scenario based on multi-source sensing state data, the environmental judgment result is determined based on vehicle body environmental data. This application embodiment receives vehicle body environmental data from onboard environmental sensors, including ambient temperature and solar radiation intensity. Then, the intelligent decision and control unit uses threshold-based rules to determine the current external thermodynamic environment of the vehicle based on the numerical range and combination characteristics of the vehicle body environmental data. For example, if the solar radiation intensity is higher than the threshold and the ambient temperature is high, it is determined to be a high external heat load state; if the ambient temperature is low, it is determined to be a low external heat load state. Finally, an environmental judgment result characterizing the external heat load state is output.

[0089] The system determines driving behavior based on vehicle operating status data. It acquires longitudinal acceleration, lateral acceleration, and combined longitudinal and lateral acceleration in real time via the vehicle's CAN bus, and integrates this data with multi-source data such as vehicle speed change rate, steering angle, and the currently selected driving mode. The intelligent decision and control unit's built-in driving behavior analysis algorithm compares these continuous kinematic parameters with preset threshold ranges. For example, when the combined acceleration exceeds a specific threshold and the duration meets the conditions, it is determined to be an "aggressive driving" state, where the driver is typically tense or gripping the steering wheel tightly. Conversely, when the acceleration is gradual, the steering angle is small, and the vehicle speed is stable, it is determined to be a "smooth cruising" state. Furthermore, the system combines the vehicle's current gear position or braking signals to further subdivide specific sub-scenarios such as "rapid acceleration," "rapid deceleration," or "low-speed crawling." Finally, the algorithm outputs a quantitative "driving behavior determination result," which not only characterizes the vehicle's current dynamic intensity but also indirectly reflects the driver's operating habits and potential physiological state, such as the risk of sweaty palms. This serves as a key input variable, working in conjunction with the environmental determination result to drive the strategy switching of the intelligent steering wheel temperature control system.

[0090] The vehicle driving scenario is determined based on the environmental assessment results and the driving behavior assessment results. This embodiment of the application logically fuses the environmental assessment results and the driving behavior assessment results obtained above. The system combines and maps environmental states with driving behaviors according to a preset scenario strategy library. For example, combining "high external heat load" with "aggressive driving" determines a "summer high-temperature aggressive driving scenario"; combining "low external heat load" with "cold start" determines a "winter cold start scenario." Finally, a specific vehicle driving scenario is generated as the basis for subsequently determining the target temperature.

[0091] Based on the above optional embodiments, this application embodiment determines the environmental judgment result based on vehicle body environmental data, determines the driving behavior judgment result based on vehicle operating status data, and determines the vehicle driving scenario based on the environmental judgment result and the driving behavior judgment result. This achieves refined multi-dimensional perception and scenario recognition of the driving environment, ensuring that the temperature control strategy can simultaneously respond to changes in the external thermal environment and the physiological needs brought about by the driver's dynamic driving behavior, thereby improving the accuracy of temperature control decisions and scenario adaptability.

[0092] Optionally, the hand physiological state data also includes: average hand skin temperature and hand humidity. Determining the target temperature corresponding to the steering wheel grip area based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user includes: determining the baseline comfort temperature range corresponding to the target user's hands based on the preset comfort temperature model; determining comfort deviation data using the average hand skin temperature, hand humidity, and baseline comfort temperature range; obtaining temperature control strategy parameters from a preset strategy library based on the vehicle driving scenario; and determining the target temperature corresponding to the steering wheel grip area based on the comfort deviation data using the temperature control strategy parameters.

[0093] The average hand skin temperature mentioned above represents the arithmetic mean of the skin temperature at all effective contact points within a defined steering wheel grip area. This data eliminates the influence of localized temperature fluctuations at contact points, more accurately reflecting the overall thermal balance of the driver's hands, and is a core input variable for assessing thermal comfort.

[0094] The aforementioned hand humidity indicates the moisture content on the skin surface of the hands within the steering wheel grip area, caused by sweating or environmental factors. This data is collected using a flexible humidity sensor array to assess the dryness of the hands. High humidity is often accompanied by a sticky feeling, reducing grip friction and affecting comfort, and is an important basis for triggering cooling or dehumidification strategies.

[0095] The aforementioned target user refers to a specific individual driver currently driving a vehicle. This application embodiment identifies the target user through facial recognition or historical learning records in order to load personalized parameters specific to that user.

[0096] The aforementioned baseline comfort temperature range represents the range of hand skin temperatures that the target user feels most comfortable under their current physiological state, calculated based on a preset comfort temperature model. This range is typically centered on the mean and has a certain tolerance range, representing an ideal state of thermal comfort.

[0097] The aforementioned comfort deviation data represents the difference or degree of deviation between the average hand skin temperature and the baseline comfort temperature range. This data quantifies the distance between the current hand condition and the ideal comfort state, and serves as a direct basis for determining the heating or cooling power. A positive deviation may indicate excessive coolness, while a negative deviation may indicate excessive heat; these need to be corrected in conjunction with humidity data.

[0098] The aforementioned preset strategy library, also known as the scenario strategy library, represents the set of rules stored in the intelligent decision and control unit, containing temperature control strategy parameters for different vehicle driving scenarios. These parameters define the temperature adjustment rate, maximum / minimum power limits, and humidity compensation coefficients under different scenarios, including rapid hand warming, cooling and drying, and constant comfort maintenance.

[0099] The aforementioned temperature control strategy parameters represent specific numerical values ​​or logical rules retrieved from the preset strategy library to guide the calculation of the target temperature. These parameters include heating / cooling power coefficients, temperature adjustment slopes, humidity compensation thresholds, etc., and are used to translate comfort deviations into specific temperature control commands.

[0100] For example, when determining the target temperature for the steering wheel grip area based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user, the system first determines the baseline comfort temperature range for the target user's hands based on the preset comfort temperature model. This embodiment reads the target user's personal comfort temperature model and, in conjunction with the current vehicle driving scenario, such as the season or ambient temperature background, queries or calculates the user's baseline comfort temperature range in the current situation. For example, if the model shows that the user prefers 32℃-34℃ in winter, the system locks this range as the baseline comfort temperature range.

[0101] Secondly, comfort deviation data is determined using the average skin temperature of the hands, hand humidity, and a baseline comfort temperature range. This embodiment acquires the average skin temperature and humidity of the hands within the current steering wheel grip area. The system compares the average skin temperature with the baseline comfort temperature range and calculates the temperature deviation value. Simultaneously, the system evaluates the hand humidity data; if the humidity exceeds a preset dryness threshold, a humidity correction coefficient is generated. Combining the temperature deviation and the humidity correction coefficient, the final comfort deviation data is generated. This data reflects the total degree and direction of the hand's deviation from a comfortable state, such as the need for heating, cooling, or dehumidification.

[0102] Then, temperature control strategy parameters are obtained from a preset strategy library based on the vehicle driving scenario. This embodiment uses the determined vehicle driving scenario as an index to retrieve the corresponding temperature control strategy parameters from the preset strategy library. For example, in the "winter cold start" scenario, "rapid hand warming" strategy parameters are obtained, including high-power heating coefficient and fast response time; in the "summer congestion" scenario, "cool and dry" strategy parameters are obtained, including cooling power coefficient and humidity sensitivity coefficient.

[0103] Finally, the target temperature corresponding to the steering wheel grip area is determined based on the comfort deviation data using the temperature control strategy parameters. In this embodiment, the comfort deviation data is calculated using the retrieved temperature control strategy parameters. Specifically, the system calculates the required power or target temperature value for each thermoelectric module based on the magnitude and direction of the deviation, combined with the adjustment coefficient in the strategy parameters. For example, if the deviation is a large positive value (i.e., the hands are very cold) and the strategy parameter is rapid heating, the target temperature is set to a higher value above the comfort range to achieve rapid heating; if the deviation is a small negative value and the humidity is high, the target temperature is set slightly below the comfort range for mild cooling and dehumidification. The target temperature corresponding to the steering wheel grip area is then determined.

[0104] Based on the above optional embodiments, this application embodiment determines the baseline comfort temperature range corresponding to the target user's hands according to a preset comfort temperature model, determines comfort deviation data using the average skin temperature of the hands, hand humidity, and the baseline comfort temperature range, obtains temperature control strategy parameters from a preset strategy library based on the vehicle driving scenario, and determines the target temperature corresponding to the steering wheel grip area based on the comfort deviation data according to the temperature control strategy parameters. This achieves accurate quantitative assessment and personalized dynamic adjustment of the driver's hand thermal comfort state, ensuring that the temperature control system can intelligently adjust the heating or cooling intensity according to individual differences, humidity changes, and driving scenarios, thereby improving driving comfort, dryness, and energy utilization efficiency.

[0105] Optionally, temperature control of the steering wheel grip area based on the target temperature includes: generating a zone control command based on the target temperature, wherein the zone control command is used to determine the current direction and current amplitude of the thermoelectric semiconductor module in the steering wheel grip area; and performing temperature control of the steering wheel grip area based on the zone control command.

[0106] The aforementioned zone control command represents a data signal generated by the intelligent decision and control unit based on the target temperature, used to independently control the operating status of each thermoelectric semiconductor temperature control actuator module within the steering wheel grip area. This command includes the required current direction and current amplitude for each module.

[0107] The aforementioned thermoelectric semiconductor module refers to a miniature thermoelectric semiconductor temperature control actuator unit embedded in the steering wheel rim. Based on the Peltier effect, it absorbs or releases heat by applying direct current, possessing both heating and cooling functions, and can be independently controlled.

[0108] The aforementioned current direction indicates the polarity direction of the direct current flowing to the thermoelectric semiconductor module. In the embodiments of this application, the current direction determines the direction of heat flow due to the Peltier effect, that is, whether the module surface releases heat to the hand or absorbs heat from the hand, i.e., heating mode or cooling mode.

[0109] The aforementioned current amplitude represents the magnitude or intensity of the direct current flowing to the thermoelectric semiconductor module. In the embodiments of this application, the current amplitude determines the power density of the module, i.e., the amount of heat transferred per unit time, thereby controlling the rate of temperature regulation and the final temperature level achieved.

[0110] For example, when controlling the temperature of the steering wheel grip area based on a target temperature, a zone control command is generated based on the target temperature. This zone control command determines the current direction and amplitude of the thermoelectric semiconductor modules within the steering wheel grip area. This embodiment receives the target temperature calculated for the steering wheel grip area and, combined with the real-time status of each thermoelectric semiconductor module, calculates the required current parameters for each module using an internal algorithm, such as a Proportional-Integral-Derivative (PID) control algorithm. The system determines the current direction of each module to match heating or cooling needs; simultaneously, it calculates the current amplitude to match the power density required to achieve the target temperature. Finally, the above parameters are encapsulated into a zone control command and sent to the corresponding drive circuit.

[0111] The temperature of the steering wheel grip area is controlled according to the zone control command. In this embodiment, the zone control command is transmitted to the drive circuits of each thermoelectric semiconductor module within the steering wheel grip area. The drive circuits switch the operating mode of the modules based on the current direction, such as heating or cooling, and adjust the output power according to the current amplitude. The system continuously monitors hand temperature feedback and dynamically adjusts the current command to quickly approach and maintain the actual temperature of the steering wheel grip area at the target temperature, thus completing closed-loop temperature control.

[0112] Based on the above optional embodiments, this application embodiment generates zone control commands based on the target temperature, and controls the temperature of the steering wheel grip area according to the zone control commands. This achieves independent and precise regulation of each thermoelectric semiconductor module in the steering wheel grip area, ensuring that the heating or cooling power can be dynamically adjusted according to the grip position and driver needs. This improves the response speed, temperature control accuracy and energy utilization efficiency of temperature control, and effectively avoids energy waste in non-grip areas.

[0113] Optionally, the vehicle steering wheel temperature control method further includes: re-identifying the current steering wheel grip area in response to a change in the position of the steering wheel grip area, and updating the zone control command based on the current steering wheel grip area.

[0114] The aforementioned change in the position of the steering wheel grip area indicates that the driver alters the contact position or grip posture of their hands on the steering wheel surface during driving, resulting in a change in the physical coordinates, shape, or pressure distribution characteristics of the previously identified steering wheel grip area. This change in position may be caused by the driver adjusting their grip posture, crossing their hands on the wheel, or a shift in the center of gravity during cornering.

[0115] The aforementioned re-identification of the current steering wheel grip area refers to the process by which the intelligent decision-making and control unit, after detecting a significant change in pressure distribution data, re-executes the grip area identification algorithm to generate a steering wheel grip area reflecting the driver's latest actual grip position. This process includes re-clustering the pressure distribution data and making corrections by incorporating steering wheel angle data to determine a new effective contact area.

[0116] For example, in response to a change in the position of the steering wheel grip area, the current steering wheel grip area is re-identified. This embodiment continuously monitors pressure distribution data from a flexible pressure sensor array. When a significant displacement of the pressure center, a change in the pressure distribution pattern, or a pressure value in the original grip area falling below a preset threshold while high pressure accumulates in a new area is detected, it is determined that a change in the position of the steering wheel grip area has occurred. At this time, the intelligent decision and control unit triggers a re-identification process, using the latest pressure distribution data and the current steering wheel angle data, through cluster analysis and logical judgment, to recalculate and determine the current steering wheel grip area reflecting the driver's latest grip posture.

[0117] Based on the current steering wheel grip area, the zone control command is updated. In this embodiment, after determining the current steering wheel grip area, the control parameters of the thermoelectric semiconductor modules in the original zone control command for the old grip area, such as current direction and amplitude, are cleared to zero or set to standby. Simultaneously, the current parameters corresponding to the new target temperature are calculated for the thermoelectric semiconductor modules in the new current steering wheel grip area. The system generates the updated zone control command and sends it to the drive circuit to change the operating state of each thermoelectric semiconductor module, causing the temperature control zone to migrate in real time as the grip position moves.

[0118] Based on the above optional embodiments, this application embodiment re-identifies the current steering wheel grip area in response to changes in the steering wheel grip area, and updates the zone control command based on the current steering wheel grip area. This achieves real-time tracking of the driver's dynamic grip position and seamless switching of the temperature control area, ensuring that heating or cooling energy is always accurately applied to the actual grip area, avoiding energy waste in non-grip areas, and improving the response speed, temperature control accuracy, and energy utilization efficiency of the temperature control system.

[0119] Optionally, the vehicle steering wheel temperature control method further includes: acquiring temperature preference data of the target user, wherein the temperature preference data is used to represent the target user's preferred hand temperature range under different ambient temperatures, and the target user's preference for temperature control response speed; and constructing a preset comfort temperature model based on the temperature preference data.

[0120] The aforementioned temperature preference data represents a set of parameters stored in the intelligent decision and control unit that reflect the personalized thermal comfort needs of the target user. Specifically, this data includes the range of hand temperatures that the target user feels comfortable under different ambient temperatures, as well as the target user's preference for the speed of temperature control system adjustments, such as a preference for rapid or gentle warming.

[0121] The hand preference temperature range mentioned above represents the range of hand skin temperature that a target user subjectively finds most comfortable under a specific ambient temperature. This range is typically obtained through user calibration or learning from historical data; for example, in a winter environment, a target user might prefer a hand temperature of 32°C to 34°C.

[0122] The aforementioned ambient temperature refers to the external air temperature of the vehicle or the basic ambient temperature inside the cabin. In this embodiment, the preferred hand temperature range is dynamically adjusted according to different ambient temperatures, such as summer, winter, and spring / autumn, to cope with different heat exchange conditions.

[0123] The preference for the aforementioned temperature control response speed indicates the target user's subjective preference for how quickly the steering wheel temperature adjusts. This parameter reflects whether the user prefers the system to quickly correct the temperature at maximum power or slowly adjust it to a comfortable state at lower power when the temperature deviates from the comfort range. For example, some users prefer rapid hand warm-up during cold starts, while others prefer gentle heating to avoid burns.

[0124] For example, when constructing a preset comfort temperature model, temperature preference data of the target user is acquired. This temperature preference data represents the target user's preferred hand temperature range under different ambient temperatures, as well as the target user's preference for temperature control response speed. In this embodiment, when the target user uses the system for the first time or when the system enters learning mode, the system guides the user through an interactive interface for calibration, or automatically analyzes the target user's historical temperature control feedback data during driving. The system records the target user's evaluation of comfort temperature under different ambient temperatures, such as evaluations for summer and winter, as well as the user's subjective choices or behavioral feedback regarding the speed of temperature adjustment, thereby extracting the target user's preferred hand temperature range and preference for temperature control response speed, and storing these as temperature preference data.

[0125] A preset comfort temperature model is constructed based on temperature preference data. In this embodiment, the acquired temperature preference data is input to the intelligent decision and control unit. The system uses this data to establish a mathematical mapping relationship and generate the preset comfort temperature model. This model includes algorithms for baseline comfort temperature ranges for different ambient temperatures, as well as PID control parameters or power adjustment curves determined based on response speed preferences. By constructing this model, the system has the ability to generate personalized temperature control commands for specific target users.

[0126] Based on the above optional embodiments, this application embodiment achieves accurate capture and modeling of the driver's personalized thermal comfort needs by acquiring the target user's temperature preference data and constructing a preset comfort temperature model based on the temperature preference data. This ensures that the temperature control system can dynamically adjust the comfort temperature range and adjustment strategy according to the user's individual differences and subjective preferences, thereby improving the personalization of the temperature control service and user satisfaction.

[0127] Figure 2 This is a schematic diagram of an optional vehicle steering wheel temperature control system according to an embodiment of this application, as shown below. Figure 2 As shown, the system includes an intelligent decision and control unit, a vehicle CAN bus, a multi-dimensional sensing steering wheel rim, a thermoelectric semiconductor temperature control actuator array, and in-vehicle environmental sensors. The multi-dimensional sensing steering wheel rim contains a ring of flexible temperature, humidity, and pressure sensors to accurately sense the temperature, sweat levels, and pressure distribution in the hand contact area. The thermoelectric semiconductor temperature control actuator array consists of multiple independent micro-thermoelectric semiconductor modules embedded in a matrix within the steering wheel rim. Each module can switch the direction of current to achieve heating or cooling. The intelligent decision and control unit, integrated into the cockpit domain controller, receives all sensor data and vehicle CAN bus information, performs calculations using built-in algorithms, including a dynamic grip area recognition algorithm, a thermal comfort model, and a scenario strategy library, and outputs control commands to independently drive each thermoelectric semiconductor module, forming a dynamic temperature control zone. The in-vehicle environmental sensors monitor external environmental parameters in real time, such as ambient temperature and sunlight intensity, providing a basis for the system to determine driving scenarios. Each module works collaboratively through data connections to form a complete closed-loop system from data acquisition and intelligent decision-making to execution control, realizing intelligent zoned temperature control based on biological perception and driving scenarios.

[0128] Figure 3 This is a schematic diagram of an optional vehicle steering wheel temperature control method according to an embodiment of this application, as shown below. Figure 3 As shown in the diagram, this schematic illustrates the intelligent control closed loop of this application, from data acquisition to closed-loop optimization. After system startup, it first enters the multi-source data acquisition layer. The system uses a flexible sensor array to monitor the temperature, humidity, and pressure distribution of the hand contact area in real time. It uses an eye-tracking camera to assist in determining the focus of the gaze, thereby indirectly predicting hand activities. It also combines the ambient temperature, driving mode, time, and other scene information obtained from the vehicle's CAN bus, as well as the sunlight intensity monitored by the onboard environmental sensors, to achieve multi-source data fusion.

[0129] The system then enters the core algorithm processing layer. First, it uses a dynamic grip area recognition algorithm to perform cluster analysis on the pressure data to identify the primary and secondary grip areas. Next, it assesses the physiological state of the hand and calculates the average hand temperature, humidity, and comfort deviation. At the same time, the driving scenario judgment engine comprehensively analyzes factors such as season, time, and driving mode to determine the current driving scenario. Finally, based on a personalized thermal comfort model and target temperature calculation module, a dynamic target temperature is set for each grip area.

[0130] After entering the hierarchical control strategy layer, the system triggers the corresponding hierarchical control strategy according to the preset scenario strategy library: in scenarios such as cold start in winter, the quick warm-up mode is executed to heat the grip area with maximum power; in scenarios of sun exposure and traffic jams in summer, the cool and dry mode is executed to provide local cooling and ventilation; in scenarios of intense driving, the sweat-proof safety mode is executed to cool the grip area or reduce the heating power; and in normal conditions, the PID algorithm is used to maintain constant comfort.

[0131] Dynamic zone execution includes the system independently driving the thermoelectric semiconductor temperature control actuator array embedded in the steering wheel, dynamically adjusting the current direction and amplitude of each thermoelectric semiconductor module, realizing the switching of heating or cooling functions and the adjustment of power density according to grip pressure, and dynamically adjusting the area according to changes in grip posture.

[0132] Meanwhile, the system monitors and provides feedback on the effects in real time. If the temperature reaches the comfortable range, it maintains the operating mode; if the temperature deviation is significant, it adjusts the output; if the grip area changes, it updates the zoning.

[0133] Finally, in the system optimization layer, the system continuously monitors changes in the driver's hand temperature and makes PID adjustments, records user preferences to establish a personal comfort model, analyzes usage habits, optimizes response speed, and manages energy efficiency based on battery charge. If abnormal hand temperature data or pressure signals are detected, it can also help determine the driver's tension or fatigue state, thereby achieving accurate, dynamic, and personalized temperature control and driving safety monitoring.

[0134] Figure 4 This is a schematic diagram of another optional vehicle steering wheel temperature control method according to an embodiment of this application, such as... Figure 4 As shown. The method includes:

[0135] Step S401: Obtain multi-source perception state data of the vehicle, wherein the multi-source perception state data includes: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data.

[0136] Step S402: Perform cluster analysis based on pressure distribution data to obtain candidate gripping regions, wherein the pressure distribution value of the candidate gripping regions is greater than a preset pressure threshold.

[0137] Step S403: Based on the steering wheel angle data, it is determined that the vehicle is in a straight-line cruising state, and the candidate grip area within the preset standard grip range is determined as the steering wheel grip area.

[0138] Step S404: The response determines that the vehicle is in a turning state based on the steering wheel angle data, and determines the steering wheel grip area based on the steering wheel angle size, steering direction and candidate grip area of ​​the steering wheel angle data;

[0139] Step S405: Determine the environmental assessment result based on the vehicle body environmental data, wherein the environmental assessment result is used to characterize the vehicle's external thermal load state.

[0140] Step S406: Determine the driving behavior judgment result based on the vehicle operating status data, wherein the driving behavior judgment result is used to characterize the dynamic driving conditions of the vehicle.

[0141] Step S407: Determine the vehicle driving scenario based on the environmental assessment results and the driving behavior assessment results;

[0142] Step S408: Determine the baseline comfort temperature range corresponding to the target user's hand based on the preset comfort temperature model;

[0143] Step S409: Determine comfort deviation data using average hand skin temperature, hand humidity, and reference comfort temperature range;

[0144] Step S410: Obtain temperature control strategy parameters from the preset strategy library based on the vehicle driving scenario;

[0145] Step S411: Determine the target temperature corresponding to the steering wheel grip area based on the comfort deviation data according to the temperature control strategy parameters;

[0146] Step S412: Generate zone control instructions based on the target temperature, wherein the zone control instructions are used to determine the current direction and current amplitude of the thermoelectric semiconductor module in the steering wheel grip area;

[0147] Step S413: Perform temperature control on the steering wheel grip area according to the zone control command.

[0148] Based on the above steps S401 to S413, this embodiment of the application adopts a dynamic zoned temperature control method. By acquiring multi-source sensing state data of the vehicle, including: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data, the steering wheel grip area and vehicle driving scenario of the target user are determined based on the multi-source sensing state data. Then, the target temperature corresponding to the steering wheel grip area is determined according to the vehicle driving scenario and the preset comfort temperature model corresponding to the target user. The preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort. Finally, the temperature of the steering wheel grip area is controlled according to the target temperature, thereby achieving the purpose of dynamically controlling the steering wheel temperature. This achieves the technical effect of precise, personalized, and scenario-based intelligent temperature control, and solves the technical problems of crude and passive control, lack of personalization, and lack of scenario adaptability in related steering wheel temperature control systems.

[0149] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0150] Figure 5 This is an optional embodiment of a vehicle steering wheel temperature control device according to an embodiment of this application, such as... Figure 5 As shown. It should be noted that this device can be used to execute the aforementioned vehicle steering wheel temperature control method. The device includes: a first acquisition module 501, used to acquire multi-source sensing state data of the vehicle, wherein the multi-source sensing state data includes: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data; a first determination module 502, used to determine the steering wheel grip area of ​​the target user and the vehicle driving scenario based on the multi-source sensing state data; a second determination module 503, used to determine the target temperature corresponding to the steering wheel grip area according to the vehicle driving scenario and the preset comfort temperature model corresponding to the target user, wherein the preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort; and a control module 504, used to perform temperature control on the steering wheel grip area according to the target temperature.

[0151] Optionally, the hand physiological state data includes pressure distribution data, and the vehicle operating state data includes steering wheel angle data. The first determining module 502 is further used to: perform cluster analysis based on the pressure distribution data to obtain candidate gripping areas, wherein the pressure distribution value of the candidate gripping areas is greater than a preset pressure threshold; and determine the steering wheel gripping area based on the steering wheel angle data and the candidate gripping areas.

[0152] Optionally, the first determining module 502 is further configured to: in response to determining that the vehicle is in a straight-line cruising state based on the steering wheel angle data, determine the candidate grip area within the preset standard grip range as the steering wheel grip area; in response to determining that the vehicle is in a turning state based on the steering wheel angle data, determine the steering wheel grip area according to the turning angle size, turning direction and candidate grip area of ​​the steering wheel angle data.

[0153] Optionally, the first determining module 502 is further configured to: determine an environmental determination result based on vehicle environmental data, wherein the environmental determination result is used to characterize the vehicle's external thermal load state; determine a driving behavior determination result based on vehicle operating status data, wherein the driving behavior determination result is used to characterize the vehicle's dynamic driving conditions; and determine the vehicle driving scenario based on the environmental determination result and the driving behavior determination result.

[0154] Optionally, the hand physiological state data also includes: average hand skin temperature and hand humidity. The second determining module 503 is further used to: determine the baseline comfort temperature range corresponding to the target user's hand according to the preset comfort temperature model; determine comfort deviation data using the average hand skin temperature, hand humidity, and baseline comfort temperature range; obtain temperature control strategy parameters from the preset strategy library based on the vehicle driving scenario; and determine the target temperature corresponding to the steering wheel grip area based on the comfort deviation data according to the temperature control strategy parameters.

[0155] Optionally, the control module 504 is further configured to: generate zone control instructions based on the target temperature, wherein the zone control instructions are used to determine the current direction and current amplitude of the thermoelectric semiconductor module in the steering wheel grip area; and perform temperature control on the steering wheel grip area according to the zone control instructions.

[0156] Optionally, the vehicle steering wheel temperature control device further includes: an update module 505, used to re-identify the current steering wheel grip area in response to a change in the position of the steering wheel grip area, and to update the zone control command based on the current steering wheel grip area.

[0157] Optionally, the vehicle steering wheel temperature control device further includes: a second acquisition module 506, used to acquire temperature preference data of the target user, wherein the temperature preference data is used to represent the target user's preferred hand temperature range under different ambient temperatures, and the target user's preference for temperature control response speed; and a construction module 507, used to construct a preset comfort temperature model based on the temperature preference data.

[0158] Embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application when it runs.

[0159] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0160] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0161] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0162] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0163] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0164] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0165] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0166] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0167] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0168] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for controlling the temperature of a vehicle steering wheel, characterized in that, include: Acquire multi-source perception state data of the vehicle, wherein the multi-source perception state data includes: hand physiological state data associated with the steering wheel, vehicle operating state data, and vehicle environment data; Based on the multi-source perception state data, the steering wheel grip area of ​​the target user and the vehicle driving scenario are determined. The target temperature corresponding to the steering wheel grip area is determined based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user, wherein the preset comfort temperature model is used to represent the mapping relationship between the user's hand skin temperature and thermal comfort. Temperature control is performed on the steering wheel grip area based on the target temperature.

2. The vehicle steering wheel temperature control method according to claim 1, characterized in that, The hand physiological state data includes pressure distribution data; the vehicle operating state data includes steering wheel angle data; and the steering wheel grip area of ​​the target user is determined based on the multi-source sensing state data, including: Cluster analysis is performed based on the pressure distribution data to obtain candidate gripping regions, wherein the pressure distribution value of the candidate gripping regions is greater than a preset pressure threshold. The steering wheel grip area is determined based on the steering wheel angle data and the candidate grip area.

3. The vehicle steering wheel temperature control method according to claim 2, characterized in that, Determining the steering wheel grip area based on the steering wheel angle data and the candidate grip areas includes: The response determines that the vehicle is in a straight-line cruising state based on the steering wheel angle data, and determines the candidate grip area within the preset standard grip range as the steering wheel grip area; The response determines that the vehicle is turning based on the steering wheel angle data, and determines the steering wheel grip area based on the angle size, angle direction and candidate grip area of ​​the steering wheel angle data.

4. The vehicle steering wheel temperature control method according to claim 1, characterized in that, The vehicle driving scenario determined based on the multi-source perception state data includes: An environmental assessment result is determined based on the vehicle body environmental data, wherein the environmental assessment result is used to characterize the external thermal load state of the vehicle. The driving behavior determination result is determined based on the vehicle operating status data, wherein the driving behavior determination result is used to characterize the dynamic driving condition of the vehicle. The vehicle driving scenario is determined based on the environmental assessment results and the driving behavior assessment results.

5. The vehicle steering wheel temperature control method according to claim 1, characterized in that, The hand physiological state data also includes: average hand skin temperature and hand humidity. The target temperature for the steering wheel grip area is determined based on the vehicle driving scenario and the preset comfort temperature model corresponding to the target user, including: The baseline comfort temperature range corresponding to the target user's hand is determined based on the preset comfort temperature model. Comfort deviation data are determined using the average skin temperature of the hand, the humidity of the hand, and the reference comfortable temperature range; Temperature control strategy parameters are obtained from a preset strategy library based on the vehicle driving scenario; The target temperature corresponding to the steering wheel grip area is determined based on the comfort deviation data according to the temperature control strategy parameters.

6. The vehicle steering wheel temperature control method according to claim 1, characterized in that, Temperature control of the steering wheel grip area based on the target temperature includes: Based on the target temperature, a zone control command is generated, wherein the zone control command is used to determine the current direction and current amplitude of the thermoelectric semiconductor module in the steering wheel grip area; Temperature control is performed on the steering wheel grip area according to the zonal control command.

7. The vehicle steering wheel temperature control method according to claim 6, characterized in that, The vehicle steering wheel temperature control method also includes: In response to a change in the position of the steering wheel grip area, the current steering wheel grip area is re-identified, and the zone control command is updated based on the current steering wheel grip area.

8. The vehicle steering wheel temperature control method according to claim 1, characterized in that, The vehicle steering wheel temperature control method also includes: Acquire the temperature preference data of the target user, wherein the temperature preference data is used to represent the target user's preferred hand temperature range under different ambient temperatures, and the target user's preference for temperature control response speed; The preset comfort temperature model is constructed based on the temperature preference data.

9. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 8.

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