Intelligent lumbar support adjustment method, system, electronic device, and computer-readable medium

Abstract

The intelligent waist support adjusting method provided by the application belongs to the technical field of automobiles, acquires vehicle physical signals, the physical signals including vehicle acceleration, angular velocity and seat pressure; identifies the current comprehensive driving state and the passenger posture according to the vehicle physical signals; calculates the waist support target parameter at the current time according to the comprehensive driving state and the passenger posture; and adjusts the physical form of the waist support according to the target parameter, which fundamentally changes the characteristic of the seat waist support being "unchanging". When the vehicle accelerates / brakes, the reverse supporting force is provided in time to offset the pulling of inertia on the lumbar vertebrae; when turning, the support on the outside of the curve is actively strengthened to maintain the spine neutral and reduce the distortion; and on the bumpy road, the impact energy transmitted to the lumbar vertebrae is absorbed and buffered through the quick and flexible response of the support mechanism. This effectively reduces the risk of disc herniation or wear due to abnormal stress.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to an intelligent lumbar support adjustment method, system, electronic device, and computer-readable medium. Background Technology

[0002] Current car seats are typically equipped with static or manually adjustable lumbar support, allowing users to manually adjust the support height and elevation to suit their individual comfort. Some high-end models also feature a memory function, which can store multiple users' preset positions.

[0003] Static support cannot adapt to dynamic driving conditions (such as bumps, turns, acceleration / deceleration), resulting in uneven stress on the lumbar spine, which can easily lead to fatigue or intervertebral disc problems; manual adjustment requires the driver to be distracted, affecting driving safety; and the memory function is only for static presets and cannot respond to changes in road conditions in real time. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art, and proposes an intelligent lumbar support adjustment method and system.

[0005] In a first aspect, embodiments of the present invention provide an intelligent lumbar support adjustment method, comprising:

[0006] Acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure;

[0007] The current overall driving status and occupant posture are identified based on the vehicle's physical signals.

[0008] The target parameters for lumbar support at the current moment are calculated based on the overall driving status and the occupant posture.

[0009] Adjust the physical shape of the lumbar support according to the target parameters.

[0010] In some embodiments, the step of acquiring vehicle physical signals includes:

[0011] Obtain the linear acceleration and angular velocity of the vehicle in three directions;

[0012] Obtain pressure distribution maps of the occupant's back and buttocks against the seat contact surface.

[0013] In some embodiments, the step of acquiring vehicle physical signals further includes: acquiring road information ahead of the vehicle.

[0014] In some embodiments, the step of identifying the current comprehensive driving state and occupant posture based on the vehicle physical signal includes: receiving the vehicle physical signal and interpreting the vehicle physical signal into a specific current comprehensive driving state and occupant posture through a built-in algorithm model, wherein the algorithm model includes a rule-based state machine or a lightweight machine learning model.

[0015] In some embodiments, the step of calculating the target parameters for lumbar support at the current moment based on the overall driving state and occupant posture includes:

[0016] The system combines user-preset patterns or self-learning to generate multiple support strategy mapping tables. These mapping tables define the target parameters that the lumbar support should have under different scenarios and state combinations. Based on the currently identified state, the system matches or calculates to generate the optimal support target parameters, which include the support point location, support strength, and support area.

[0017] In some embodiments, the step of adjusting the physical form of the lumbar support according to the target parameters includes: the actuator precisely moving to adjust the physical form of the lumbar support; simultaneously, continuously monitoring the pressure changes after adjustment, generating feedback signals and comparing the actual pressure distribution with the expected target; if there is a deviation, fine-tuning the instructions through a closed-loop control algorithm until the best support effect is achieved.

[0018] In some embodiments, the system also includes: allowing users to switch vehicle modes or manually fine-tune the physical form of the lumbar support at any time via an interactive interface.

[0019] Secondly, embodiments of the present invention provide an intelligent lumbar support adjustment system, comprising:

[0020] The acquisition unit is used to acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure.

[0021] The identification unit is used to identify the current overall driving status and occupant posture based on the vehicle's physical signals;

[0022] The calculation unit is used to calculate the target parameters of lumbar support at the current moment based on the overall driving status and occupant posture;

[0023] An execution unit is used to adjust the physical shape of the lumbar support according to the target parameters.

[0024] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0025] One or more processors;

[0026] Memory, used to store one or more programs;

[0027] When the one or more programs are executed by the one or more processors, the one or more processors implement any of the methods.

[0028] Fourthly, embodiments of the present invention also provide a computer-readable medium storing a computer program, which, when executed by a processor, implements the steps of any of the methods described.

[0029] The intelligent lumbar support adjustment method provided by this invention acquires vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure; identifies the current overall driving state and occupant posture based on the electrical signals; calculates the target parameters for lumbar support at the current moment based on the overall driving state and occupant posture; and adjusts the physical form of the lumbar support according to the target parameters. This adjustment method fundamentally changes the "static" characteristic of seat lumbar support. During vehicle acceleration / braking, it provides immediate counter-support force to counteract the inertial pull on the lumbar spine; during cornering, it actively strengthens the support on the outer side of the curve to maintain spinal neutrality and reduce twisting; on bumpy roads, the rapid and flexible response of the support mechanism absorbs and buffers the impact energy transmitted to the lumbar spine. This effectively reduces the risk of intervertebral disc herniation or wear due to abnormal stress. Furthermore, it can identify sub-health states such as "slight fatigue during long-distance driving," automatically adjusting the support points and force to promote lumbar blood circulation and relieve static muscle load, thereby significantly improving comfort during long-term seating and combating fatigue. All adjustments are completed automatically, eliminating the need for the driver to search for and operate manual adjustment buttons, allowing them to remain focused on driving and improving driving safety. Furthermore, this method goes beyond static physical adjustments; through "mode selection" and "adaptive learning" functions, the same hardware can adapt to the personalized physiological needs of users with different body types and driving habits, achieving an evolution from a "universal seat" to a "personalized health cabin." Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the steps of an embodiment of the intelligent lumbar support adjustment method of the present invention;

[0031] Figure 2 This is a schematic diagram illustrating the steps of one embodiment of the present invention for acquiring vehicle physical signals;

[0032] Figure 3 This is a schematic diagram illustrating the steps of an embodiment of the present invention for adjusting the physical form of the lumbar support according to the target parameters;

[0033] Figure 4 This is a schematic diagram of the structure of one embodiment of the intelligent lumbar support adjustment system of the present invention;

[0034] Figure 5 This is a schematic diagram of the structure of an embodiment of the electronic device of the present invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0036] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0037] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0038] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0039] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0040] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0041] In related technologies, static support cannot adapt to dynamic driving conditions (such as bumps, turns, acceleration / deceleration), resulting in uneven stress on the lumbar spine, which can easily lead to fatigue or intervertebral disc problems; manual adjustment requires the driver to be distracted, affecting driving safety; and the memory function is only for static presets and cannot respond to changes in road conditions in real time.

[0042] The core function of the automatic lumbar support adjustment method for seats described in this invention lies in its ability to intelligently decide and proactively adjust the physical form of the lumbar support by sensing the vehicle and occupant status in real time, thereby achieving the goal of dynamically protecting lumbar spine health. The following will elaborate on the method's steps, specific implementation scheme, logical relationships, and technical effects from a functional perspective.

[0043] The specific terminology involved in this invention is as follows:

[0044] ECU: Electronic Control Unit

[0045] IMU: Inertial Measurement Unit

[0046] Air cushion / airbag: refers to the inflatable support structure in the lumbar region of the seat.

[0047] PID control: Proportional-Integral-Derivative Control, a proportional-integral-derivative control algorithm.

[0048] To address at least one of the technical problems existing in the aforementioned related technologies, the present invention provides an intelligent lumbar support adjustment method. Figure 1 A flowchart illustrating the steps of an intelligent lumbar support adjustment method provided in an embodiment of the present invention.

[0049] like Figure 1 As shown, the intelligent lumbar support adjustment method includes the following steps:

[0050] Step S10: Acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure.

[0051] Please see Figure 2 In this embodiment, the step of acquiring vehicle physical signals includes: acquiring the linear acceleration and angular velocity of the vehicle in three directions; and acquiring the pressure distribution map of the occupant's back and buttocks in contact with the seat.

[0052] Specifically, to implement the above method, this embodiment adopts the following specific technical solution.

[0053] In this embodiment, a vehicle dynamic sensing unit is included, typically implemented by one or more inertial measurement units (IMUs). This unit is fixed to the vehicle chassis or a rigid body structure and continuously measures the vehicle's linear acceleration (for sensing rapid acceleration, deceleration, and impacts) and angular velocity (for sensing lateral and yaw motion during cornering and lane changes) in three directions. Essentially, it quantifies the vehicle's real-time motion attitude into processable data.

[0054] Furthermore, it also includes an occupant-seat interaction sensing unit: implemented by a high-resolution pressure sensor array embedded under the surface of the seat cushion and backrest. This array can accurately map the pressure distribution between the occupant's back and buttocks and the seat contact surface. By analyzing the map, the occupant's sitting posture (whether leaning forward, backward, or sideways), body center of gravity shift, and muscle tension can be inferred.

[0055] Furthermore, it also includes: obtaining information about the road ahead of the vehicle.

[0056] In this embodiment, a forward-looking road condition perception unit may also be included: this unit can integrate signal input from the vehicle's existing forward-facing camera or radar. This unit does not directly participate in support adjustment, but can provide early warning information such as "approaching a speed bump" or "uneven road surface ahead," allowing the decision-making module to prepare and adjust strategies in advance.

[0057] Step S20: Identify the current overall driving status and occupant posture based on the vehicle's physical signals.

[0058] Understandably, this step is responsible for processing information, making judgments, and issuing instructions, and is usually implemented by a dedicated seat control electronic control unit (ECU).

[0059] In this embodiment, the ECU receives real-time data streams from all sensing modules. Through a built-in algorithmic model (e.g., a rule-based state machine or a lightweight machine learning model), the raw data is fused and interpreted into specific "driving scenarios" and "occupant states." For example, it identifies composite states such as "high-speed cornering," "continuous gravel road bumps," and "driver slightly fatigued and leaning to the right during long-distance driving."

[0060] Furthermore, the ECU pre-stores or learns and generates multiple support strategy mapping tables. These mapping tables define the target parameters (such as support point location, support strength, and support area) for lumbar support under different "scenario + state" combinations. During decision-making, the ECU matches or calculates the optimal support target parameters based on the currently identified state.

[0061] Furthermore, this ECU serves as the logical backend for the user interface. It stores user-selected preset modes such as "Comfort," "Sport," and "Long-Distance," which are essentially packages of strategy parameters with different preferences. In addition, the system can record the user's manual fine-tuning habits after automatic adjustment, and through long-term learning, gradually optimize the personalized support strategy for that user, achieving "the more you use it, the more considerate it becomes."

[0062] Step S30: Calculate the target parameters for lumbar support at the current moment based on the overall driving status and occupant posture.

[0063] Understandably, the ECU, as the core component, first integrates and analyzes all input data to identify the current overall driving state and occupant posture. Subsequently, it combines user-preset modes (from the interactive interface) and the built-in algorithm and strategy mapping table to calculate the most suitable target parameters for lumbar support at the current moment (such as airbag target pressure and lumbar support target position).

[0064] Step S40: Adjust the physical shape of the lumbar support according to the target parameters.

[0065] In this embodiment, the ECU's virtual commands are translated into actual changes in the lumbar support structure.

[0066] Please see Figure 3 Specifically, the actuator precisely adjusts the physical shape of the lumbar support. Simultaneously, a pressure sensor array continuously monitors the pressure changes after adjustment, generating feedback signals that are sent back to the ECU. The ECU compares the actual pressure distribution with the expected target; if there is a deviation, it fine-tunes the commands through a closed-loop control algorithm (such as PID) until the optimal support effect is achieved.

[0067] In this embodiment, multiple independent or zoned flexible airbags are built into the lumbar region of the seat back. The ECU controls a miniature air pump and a set of precision solenoid valves to change the support height, raised area, and firmness by inflating or deflating specific airbags. Its advantages are smooth movement, low noise, and the ability to achieve adjustable "surface support".

[0068] Furthermore, one or more linkage or push rod mechanisms driven by micro-motors are installed inside the seat back. The ECU controls the forward and reverse rotation and travel of the motors, pushing the lumbar support plate to adjust up and down, forward and backward, or in arc. Its advantages are fast response speed, strong support, and providing more resilient "point or line support".

[0069] It is understandable that combining the above two methods—for example, using an electric actuator for wide-range height and curvature adjustment, and using an airbag for fine-tuning of localized hardness and fit—can achieve the most precise support effect.

[0070] In this embodiment, it also includes: the user can switch vehicle modes or manually fine-tune the physical form of the lumbar support at any time through the interactive interface.

[0071] Specifically, users can switch vehicle modes (such as Comfort / Sport / Long Range) or manually fine-tune them at any time through the interactive interface. This operation is treated as a higher-priority command to the ECU, which responds immediately. Simultaneously, the ECU learns these manual preferences to optimize future automatic decisions under similar conditions.

[0072] In this embodiment, it typically consists of a set of physical buttons or virtual menus located on the side of the seat or on the central touchscreen. Key functions include: a mode selection switch (one-click switching of preset global strategies), manual fine-tuning controls (temporarily adjusting support position or intensity in automatic mode), and possible system switches and personalized profile storage / recall functions.

[0073] The intelligent lumbar support adjustment method provided by this invention acquires vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure; identifies the current overall driving state and occupant posture based on the electrical signals; calculates the target parameters for lumbar support at the current moment based on the overall driving state and occupant posture; and adjusts the physical form of the lumbar support according to the target parameters. This adjustment method fundamentally changes the "static" characteristic of seat lumbar support. During vehicle acceleration / braking, it provides immediate counter-support force to counteract the inertial pull on the lumbar spine; during cornering, it actively strengthens the support on the outer side of the curve to maintain spinal neutrality and reduce twisting; on bumpy roads, the rapid and flexible response of the support mechanism absorbs and buffers the impact energy transmitted to the lumbar spine. This effectively reduces the risk of intervertebral disc herniation or wear due to abnormal stress. Furthermore, it can identify sub-health states such as "slight fatigue during long-distance driving," automatically adjusting the support points and force to promote lumbar blood circulation and relieve static muscle load, thereby significantly improving comfort during long-term seating and combating fatigue. All adjustments are completed automatically, eliminating the need for the driver to search for and operate manual adjustment buttons, allowing them to remain focused on driving and improving driving safety. Furthermore, this method goes beyond static physical adjustments; through "mode selection" and "adaptive learning" functions, the same hardware can adapt to the personalized physiological needs of users with different body types and driving habits, achieving an evolution from a "universal seat" to a "personalized health cabin."

[0074] Please see Figure 4 The present invention also provides an intelligent lumbar support adjustment system. Figure 4 This is a schematic diagram of the structure of an intelligent lumbar support adjustment system provided in an embodiment of the present invention. It is applied to the intelligent lumbar support adjustment method provided in the above embodiment and specifically includes: a data acquisition unit, an identification unit, a calculation unit, and an execution unit.

[0075] The acquisition unit is used to acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure.

[0076] Specifically, to implement the above method, this embodiment adopts the following specific technical solution.

[0077] In this embodiment, a vehicle dynamic sensing unit is included, typically implemented by one or more inertial measurement units (IMUs). This unit is fixed to the vehicle chassis or a rigid body structure and continuously measures the vehicle's linear acceleration (for sensing rapid acceleration, deceleration, and impacts) and angular velocity (for sensing lateral and yaw motion during cornering and lane changes) in three directions. Essentially, it quantifies the vehicle's real-time motion attitude into processable data.

[0078] Furthermore, it also includes an occupant-seat interaction sensing unit: implemented by a high-resolution pressure sensor array embedded under the surface of the seat cushion and backrest. This array can accurately map the pressure distribution between the occupant's back and buttocks and the seat contact surface. By analyzing the map, the occupant's sitting posture (whether leaning forward, backward, or sideways), body center of gravity shift, and muscle tension can be inferred.

[0079] Furthermore, it also includes: obtaining information about the road ahead of the vehicle.

[0080] In this embodiment, a forward-looking road condition perception unit may also be included: this unit can integrate signal input from the vehicle's existing forward-facing camera or radar. This unit does not directly participate in support adjustment, but can provide early warning information such as "approaching a speed bump" or "uneven road surface ahead," allowing the decision-making module to prepare and adjust strategies in advance.

[0081] The identification unit is used to identify the current overall driving status and occupant posture based on the vehicle's physical signals.

[0082] Understandably, this unit is responsible for processing information, making judgments, and issuing instructions, and is usually implemented by a dedicated seat control electronic control unit (ECU).

[0083] In this embodiment, the ECU receives real-time data streams from all sensing modules. Through a built-in algorithmic model (e.g., a rule-based state machine or a lightweight machine learning model), the raw data is fused and interpreted into specific "driving scenarios" and "occupant states." For example, it identifies composite states such as "high-speed cornering," "continuous gravel road bumps," and "driver slightly fatigued and leaning to the right during long-distance driving."

[0084] Furthermore, the ECU pre-stores or learns and generates multiple support strategy mapping tables. These mapping tables define the target parameters (such as support point location, support strength, and support area) for lumbar support under different "scenario + state" combinations. During decision-making, the ECU matches or calculates the optimal support target parameters based on the currently identified state.

[0085] Furthermore, this ECU serves as the logical backend for the user interface. It stores user-selected preset modes such as "Comfort," "Sport," and "Long-Distance," which are essentially packages of strategy parameters with different preferences. In addition, the system can record the user's manual fine-tuning habits after automatic adjustment, and through long-term learning, gradually optimize the personalized support strategy for that user, achieving "the more you use it, the more considerate it becomes."

[0086] The calculation unit is used to calculate the target parameters of lumbar support at the current moment based on the overall driving status and occupant posture.

[0087] Understandably, the ECU, as the core component, first integrates and analyzes all input data to identify the current overall driving state and occupant posture. Subsequently, it combines user-preset modes (from the interactive interface) and the built-in algorithm and strategy mapping table to calculate the most suitable target parameters for lumbar support at the current moment (such as airbag target pressure and lumbar support target position).

[0088] An execution unit is used to adjust the physical shape of the lumbar support according to the target parameters.

[0089] In this embodiment, the ECU's virtual commands are translated into actual changes in the lumbar support structure.

[0090] Please see Figure 3 Specifically, the actuator precisely adjusts the physical shape of the lumbar support. Simultaneously, a pressure sensor array continuously monitors the pressure changes after adjustment, generating feedback signals that are sent back to the ECU. The ECU compares the actual pressure distribution with the expected target; if there is a deviation, it fine-tunes the commands through a closed-loop control algorithm (such as PID) until the optimal support effect is achieved.

[0091] In this embodiment, multiple independent or zoned flexible airbags are built into the lumbar region of the seat back. The ECU controls a miniature air pump and a set of precision solenoid valves to change the support height, raised area, and firmness by inflating or deflating specific airbags. Its advantages are smooth movement, low noise, and the ability to achieve adjustable "surface support".

[0092] Furthermore, one or more linkage or push rod mechanisms driven by micro-motors are installed inside the seat back. The ECU controls the forward and reverse rotation and travel of the motors, pushing the lumbar support plate to adjust up and down, forward and backward, or in arc. Its advantages are fast response speed, strong support, and providing more resilient "point or line support".

[0093] It is understandable that combining the above two methods—for example, using an electric actuator for wide-range height and curvature adjustment, and using an airbag for fine-tuning of localized hardness and fit—can achieve the most precise support effect.

[0094] The intelligent lumbar support adjustment system provided by this invention provides immediate counter-support force during vehicle acceleration / braking to counteract the inertial pull on the lumbar spine; during cornering, it actively strengthens support on the outer side of the curve to maintain spinal neutrality and reduce twisting; on bumpy roads, the rapid and flexible response of the support mechanism absorbs and buffers the impact energy transmitted to the lumbar spine. This effectively reduces the risk of intervertebral disc herniation or wear due to abnormal stress. It can also recognize sub-health states such as "slight fatigue during long-distance driving" and automatically adjust the support points and force to promote lumbar blood circulation and relieve static muscle load, thereby significantly improving comfort during long journeys and combating fatigue. All adjustments are completed automatically, eliminating the need for the driver to search for and operate manual adjustment buttons, allowing them to remain focused on driving and improving driving safety. Furthermore, this method transcends static physical adjustments; through "mode selection" and "adaptive learning" functions, the same hardware can adapt to the personalized physiological needs of users with different body types and driving habits, achieving an evolution from a "universal seat" to a "personal health cabin."

[0095] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the intelligent lumbar support adjustment methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0096] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0097] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0098] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0099] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the intelligent lumbar support adjustment methods described in the above embodiments. The computer-readable storage medium may be volatile or non-volatile.

[0100] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described intelligent lumbar support adjustment method.

[0101] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0102] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0103] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0104] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0105] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0106] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0107] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0108] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0109] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0110] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A method for intelligent lumbar support adjustment, characterized in that, It includes: Acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure; The current overall driving status and occupant posture are identified based on the vehicle's physical signals. The target parameters for lumbar support at the current moment are calculated based on the overall driving status and the occupant posture. Adjust the physical shape of the lumbar support according to the target parameters.

2. The intelligent lumbar support adjustment method according to claim 1, characterized in that, The steps for acquiring vehicle physical signals include: Obtain the linear acceleration and angular velocity of the vehicle in three directions; Obtain pressure distribution maps of the occupant's back and buttocks against the seat contact surface.

3. The intelligent lumbar support adjustment method according to claim 2, characterized in that, The step of acquiring vehicle physical signals also includes: acquiring road information ahead of the vehicle.

4. The intelligent lumbar support adjustment method according to claim 3, characterized in that, The step of identifying the current comprehensive driving state and occupant posture based on the vehicle physical signals includes: receiving the vehicle physical signals and interpreting the vehicle physical signals into specific current comprehensive driving state and occupant posture through a built-in algorithm model, wherein the algorithm model includes a rule-based state machine or a lightweight machine learning model.

5. The intelligent lumbar support adjustment method according to claim 4, characterized in that, The steps for calculating the target parameters for lumbar support at the current moment based on the overall driving conditions and occupant posture include: The system combines user-preset patterns or self-learning to generate multiple support strategy mapping tables. These mapping tables define the target parameters that the lumbar support should have under different scenarios and state combinations. Based on the currently identified state, the system matches or calculates to generate the optimal support target parameters, which include the support point location, support strength, and support area.

6. The intelligent lumbar support adjustment method according to claim 5, characterized in that, The step of adjusting the physical form of the lumbar support according to the target parameters includes: the actuator adjusting the physical form of the lumbar support; at the same time, continuously monitoring the pressure change after adjustment, generating a feedback signal and comparing the actual pressure distribution with the expected target. If there is a deviation, the instructions are fine-tuned through a closed-loop control algorithm until the best support effect is achieved.

7. The intelligent lumbar support adjustment method according to claim 1, characterized in that, Also includes: Users can switch vehicle modes or manually fine-tune the physical shape of the lumbar support at any time through the interactive interface.

8. An intelligent lumbar support adjustment system, characterized in that, include: The acquisition unit is used to acquire vehicle physical signals, including vehicle acceleration, angular velocity, and seat pressure. The identification unit is used to identify the current overall driving status and occupant posture based on the vehicle's physical signals; The calculation unit is used to calculate the target parameters of lumbar support at the current moment based on the overall driving status and occupant posture; An execution unit is used to adjust the physical shape of the lumbar support according to the target parameters.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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