Method for adjusting a zero-gravity seat within a vehicle, computing device, and vehicle

Abstract

The present application relates to a method for adjusting a seat in a vehicle, the seat being a zero-gravity seat having a sitting mode and a zero-gravity mode. The method comprises: obtaining user feature information of an occupant of the seat and seat mode information, adjusting a seat state of the seat to an initial state; obtaining seat feature data of the seat, obtaining vehicle static parameter information and vehicle dynamic parameter information of the vehicle; based on the user feature information, the vehicle static parameter information, the vehicle dynamic parameter information, the seat feature data, a damping coefficient and a stiffness coefficient, evaluating comfort of the seat; determining a first target damping coefficient that makes the comfort of the seat satisfy a predetermined comfort condition; and based on the first target damping coefficient, adjusting the seat state of the seat to a first target state. The present application can dynamically adjust the seat during vehicle driving, and objectively evaluate comfort through multi-dimensional input, thereby improving individual adaptability in the zero-gravity mode.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle technology, and more specifically, to a method, computing device, and vehicle for adjusting a zero-gravity seat inside a vehicle. Background Technology

[0002] Comfort has always been one of the most important factors for users when it comes to vehicles. As a crucial component of the entire vehicle, vehicle seats are subject to increasingly higher demands for comfort from occupants (including drivers and passengers). To improve comfort, more and more automakers are focusing on providing zero-gravity seats. Zero-gravity seats are designed by combining ergonomic design with the principles of zero gravity. Their purpose is to minimize pressure on the parts of the body that come into contact with the seat, or to distribute body pressure more evenly, thereby reducing discomfort when using the seat.

[0003] However, existing technologies for adjusting seats often only consider ideal sitting posture and static adjustment, and lack sufficient adaptability for adjusting zero-gravity seats. Summary of the Invention

[0004] To address the aforementioned deficiencies in the prior art, this invention provides a method for adjusting a vehicle seat, a computing device, a computer-readable storage medium, and a vehicle including the computing device. This invention dynamically adjusts the seat during vehicle operation and objectively evaluates comfort through multi-dimensional input, thereby improving personalized adaptability in zero-gravity postures.

[0005] According to a first aspect of the present invention, a method for adjusting a seat in a vehicle, the seat being a zero-gravity seat having a sitting posture mode and a zero-gravity posture mode, the method comprising: acquiring user characteristic information of a occupant of the seat, seat mode information, and seat characteristic data, the seat characteristic data including seat mass information, an initial damping coefficient, and an initial stiffness coefficient; adjusting the seat state to an initial state based on the user characteristic information and the seat mode information, wherein the seat state includes a damping coefficient, a stiffness coefficient, and seat position parameters; acquiring vehicle static parameter information and vehicle dynamic parameter information during a first time period during driving; when the vehicle is in motion and the seat is in the zero-gravity posture mode, performing the following steps: evaluating the comfort of the seat based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information during the first time period, the seat characteristic data, the damping coefficient, and the stiffness coefficient; determining a first target damping coefficient during the first time period that makes the comfort of the seat meet a predetermined comfort condition; and adjusting the seat state to the first target state based on the first target damping coefficient.

[0006] The method for adjusting a seat in a vehicle according to the first aspect described above may include, individually or in combination, any of the following preferred features.

[0007] Preferably, the user characteristic information includes the passenger's gender, age, and physical characteristics.

[0008] Preferably, the physical characteristics information includes upper body dimensions, lower body dimensions, shoulder width, hip width, and weight.

[0009] Preferably, adjusting the seat state to an initial state based on the user characteristic information and the seat mode information includes: determining a seat position parameter model based on the seat mode information; determining an initial seat position parameter based on the seat position parameter model and the user characteristic information; determining an initial damping coefficient based on the seat mode information; and adjusting the seat state to an initial state having the initial seat position parameter and the initial damping coefficient.

[0010] Preferably, the seat position parameters include at least one of the following: slide rail position, seat height, backrest position, and headrest position.

[0011] Preferably, evaluating the comfort of the seat based on the seat mode information, the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information, the seat characteristic data, the damping coefficient, and the stiffness coefficient includes: determining a dynamic model based on the seat mode information; determining model parameters for a user classification model based on the user characteristic information, wherein the user classification model is a classification model obtained by training, validating, and testing a dataset based on big data; establishing human body model data based on the dynamic model, the user classification model, the model parameters, and the user characteristic information, wherein the human body model data includes the mass, stiffness coefficient, and damping coefficient of each part of at least one part of the human body; calculating at least one root mean square value of acceleration corresponding to the at least one part of the human body based on the human body model data, the vehicle static parameter information, the vehicle dynamic parameter information, the seat characteristic data, the damping coefficient, and the stiffness coefficient; and generating the comfort level of the seat based on the at least one root mean square value of acceleration.

[0012] Preferably, the at least one root mean square value of acceleration includes two or more root mean square values ​​of acceleration, and generating the comfort level of the seat based on the at least one root mean square value of acceleration includes: generating the comfort level of the seat based on a weighted average of the two or more root mean square values ​​of acceleration.

[0013] Preferably, the at least one root mean square value of acceleration includes two or more root mean square values ​​of acceleration, and the comfort level of the seat is generated based on the at least one root mean square value of acceleration. Generating the comfort level of the seat includes: generating the comfort level of the seat based on a weighted average of the two or more root mean square values ​​of acceleration.

[0014] Preferably, the at least one part of the human body includes at least one of the following: head, upper body, internal organs, and lower body.

[0015] Preferably, the vehicle static parameter information includes vehicle mass, body rotational inertia, stiffness coefficient, and damping coefficient.

[0016] Preferably, the vehicle dynamic parameter information includes vehicle speed information, vertical acceleration information, and vertical vibration frequency information.

[0017] Preferably, determining a first target damping coefficient that makes the comfort of the seat meet a predetermined comfort condition during the first time period includes the following steps: A. Using an initial damping coefficient as the current damping coefficient, and using the comfort of the seat under the configuration of the initial damping coefficient as the current comfort; B. Adjusting the current damping coefficient in a first direction by a step length to generate a new damping coefficient; C. Evaluating the new comfort of the seat based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information, the seat characteristic data, the new damping coefficient, and the stiffness coefficient; D. If the iteration number is... If the number of times reaches the threshold, proceed to step E; otherwise, if the new comfort level is greater than the current comfort level, update the current damping coefficient to the new damping coefficient and the current comfort level to the new comfort level, and return to step B; if the new comfort level is less than the current comfort level, update the first direction to the opposite direction and return to step B; E. If the new comfort level is greater than the current comfort level, use the new damping coefficient as the first target damping coefficient and end the process, or if the new comfort level is less than the current comfort level, use the current damping coefficient as the first target damping coefficient and end the process.

[0018] Preferably, the method further includes: acquiring vehicle dynamic parameter information during a second time period while the vehicle is in motion; when the vehicle is in motion and the seat is in the zero-gravity posture mode, performing the following steps: evaluating the comfort of the seat based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information during the second time period, the seat characteristic data, the damping coefficient, and the stiffness coefficient; determining a second target damping coefficient during the second time period that makes the comfort of the seat meet a predetermined comfort condition; and adjusting the seat state to a second target state based on the second target damping coefficient.

[0019] Preferably, the comfort conditions include at least one of the following: the comfort of the seat exceeds the comfort of the seat in the configuration of the initial damping coefficient; the comfort of the seat exceeds a predetermined comfort threshold; the comfort of the seat has been adjusted a number of times according to the threshold.

[0020] Preferably, the method further includes: acquiring vehicle dynamic parameter information during a second time period while the vehicle is in motion; when the vehicle is in motion and the seat is in the zero-gravity posture mode, performing the following steps: evaluating the comfort of the seat based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information during the second time period, the seat characteristic data, the damping coefficient, and the stiffness coefficient; determining a second target damping coefficient during the second time period that makes the comfort of the seat meet a predetermined comfort condition; and adjusting the seat state to a second target state based on the second target damping coefficient.

[0021] Preferably, the comfort conditions include at least one of the following: the comfort of the seat exceeds the comfort of the seat in the configuration of the initial damping coefficient; the comfort of the seat exceeds a predetermined comfort threshold; the comfort of the seat has been adjusted a number of times according to the threshold.

[0022] According to a second aspect of the present invention, a computing device is provided, comprising: at least one processor; and a memory for storing computer-executable instructions that, when executed, cause the at least one processor to perform the method according to the aforementioned first aspect.

[0023] According to a third aspect of the present invention, a computer-readable storage medium is provided having computer-executable instructions stored thereon for performing the method according to the first aspect described above.

[0024] According to a fourth aspect of the invention, a vehicle is provided, including the computing device described in the preceding second aspect. Attached Figure Description

[0025] Other features and advantages of the invention will be better understood through the following detailed description of preferred embodiments in conjunction with the accompanying drawings, wherein the same reference numerals denote the same or similar parts.

[0026] Figure 1 A flowchart illustrating an exemplary method for adjusting a seat in a vehicle according to an embodiment of the present invention is shown.

[0027] Figure 2 An embodiment according to the present invention is shown. Figure 1An exemplary flowchart of how step 105 is implemented.

[0028] Figure 3 A block diagram of a computing device according to an embodiment of the present invention is shown. Detailed Implementation

[0029] In existing technologies, seat adjustments often only consider ideal sitting posture and static adjustment, and have few input dimensions and lack objective comfort assessment, thus lacking sufficient adaptability for zero-gravity seat adjustments.

[0030] As described below, some exemplary embodiments of this disclosure provide methods and vehicles for adjusting zero-gravity seats within a vehicle. More specifically, the seats are dynamically adjusted during vehicle operation, and comfort is objectively evaluated through multi-dimensional inputs, thereby improving personalized adaptability in zero-gravity postures.

[0031] refer to Figure 1 The diagram illustrates a block diagram 100 of an exemplary method for adjusting a seat in a vehicle according to an embodiment of the present invention, the seat being a zero-gravity seat having a sitting posture mode and a zero-gravity posture mode. Method 100 may be, for example, […]. Figure 3 The computing device 300 is used for implementation. Method 100 includes steps 101 to 106.

[0032] In step 101, user characteristic information of the seat occupant, seat mode information and seat characteristic data are obtained. The seat characteristic data includes seat mass information (Ws), original damping coefficient (C0) and original stiffness coefficient (K0).

[0033] For example, seat feature data can be obtained via the electronic control unit (ECU) through the body bus (e.g., CAN or other buses).

[0034] For example, seat mode information can be set to sitting mode or zero-gravity posture mode with a single button on the vehicle, or the seat mode can be set to sitting mode or zero-gravity posture mode through the vehicle's human-machine interface (HMI).

[0035] For example, user characteristic information includes the rider's gender (Ge), age (Ag), and physical characteristics. Further, physical characteristics include upper body dimensions (Lu), lower body dimensions (Ld), shoulder width (Ls), hip width (Lb), and weight (Wt). Including gender and age information in the user characteristic information allows for better differentiation modeling of the human body; for example, adults and children of the same weight should have different body models.

[0036] In some examples, user characteristics can be entered manually by the user.

[0037] In some examples, various body size information (e.g., upper body size, lower body size, shoulder width, hip width) can be obtained via visual sensors, and weight information can be obtained based on pressure sensors installed on or in the seat cushion, such as through an Occupant Classification System.

[0038] In some examples, image information of the seat occupant can be captured by optical systems such as cameras deployed within the cockpit system, thereby obtaining information such as the occupant's gender, age, and physical characteristics, without requiring user input.

[0039] In step 102, based on user characteristic information and seat mode information, the seat state is adjusted to the initial state, wherein the seat state includes damping coefficient, stiffness coefficient, and seat position parameters.

[0040] In some examples, step 102 may include: determining a seat position parameter model based on seat pattern information; determining initial seat position parameters based on the seat position parameter model and user feature information; determining an initial damping coefficient based on seat pattern information; and adjusting the seat state to an initial state with the initial seat position parameters and the initial damping coefficient.

[0041] In some examples, the seat position parameters include at least one of the following: slide rail position, seat height, backrest position, and headrest position.

[0042] For example, based on user characteristic information, a human body data matrix X = (Lu, Ld, Ls, Lb, Ge, Ag, Wt) can be obtained. T When the seat mode information indicates a sitting posture mode, the seat position parameter model M1 is obtained, thereby generating the seat position adjustment parameter matrix Y = M1 * X. For example, the seat adjustment model can be:

[0043] Y = (T,H,B,P) = M1*X

[0044] Where T represents the percentage of the adjusted seat rail position, H represents the percentage of the adjusted seat height, B represents the percentage of the adjusted seat back, P represents the percentage of the adjusted headrest position, and M1 represents the regression model trained on the dataset based on big data.

[0045] When the seat mode information indicates a sitting posture mode, the initial damping coefficient C0 of the seat can be, for example, the default damping coefficient C1 calibrated at the factory for the sitting posture mode.

[0046] Similarly, when the seat mode information indicates a zero-gravity posture mode, the seat position parameter model M2 is obtained, thereby generating the seat position adjustment parameter matrix Y = M2 * X. For example, the seat adjustment model can be:

[0047] Y = (T, H, B, P) = M² * X

[0048] When the seat mode information indicates the sitting posture mode, the initial damping coefficient C0 of the seat can be, for example, the damping coefficient C2 calibrated at the factory for the zero-gravity posture mode.

[0049] In some examples, adjusting the seat to its initial state may include sending determined initial seat position parameters, initial damping coefficients, and initial stiffness coefficients to a controller that controls the seat (e.g., via the vehicle bus), causing the controller to adjust the seat rails, backrest, height, headrest, and dampers. The dampers may be, for example, air dampers, magnetorheological dampers, or electrical dampers. Furthermore, one or more dampers may be placed at various points on the seat (e.g., headrest, backrest, seat cushion) to improve damping and thus enhance comfort.

[0050] In step 103, the vehicle's static parameter information and the vehicle's dynamic parameter information during the first time period of driving are obtained.

[0051] For example, vehicle static information may include vehicle mass (Wv), body moment of inertia (Jv), suspension stiffness coefficient (Kv), and suspension damping coefficient (Cv). For example, vehicle static information can be obtained through vehicle calibration.

[0052] For example, vehicle dynamic parameter information may include vehicle speed (Vs), vertical acceleration (Av), and vertical vibration frequency (Fv). For instance, vehicle speed information can be obtained via the body bus (e.g., CAN or other buses) through the ECU (e.g., the vehicle ECU), and vertical acceleration and its rate of change, as well as vertical vibration frequency and its rate of change, can be obtained via vibration sensors installed under the seat. Vehicle dynamic parameter information can reflect driving conditions; for example, due to road bumps, vibrations from the ground are transmitted to the occupant through the seat, affecting their comfort. Adjusting the seat's damping coefficient can, for example, achieve shock absorption to improve occupant comfort.

[0053] In step 104, when the vehicle is in motion and the seat is in the zero-gravity posture mode, the following steps are performed: The comfort of the seat is evaluated based on user characteristic information, vehicle static parameter information, vehicle dynamic parameter information during the first time period, seat characteristic data, damping coefficient, and stiffness coefficient. In this step, through multi-dimensional input, comfort can be fully calculated and objectively evaluated from more perspectives (such as gender, age, etc.).

[0054] In some examples, step 104 may include: determining a dynamic model based on seat pattern information; determining model parameters for a user classification model based on user characteristic information, wherein the user classification model is a classification model obtained by training, validating, and testing a dataset based on big data; establishing human body model data based on the user classification model, model parameters, and user characteristic information, wherein the human body model data includes the mass, stiffness coefficient, and damping coefficient of each part of at least one part of the human body; calculating at least one root mean square value of acceleration corresponding to at least one part of the human body based on the dynamic model, human body model data, vehicle static parameter information, vehicle dynamic parameter information, seat characteristic data, damping coefficient, and stiffness coefficient; and generating the comfort of the seat based on the at least one root mean square value of acceleration.

[0055] For example, the dynamic model Dm=(Dm1,Dm2) T Select the seating position indicated by the seat configuration mode information.

[0056] For example, a four-degree-of-freedom human body model can be built using the acquired anthropometric data, gender, and age information of the occupant. The calculation formula is as follows:

[0057] Y2 = CM * X2

[0058] Where CM = (CM1, CM2, CM3) T This is a classification model that can automatically select different model parameters based on different body features, gender, and age group. CM1 is the size model, CM2 is the gender model, and CM3 is the age model. The human body data matrix X2 = (Lu, Ld, Ls, Lb, Ge, Ag, Wt). T To obtain user characteristic information of the passengers.

[0059]

[0060] Y2 is the output four-degree-of-freedom linear human body model consisting of the head, upper torso, internal organs, and lower torso, including the mass (m1, m2, m3, m4), stiffness coefficient (k1, k2, k3, k4), and damping coefficient (c1, c2, c3, c4) of each part.

[0061] The acceleration response of different parts of the human body is analyzed, and the response formula is as follows:

[0062] (Vs, Av, Fv, Cs) T

[0063] Where X = (Vs, Av, Fv, Cs) TTo obtain vehicle dynamic parameters and seat suspension damping coefficients; Y = (ah, ab, ai, al) T Let S be the root mean square matrix of accelerations for each degree of freedom (e.g., head, upper torso, internal organs, and lower torso); S = (ms, C0, K0) T The initial parameter matrix for the seat includes seat mass, initial damping, and initial stiffness; V = (mv, Jv, Kv, Cv) T Y1 represents the vehicle's static parameter matrix; Y2 represents the four-degree-of-freedom human body model data calculated above.

[0064] For example, based on Y = (ah, ab, ai, al) T By applying weights, comfort can be calculated as follows:

[0065]

[0066] Among them, w1 to w4 are weighting coefficients, and their sum is 1.

[0067] For example, weighting can be selectively applied to highlight the importance of the comfort of a specific part among multiple parts to the overall comfort. For example, when you want to primarily assess head comfort, you can set w1 to the largest coefficient (e.g., 1). For example, when you want to ignore head comfort, you can set w1 to the smallest coefficient (e.g., 0).

[0068] In some examples, comfort values ​​can be categorized according to the table below.

[0069] Sa(m / C2) Subjective feelings Comfort <SaO No discomfort 1 Sa1~Sa2 Slight discomfort 0.8 Sa3~Sa4 Some discomfort 0.6 Sa5~Sa6 discomfort 0.4 Sa7~Sa8 Very uncomfortable 0.2 >Sa9 Extremely uncomfortable 0

[0070] Table 1: Comfort Classification

[0071] For example, as shown in Table 1, comfort level Sa can be divided into different comfort levels according to intervals. By adjusting the seat suspension damping, a new comfort level can be obtained. Comparing the new comfort level with the initial comfort level determines whether the comfort level has increased. If it has increased, it indicates that the comfort level has improved. In some examples, the calculated comfort level Sa can also be directly used as the comfort level.

[0072] In step 105, a first target damping coefficient is determined during the first time period to ensure that the comfort of the seat meets the predetermined comfort conditions.

[0073] In step 106, based on the first target damping coefficient, the seat state is adjusted to the first target state.

[0074] In some examples, the seat's position is adjusted to a first target state based on a first target damping coefficient. Similarly, as previously described, adjusting the seat's position to the first target state may include sending the determined first target damping coefficient to a controller that controls the seat (e.g., via a vehicle bus) so that the controller adjusts the seat's rails, backrest, height, headrest, and dampers.

[0075] Compared with existing technologies, method 100 can dynamically adjust the damping coefficient of the seat based on the influence of vehicle dynamic parameter information on the zero-gravity seat during vehicle operation, so as to increase the comfort of the zero-gravity posture.

[0076] Figure 2 An embodiment according to the present invention is shown. Figure 1 An exemplary flowchart of an exemplary implementation of step 105, 200. Implementation 200 includes steps 201 to 204.

[0077] In step 201, the initial damping coefficient is used as the current damping coefficient, and the seat comfort under the configuration of the initial damping coefficient is used as the current comfort. The current damping coefficient is adjusted or updated in the first direction (e.g., with a step length) to generate a new damping coefficient.

[0078] In step 202, the acceleration response of various parts of the human body is analyzed based on the new damping coefficient to evaluate the new comfort of the seat.

[0079] In step 203, the new comfort level is compared with the current comfort level to assess whether the comfort level has changed.

[0080] If the new comfort level is greater than the current comfort level at step 203, return to step 201, use the current damping coefficient as the new damping coefficient and the current comfort level as the new comfort level, and continue to adjust or update the damping coefficient in the first direction.

[0081] If the new comfort level at step 203 is less than the current comfort level, proceed to step 204, return to the previous damping coefficient, and adjust the update direction from the first direction to the opposite direction. Then, return to step 201 and continue adjusting or updating the previous damping coefficient in the updated first direction.

[0082] In some examples, a threshold number of iterations can be set so that the adjustment or update of the damping coefficient is terminated when the adjustment process iterates to the threshold number of iterations.

[0083] In some examples, the process can be terminated when the adjustment process iterates to reach a locally optimal level of comfort, and the last damping coefficient can be determined as the target damping coefficient or the optimal damping coefficient.

[0084] In some examples, the damping coefficient can be initially adjusted with a first step size, and then adjusted with a second step size after the approximation direction of the damping coefficient is determined. The second step size can be smaller than the first step size in order to more finely adjust the damping coefficient to the target damping coefficient that meets the comfort conditions.

[0085] Figure 3 A schematic diagram of a computing device 300 according to an embodiment of the present invention is shown. The computing device 300 includes at least one processor 310 and a memory 320 coupled to the processor 310. The memory 320 is used to store computer-executable instructions that, when executed, cause the processor 310 to perform the methods described in the above embodiments (e.g., any one or more steps of the foregoing method 100 or implementation 200).

[0086] In some examples, processor 310 may be an onboard ECU that controls or communicates with components used to adjust the seat (e.g., slide rails, headrests, backrests, suspension, dampers, etc.) so that processor 310 can adjust the state of the seat based on determined seat position parameters, damping coefficients, and stiffness coefficients.

[0087] Alternatively, the above methods can be implemented using a computer-readable storage medium. The computer-readable storage medium carries computer-readable program instructions for executing the various embodiments of this disclosure. The computer-readable storage medium can be a tangible device capable of holding and storing instructions used by an instruction execution device. The computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combinations thereof. The computer-readable storage medium used herein is not to be interpreted as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0088] Therefore, in another embodiment, this disclosure provides a computer-readable storage medium having computer-executable instructions stored thereon for performing the methods of various embodiments of this disclosure.

[0089] It should be noted that the present invention (e.g., inventive concepts, etc.) has been described in the specification of this patent document and / or illustrated in the figures according to exemplary embodiments; embodiments of the present invention are presented by way of example only and are not intended to limit the scope of the invention. The structure and / or arrangement of elements of the inventive concept embodied in the present invention as described in the specification and / or illustrated in the figures are merely illustrative. Although exemplary embodiments of the present invention have been described in detail in this patent document, it will be readily understood by those skilled in the art that equivalents, modifications, variations, etc., of the subject matter of the exemplary and alternative embodiments are possible and are considered to be within the scope of the present invention; all such subject matter (e.g., modifications, variations, embodiments, combinations, equivalents, etc.) are intended to be included within the scope of the present invention. It should also be noted that various modifications, variations, substitutions, equivalents, alterations, omissions, etc., may be made in the configuration and / or arrangement of exemplary embodiments (e.g., in terms of concept, design, structure, device, form, assembly, construction, means, function, system, process / method, steps, sequence of process / method steps, operation, operating conditions, performance, materials, composition, combination, etc.) without departing from the scope of the invention; all such subject matter (e.g., modifications, variations, embodiments, combinations, equivalents, etc.) is intended to be included within the scope of the invention. The scope of the invention is not intended to be limited to the subject matter described in the specification and / or figures of this patent document (e.g., details, structure, function, materials, behavior, steps, sequence, system, result, etc.). Considering that the claims of this patent document will be properly interpreted to cover the full scope of the subject matter of the invention (e.g., including any and all such modifications, variations, embodiments, combinations, equivalents, etc.); it should be understood that the terminology used in this patent document is for the purpose of providing a description of the subject matter of exemplary embodiments and not as a limitation on the scope of the invention.

[0090] It should also be noted that, according to exemplary embodiments, the present invention may include conventional techniques (e.g., techniques implemented and / or integrated in exemplary embodiments, modifications, variations, combinations, equivalents, etc.), or may include any other applicable techniques (now and / or in the future) with the ability to perform the functions and processes / operations described in the specification and / or illustrated in the figures. All such techniques (e.g., techniques implemented in the manner of embodiments, modifications, variations, combinations, equivalents, etc.) are considered to be within the scope of the present invention of this patent document.

Claims

1. A method for adjusting a seat in a vehicle, said seat being a zero-gravity seat having a sitting posture mode and a zero-gravity posture mode, the method comprising: The user characteristic information, seat mode information, and seat characteristic data of the occupant of the seat are obtained. The seat characteristic data includes seat mass information, original damping coefficient, and original stiffness coefficient. Based on the user characteristic information and the seat mode information, the seat state is adjusted to the initial state, wherein the seat state includes damping coefficient, stiffness coefficient, and seat position parameters; Obtain the vehicle's static parameter information and the vehicle's dynamic parameter information during the first time period of the driving process; When the vehicle is in motion and the seat is in the zero-gravity posture mode, the following steps are performed: The comfort of the seat is evaluated based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information during the first time period, the seat characteristic data, the damping coefficient, and the stiffness coefficient; and Determine a first target damping coefficient during the first time period that makes the comfort level of the seat meet a predetermined comfort condition; and Based on the first target damping coefficient, the seat state is adjusted to the first target state.

2. The method according to claim 1, wherein, The user characteristic information includes the passenger's gender, age, and physical characteristics.

3. The method according to claim 2, wherein, The physical characteristics information includes upper body dimensions, lower body dimensions, shoulder width, hip width, and weight.

4. The method according to claim 2, wherein, Adjusting the seat state to its initial state based on the user characteristic information and the seat mode information includes: Based on the seat mode information, determine the seat position parameter model; Based on the seat position parameter model and the user feature information, the initial seat position parameters of the seat are determined; Based on the seat mode information, determine the initial damping coefficient; The seat is adjusted to an initial state with the initial seat position parameters and the initial damping coefficient.

5. The method according to claim 1, wherein, The seat position parameters include at least one of the following: slide rail position, seat height, backrest position, and headrest position.

6. The method according to claim 1 or 2, wherein, The comfort of the seat is evaluated based on the seat mode information, user characteristic information, vehicle static parameter information, vehicle dynamic parameter information, seat characteristic data, damping coefficient, and stiffness coefficient, including: Based on the seat mode information, a dynamic model is determined; Based on the user feature information, model parameters are determined for the user classification model, which is a classification model obtained by training, validating and testing a dataset based on big data. Based on the user classification model, the model parameters, and the user feature information, human body model data is established, wherein the human body model data includes the mass, stiffness coefficient, and damping coefficient of each part of at least one part of the human body. Based on the dynamic model, the human body model data, the vehicle static parameter information, the vehicle dynamic parameter information, the seat feature data, the damping coefficient, and the stiffness coefficient, calculate at least one root mean square value of acceleration corresponding to at least one part of the human body; The comfort level of the seat is generated based on the at least one root mean square value of acceleration.

7. The method according to claim 6, wherein, The at least one root mean square acceleration value includes two or more root mean square acceleration values, and Generating the comfort level of the seat based on the at least one root mean square value of acceleration includes: generating the comfort level of the seat by weighting two or more root mean square values ​​of acceleration.

8. The method according to claim 6, wherein, The at least one part of the human body includes at least one of the following: head, upper body, internal organs, and lower body.

9. The method according to claim 1, wherein, The vehicle static parameter information includes vehicle mass, body rotational inertia, suspension stiffness coefficient, and suspension damping coefficient.

10. The method according to claim 1, wherein, The vehicle dynamic parameter information includes vehicle speed information, vertical acceleration information, and vertical vibration frequency information.

11. The method according to claim 1, wherein, Determining a first target damping coefficient that makes the seat's comfort meet predetermined comfort conditions during the first time period includes the following steps: A. Use the initial damping coefficient as the current damping coefficient, and use the comfort level of the seat under the configuration of the initial damping coefficient as the current comfort level; B, adjust the current damping coefficient in the first direction to generate a new damping coefficient; C. Based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information, the seat characteristic data, the new damping coefficient, and the stiffness coefficient, evaluate the new comfort level of the seat; D. If the number of adjustments reaches the threshold, proceed to step E; otherwise... If the new comfort level is greater than the current comfort level, then update the current damping coefficient to the new damping coefficient and update the current comfort level to the new comfort level, then return to step B; If the new comfort level is less than the current comfort level, then update the first direction to the opposite direction and return to step B; E. If the new comfort level is greater than the current comfort level, then the new damping coefficient is used as the first target damping coefficient, and the process ends, or If the new comfort level is less than the current comfort level, then the current damping coefficient is used as the first target damping coefficient, and the process ends.

12. The method according to claim 1, further comprising: Obtain vehicle dynamic parameter information during the second time period of the vehicle's operation; When the vehicle is in motion and the seat is in the zero-gravity posture mode, the following steps are performed: The comfort of the seat is evaluated based on the user characteristic information, the vehicle static parameter information, the vehicle dynamic parameter information in the second time period, the seat characteristic data, the damping coefficient, and the stiffness coefficient. as well as During the second time period, a second target damping coefficient is determined to ensure that the comfort of the seat meets a predetermined comfort condition; as well as Based on the second target damping coefficient, the seat state is adjusted to the second target state.

13. The method according to claim 1, wherein, The comfort conditions include at least one of the following: The comfort level of the seat exceeds that of the seat in the configuration with the initial damping coefficient; The comfort level of the seat exceeds a predetermined comfort threshold; The comfort level of the seat was adjusted a threshold number of times.

14. A computing device, comprising: At least one processor; as well as A memory for storing computer-executable instructions that, when executed, cause the at least one processor to perform the method according to any one of claims 1-13.

15. A computer-readable storage medium having computer-executable instructions stored thereon for performing the method according to any one of claims 1-13.

16. A vehicle comprising the computing device according to claim 14.

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