Self-learning calibration method for seat motor, related equipment and vehicle

Abstract

This invention provides a self-learning calibration method, related equipment, and vehicle for a seat motor. The method includes: driving the seat motor of a target seat to rotate in a preset learning direction according to a folding command until the seat motor stalls; determining a first stop point of the seat motor rotor when the seat motor stalls; determining whether the distance between the first stop point and a desired stop point is less than a preset Hall distance; wherein the desired stop point is a pre-calibrated stop point of the seat motor rotor in the preset learning direction; and updating the desired stop point to the first stop point in response to the distance between the first stop point and the desired stop point being less than the preset Hall distance; wherein the first stop point represents the stop point of the seat motor's next rotation in the preset learning direction.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to a self-learning calibration method for a seat motor, related equipment, and a vehicle. Background Technology

[0002] With the rapid development of the automotive industry and the continuous advancement of intelligent technologies, automobiles have become an indispensable means of transportation in modern life. Among them, seat memory function, as an important feature to improve driving comfort and convenience, is widely used in various types of vehicles.

[0003] However, in the current position learning method for realizing seat memory function, the Hall sensor of the seat motor may be inaccurate in counting due to premature shutdown or reverse rotation of the seat motor. This, to some extent, restricts the accuracy of seat adjustment and its self-learning. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in related technologies. To this end, the first objective of this invention is to propose a self-learning calibration method for a seat motor, which solves the problem of inaccurate Hall sensor counting in the seat motor by continuously calibrating the stop point of the seat motor, effectively improving the accuracy of seat adjustment and its self-learning.

[0005] The second objective of this invention is to provide a self-learning calibration device for a seat motor.

[0006] The third objective of this invention is to provide an electronic device.

[0007] The fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0008] The fifth objective of this invention is to provide a seat motor.

[0009] The sixth objective of this invention is to provide a vehicle.

[0010] To achieve the above objectives, a first aspect of the present invention provides a self-learning calibration method for a seat motor, the method comprising:

[0011] The seat motor of the target seat is driven to rotate in the preset learning direction according to the folding command until the seat motor stalls.

[0012] Determine the first stopping point of the seat motor rotor when the seat motor stalls;

[0013] Determine whether the distance between the first stop point and the desired stop point is less than the preset Hall distance; wherein, the desired stop point is the stop point pre-calibrated by the rotor of the seat motor in the preset learning direction;

[0014] In response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, the desired stop point is updated to the first stop point; wherein, the first stop point represents the stop point at which the seat motor will next rotate in the preset learning direction.

[0015] In addition, the self-learning calibration method for the seat motor in the above embodiments of the present invention may also have the following additional technical features:

[0016] Optionally, before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes:

[0017] In response to receiving a folding command, determine whether the target seat meets the folding conditions;

[0018] In response to the target seat meeting the folding conditions, the seat motor of the target seat is controlled to rotate in the preset learning direction according to the folding command.

[0019] Optionally, determine whether the target seat meets the folding conditions, including:

[0020] Determine if the target seat is occupied;

[0021] In response to the target seat being occupied, it is determined that the target seat does not meet the folding condition.

[0022] Optionally, determining whether the target seat meets the folding requirements also includes:

[0023] Determine whether there are any obstacles within the range of motion of the target seat as it rotates in the preset learning direction;

[0024] If an obstacle exists within the travel range of the target seat when it rotates in the preset learning direction, it is determined that the target seat does not meet the folding condition.

[0025] Optionally, the obstacle may include other seats, and the method may further include:

[0026] In response to other seats blocking the target seat's travel range toward the preset learning direction, the other seats are adjusted to move them away from the travel range.

[0027] Optionally, before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes:

[0028] Determine whether the engine used to drive the seat motor is running, and determine whether the seat motor has a stored desired stop point;

[0029] In response to the engine being started and the seat motor storing the desired stop point, the seat motor driving the target seat is determined to rotate in the preset learning direction.

[0030] Optionally, the method further includes:

[0031] Record the number of the first Hall pulses output by the seat motor from the moment of startup to the moment when the seat motor stalls;

[0032] The first Hall pulse count is converted into the first Hall value according to a preset ratio.

[0033] Optionally, determining whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance includes:

[0034] Calculate the difference between the first Hall value and the preset Hall value corresponding to the desired stopping point, which is the Hall distance;

[0035] Determine whether the difference Hall distance is less than the preset Hall distance.

[0036] Optionally, the method further includes:

[0037] In response to the fact that the distance between the first stop point and the desired stop point is not less than the preset Hall distance, it is determined whether the number of times the seat motor stalls within the preset time interval reaches the preset number threshold.

[0038] In response to the number of times the seat motor stalls within a preset time interval reaching a preset threshold, the second stop point when the seat motor stalls for the last time is determined;

[0039] The desired stopping point is updated to the second stopping point; where the second stopping point represents the stopping point of the seat motor when it rotates in the preset learning direction next.

[0040] Optionally, determine the second stop point when the seat motor last stalled, including:

[0041] Record the number of second Hall pulses output by the seat motor from the start-up moment to the last time the seat motor stalls;

[0042] The second stop point is determined based on the second Hall pulse count.

[0043] According to the self-learning calibration method of the seat motor of the present invention, the seat motor of the target seat is first driven to rotate in a preset learning direction according to the folding command until the seat motor stalls. Further, a first stop point of the rotor of the seat motor when stalling occurs is determined, and it is determined whether the distance between the first stop point and the desired stop point is less than a preset Hall distance. The desired stop point is a pre-calibrated stop point of the rotor of the seat motor in the preset learning direction. In response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, the desired stop point is updated to the first stop point. The first stop point represents the stop point of the seat motor's next rotation in the preset learning direction. This invention solves the problem of inaccurate Hall sensor counting in the seat motor by continuously calibrating the stop point of the seat motor, effectively improving the accuracy of seat adjustment and its self-learning.

[0044] To achieve the above objectives, a second aspect of the present invention provides a self-learning calibration device for a seat motor, the device comprising:

[0045] The control module is configured to drive the seat motor of the target seat to rotate in a preset learning direction according to the folding command until the seat motor stalls.

[0046] The first determining module is configured to determine the first stop point of the seat motor rotor when the seat motor stalls;

[0047] The second determining module is configured to determine whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance; wherein, the desired stopping point is the stopping point of the rotor of the seat motor pre-calibrated in a preset learning direction;

[0048] The calibration module is configured to update the desired stop point to the first stop point in response to the distance between the first stop point and the desired stop point being less than a preset Hall distance; wherein the first stop point represents the stop point at which the seat motor will next rotate in the preset learning direction.

[0049] According to an embodiment of the present invention, a self-learning calibration device for a seat motor first drives the seat motor of the target seat to rotate in a preset learning direction according to a folding command via a control module until the seat motor stalls. Further, a first determining module determines the first stop point of the seat motor rotor when the seat motor stalls, and a second determining module determines whether the distance between the first stop point and the desired stop point is less than a preset Hall distance. The desired stop point is a pre-calibrated stop point of the seat motor rotor in the preset learning direction. Finally, in response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, a calibration module updates the desired stop point to the first stop point. The first stop point represents the stop point of the seat motor's next rotation in the preset learning direction. This invention solves the problem of inaccurate Hall sensor counting in the seat motor by continuously calibrating the stop point of the seat motor, effectively improving the accuracy of seat adjustment and its self-learning.

[0050] To achieve the above objectives, a third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the self-learning calibration method for the seat motor as described above. By continuously calibrating the stop point of the seat motor, the problem of inaccurate counting by the Hall sensor of the seat motor is solved, effectively improving the accuracy of seat adjustment and its self-learning.

[0051] To achieve the above objectives, a fourth aspect of the present invention provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the self-learning calibration method for the seat motor described above. By continuously calibrating the stop point of the seat motor, the inaccurate counting of the Hall sensor of the seat motor is solved, effectively improving the accuracy of seat adjustment and its self-learning.

[0052] To achieve the above objectives, a seat motor is provided in a fifth aspect embodiment of the present invention, the seat motor including the electronic equipment as described above.

[0053] To achieve the above objectives, a vehicle is provided in a sixth aspect of the present invention, the vehicle including a seat motor as described above.

[0054] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a schematic diagram of the self-learning calibration method for a seat motor provided in an embodiment of the present invention.

[0057] Figure 2 This is a schematic diagram of a target seat folding application scenario provided by an embodiment of the present invention.

[0058] Figure 3 This is a schematic diagram of the seat motor reversing according to an embodiment of the present invention.

[0059] Figure 4 Another schematic diagram showing the seat motor reversing according to an embodiment of the present invention.

[0060] Figure 5 A side view showing the step difference generated in the target seat according to an embodiment of the present invention.

[0061] Figure 6 A top view showing the step difference generated by the target seat in an embodiment of the present invention.

[0062] Figure 7 This is a schematic diagram of the overall process of the self-learning calibration method for a seat motor provided in an embodiment of the present invention.

[0063] Figure 8 This is a schematic diagram of a self-learning calibration device for a seat motor provided in an embodiment of the present invention.

[0064] Figure 9 This is a schematic diagram of a more specific electronic device hardware structure provided for an embodiment of the present invention.

[0065] Figure 10 A schematic diagram of a seat motor provided for an embodiment of the present invention.

[0066] Figure 11 This is a schematic diagram of a vehicle provided for an embodiment of the present invention. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0068] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0069] As described in the background section, with the rapid development of the automotive industry and the continuous advancement of intelligent technology, automobiles have become an indispensable means of transportation in modern life. Among them, vehicle seat memory function, as an important feature to improve driving comfort and convenience, is widely used in various types of vehicles.

[0070] In the process of developing this invention, the applicant discovered that existing vehicle seat learning technologies suffer from problems such as incomplete seat movement, step differences, and seat position misalignment. These problems mainly arise from three aspects: First, the large amount of foam interference in the third-row seats prevents the rear-deployed seats from accurately positioning, resulting in step differences. Second, the Hall effect interruption acquisition time after the motor stops is too short, potentially causing missed Hall signals during large motor braking strokes. Repeated folding and unfolding accumulates errors, causing the seat position to gradually shift backward. Finally, the third-row seat motor lacks a self-locking function. During the stop-drive process, the reverse resistance of the foam after the backrest is folded may cause the motor to reverse, generating a reverse Hall waveform. This leads to the module miscounting Hall numbers, while the actual seat travel shifts upward. These issues all involve deviations in Hall sensor counting during vehicle seat adjustment and memory learning, which can be understood as a "Hall effect drift phenomenon."

[0071] Therefore, this invention provides a self-learning calibration method, related equipment, and vehicle for a seat motor. First, the seat motor of the target seat is driven to rotate in a preset learning direction according to a folding command until the seat motor stalls. Further, a first stop point of the seat motor rotor when stalling occurs is determined, and it is determined whether the distance between the first stop point and a desired stop point is less than a preset Hall distance. The desired stop point is a pre-calibrated stop point of the seat motor rotor in the preset learning direction. In response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, the desired stop point is updated to the first stop point. The first stop point represents the stop point of the seat motor's next rotation in the preset learning direction. This invention solves the problem of inaccurate Hall sensor counting in the seat motor by continuously calibrating the stop point of the seat motor, effectively improving the accuracy of seat adjustment and its self-learning.

[0072] The following describes a self-learning calibration method for a seat motor according to an exemplary embodiment of the present invention, using specific application scenarios. It should be noted that the above application scenarios are shown only to facilitate understanding of the spirit and principles of the present invention, and the embodiments of the present invention are not limited in any way. Rather, the embodiments of the present invention can be applied to any applicable scenario.

[0073] refer to Figure 1 This is a schematic diagram of the self-learning calibration method for a seat motor provided in an embodiment of the present invention.

[0074] Step S102: Drive the seat motor of the target seat to rotate in the preset learning direction according to the folding command until the seat motor stalls;

[0075] Step S104: Determine the first stop point of the seat motor rotor when the seat motor stalls;

[0076] Step S106: Determine whether the distance between the first stop point and the desired stop point is less than the preset Hall distance; wherein, the desired stop point is the stop point pre-calibrated by the rotor of the seat motor in the preset learning direction;

[0077] Step S108: In response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, the desired stop point is updated to the first stop point; wherein, the first stop point represents the stop point at which the seat motor will next rotate in the preset learning direction.

[0078] refer to Figure 2 This is a schematic diagram of a target seat folding application scenario provided in an embodiment of the present invention.

[0079] First, seat foam interference refers to the physical contact or conflict between the seat foam material (usually polyurethane foam) and the seat frame, other components, or surrounding space during seat folding, unfolding, or adjustment. This interference may cause the seat to fail to reach its intended position accurately, resulting in a step difference, affecting the flatness and aesthetics of the seat, and may even lead to seat malfunction.

[0080] Seat memory function relies on a built-in memory chip to store and retrieve user-set seat positions and angles. However, if the seat is affected by foam interference during adjustment, it may not accurately reach the preset position. Contact or friction between the foam material and the seat frame or other components can obstruct seat movement, resulting in positional deviation. This deviation directly affects the accuracy of the seat memory function, preventing the seat from returning to the user's desired position. To address this issue, the size, shape, and installation location of the foam material can be optimized to reduce interference between the foam and the seat frame or other components. Improving the assembly precision of each seat component, ensuring reasonable clearances between parts, and avoiding interference problems caused by assembly errors can also help.

[0081] Furthermore, if the Hall effect interruption time is set too short after the motor stops, Hall effect signals may be missed when the motor braking stroke is large. Hall effect signals are crucial for motor position and speed control; missed signals prevent the control system from accurately determining the motor's actual position. After multiple repositioning operations, this error accumulates, eventually causing the seat position to gradually shift backward, affecting the seat's accuracy and stability. To address this issue, the Hall effect interruption time after the motor stops can be appropriately increased to ensure accurate acquisition of all Hall effect signals even during large motor braking strokes. Filtering and noise reduction of the acquired Hall effect signals can also improve their accuracy and reliability. Alternatively, algorithm optimization can be used to perform real-time analysis and processing of the signals, ensuring accurate calculation of the motor's position and speed.

[0082] If the seat motor lacks a self-locking function (such as in the third-row seats of a vehicle) during the stopping process, it may reverse due to the reverse resistance of the foam generated after the backrest is folded. This reversal generates a reverse Hall effect waveform, causing the Hall sensor to miscount, while the actual seat travel shifts upwards. This problem not only affects the accuracy and stability of the seat but may also damage the motor and control system.

[0083] refer to Figure 3 This is a schematic diagram of the seat motor reversing according to an embodiment of the present invention.

[0084] In some cases, if the number of poles in the seat motor and the layout of the Hall sensor are properly designed, reversing the rotation may not change the number of times the Hall sensor passes through the magnetic poles (i.e., the Hall number). The Hall number remains unchanged, and the seat motor position reverses from position P1 to position P2. This is because the Hall sensor detects changes in the magnetic field, and the magnetic field may pass through the Hall sensor in the same way when the seat motor rotates forward and backward. However, although the Hall number may remain unchanged, the actual travel of the seat motor (i.e., the distance or position of rotation of the seat motor shaft) will change due to reversal. This is because the travel is calculated based on the direction of rotation of the seat motor and the accumulated Hall signal. Reversal means that the direction of movement of the seat motor shaft is reversed, so even if the Hall number is the same, the final position of the seat motor shaft will be different.

[0085] refer to Figure 4 This is another schematic diagram of the seat motor reversing according to an embodiment of the present invention.

[0086] In some seat motor and Hall sensor configurations, reversal can cause changes in the Hall signal. The Hall count changes as the seat motor position reverses from P1 to P3 (recording an increase in the Hall count, crossing the P2 position). This could be because the direction of the magnetic field changes during reversal, causing the Hall sensor to detect a different signal sequence. If the change in the Hall signal does not match the expected sequence (e.g., signal inversion due to reversal), the control system may incorrectly record additional Hall signals. This could be because the control system encounters difficulties in interpreting the Hall signal, thus misidentifying the additional signal change. Due to the change in the Hall signal and potential erroneous recording, the seat motor's travel calculation can also be affected. This can lead the control system to misunderstand the actual position of the seat motor, thus affecting the seat motor's performance and positioning accuracy.

[0087] refer to Figure 5 This is a side view showing the step difference generated in the target seat according to an embodiment of the present invention. (See reference...) Figure 6 This is a top view showing the step difference in the target seat provided in this embodiment of the invention. Because the left and right seats of the vehicle generate step differences due to the aforementioned reasons after executing different folding and lifting commands, the cumulative effect causes the backrests of the left and right seats to become unable to be leveled and aligned.

[0088] To address the aforementioned problems, particularly the issue of Hall sensor miscalculation due to the reverse rotation of the seat motor, this invention proposes a self-learning calibration method for the seat motor. By enabling the seat motor to "self-learn" with each adjustment, it can relearn the optimal stopping point during each folding process. For multiple seats in the same row, the left and right seats can be restored to their initial positions after each folding, and the initial positions can be self-learned. After executing the same adjustment procedure again, the left and right backrests are ensured to be aligned each time.

[0089] In the operation of the seat motor, the controller plays a crucial role. It is the "brain" of the entire motor control system, responsible for receiving folding commands from the vehicle's central control unit (such as the ECU) or other command sources. Once these commands are received, the controller sends corresponding current or voltage signals to the seat motor according to preset programs and logic, driving the motor to rotate in a specified direction (such as folding or unfolding). Folding commands can originate from the vehicle's control panel, remote control, or central control unit (ECU).

[0090] When the controller receives a folding command, it drives the target seat's motor to begin rotating in a preset learning direction. This rotation continues until the seat motor encounters resistance and stalls, meaning the motor can no longer rotate. The preset learning direction can be the folding or flipping direction of the target seat. The target seat can be any seat or any row of seats in the vehicle. When the target seat refers to any row of seats in the target vehicle, all individual seats in that row are driven synchronously.

[0091] Taking the case where the target seat cushion remains stationary (i.e., the target seat does not adjust forward or backward) as an example, the target seat rotating in the preset learning direction means that the backrest of the target seat rotates in the folding or flipping direction under the drive of its corresponding seat motor. Throughout this process, the range of travel for the target seat rotating in the preset learning direction is limited. For example, if the maximum flipping angle of the target seat backrest is 135°, the corresponding travel range of the seat motor might be 1800 Hall effect units. Theoretically, when the target seat backrest flips to 135°, the seat motor could travel from 0 to 1800 Hall effect units. However, due to factors such as foam interference, Hall effect sensor underestimation, and seat motor reversal, the seat motor might stall before reaching the maximum Hall effect distance during each adjustment. When the seat motor stalls, the position of the seat motor rotor at this time is recorded; this position is defined as the first stop point. Next, the system calculates the distance between this first stop point and the desired stop point. Here, the desired stop point is the position where the seat motor rotor is expected to stop in the preset learning direction (i.e., the desired stop point). As can be understood, the desired stopping point is the theoretically correct point where the seat motor "should" stop. Continuing with the example above, if the target seat's backrest has a maximum tilt angle of 135°, the corresponding travel range of the seat motor might be 1800 Hall effect points. Therefore, the position of the seat motor's rotor when it reaches 1800 Hall effect points can be considered the desired stopping point.

[0092] However, due to factors such as foam interference, Hall sensor miscalculations, and seat motor reversal, when the seat motor reaches its 1750 Hall effect point, it encounters resistance and cannot continue moving; that is, the seat motor stalls at this point. The system records the stopping point (the first stopping point) when the seat motor reaches this 1750 Hall effect point. If the distance between the calculated first stopping point and the desired stopping point is less than the preset Hall effect distance, the system considers this first stopping point to be a more accurate or suitable stopping point. Therefore, the system updates the position of the desired stopping point and sets it as the position of this first stopping point. This updated stopping point will serve as the stopping point for the seat motor's next rotation in the preset learning direction.

[0093] It should be noted that the preset Hall distance is a pre-defined threshold used to compare the difference between the actual stopping position and the desired stopping position. The most precise stopping point of the seat motor is determined through actual operation and testing, and the motor's stopping position is continuously optimized by comparing and updating it with the preset value. This improves the control accuracy and stability of the seat motor, which is the "self-learning" of the seat calibration position.

[0094] As an optional embodiment, before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes: in response to receiving the folding command, determining whether the target seat meets the folding conditions; and in response to the target seat meeting the folding conditions, determining to control the seat motor of the target seat to rotate in a preset learning direction according to the folding command.

[0095] In practice, before the target seat motor responds to the folding command, the system will first check whether the target seat meets the folding conditions.

[0096] As an optional embodiment, determining whether the target seat meets the folding conditions includes: determining whether the target seat is occupied; and in response to the target seat being occupied, determining that the target seat does not meet the folding conditions.

[0097] In practice, these conditions may include, but are not limited to, the need to determine whether there are passengers or items on the target seat to ensure that the folding operation does not cause any injury or damage. For these situations, a weight sensor or infrared sensor can be installed on the target seat to detect the presence of passengers or items. When the sensor detects weight or an object, the system automatically locks the folding function to prevent accidental operation. Alternatively, an in-vehicle camera or radar system can be used to monitor the target seat area in real time. Image recognition technology can be used to determine whether there are passengers or items on the target seat, thereby avoiding the folding operation. Furthermore, before the folding operation, the system can prompt the user via display or voice to confirm whether there are people or items on the target seat. The system will only execute the folding operation after the user manually confirms.

[0098] As an optional embodiment, determining whether the target seat meets the folding conditions further includes: determining whether there is an obstacle within the travel range of the target seat rotating in the preset learning direction; and determining that the target seat does not meet the folding conditions in response to the existence of an obstacle within the travel range of the target seat rotating in the preset learning direction.

[0099] As an optional embodiment, the obstacle includes other seats, which are adjusted to move away from the range of motion of the target seat as it rotates toward the preset learning direction, in response to the other seats blocking the range of motion of the target seat.

[0100] In practice, meeting the folding conditions may also involve determining whether there is sufficient space around the target seat for folding to avoid collisions with other parts of the vehicle. For this, ultrasonic sensors, laser sensors, or radar can be used to measure the space around the target seat. When insufficient space is detected, the system will automatically stop the folding operation and issue a warning. Alternatively, the target seat folding system can be integrated with the vehicle's parking assist system, radar system, etc., to achieve information sharing. When the vehicle is in a confined space or there are obstacles nearby (such as the front seats being too far back), the system will automatically restrict the target seat folding operation. Alternatively, users can set the minimum space requirement for folding the target seat in the system according to their actual needs. When the actual space is less than the user-set value, the system will automatically stop the folding operation.

[0101] As an optional embodiment, meeting the folding conditions may also include determining whether the mechanical structure of the target seat is in normal condition to ensure smooth folding operation. Regular inspection and maintenance of the seat's mechanical structure can ensure all components are in good working order. Problems should be repaired or replaced promptly to avoid affecting the folding operation. Sensors and diagnostic technologies can also be used to monitor the operating status of the seat's mechanical structure in real time. When an anomaly is detected, the system will automatically stop the folding operation and provide a fault indication. Regular software upgrades and optimizations of the seat folding system can also improve its stability and reliability. Furthermore, software upgrades can enable remote monitoring and diagnostics of the seat's mechanical structure.

[0102] It should be noted that the target seat is not allowed to be adjusted when the seat adjacent to it is in motion. For example, if the target seat is the third row of seats in the vehicle and you want to fold it, the second row of seats in the vehicle is moving towards the third row of seats. Folding the target seat may cause it to collide with and interfere with the second row of seats. Therefore, the target seat is determined not to meet the folding conditions in this case.

[0103] It should be noted that when the target seat is moving forward or backward, it is not allowed to perform folding or flipping operations, that is, the folding conditions are not met. When the target seat is performing folding or flipping operations, it is not allowed to move forward or backward.

[0104] As an optional embodiment, before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes: determining whether the engine used to drive the seat motor is in a running state, and determining whether the seat motor stores a desired stop point; in response to the engine being in a running state and the seat motor storing a desired stop point, determining to drive the seat motor of the target seat to rotate in the preset learning direction.

[0105] In practice, it is necessary to determine the engine status and the expected stop point storage status of the seat motor to ensure that the system is in the appropriate operating state before driving the seat motor to perform the folding operation.

[0106] Specifically, upon receiving a folding command, the system first checks if the engine driving the seat motor (which can be understood as the vehicle's main engine or an auxiliary engine / power source specifically for powering the seat motor) is running. If the engine is not running, the system may prompt the user to start the engine or attempt to start it automatically. Engine running is a prerequisite for the seat motor to function properly, as it provides the necessary electrical or power source. Next, the system checks if the seat motor has stored a desired stop point. This desired stop point is the position where the seat motor should stop in the preset learning direction. If the seat motor has not stored a desired stop point, the system may perform a self-learning or calibration process to determine this point, or prompt the user to perform calibration. Storing the desired stop point is crucial for the seat motor to stop accurately at the expected position, ensuring the accuracy and reliability of the seat folding operation. Only when the engine is running and the seat motor has stored the desired stop point will the system drive the seat motor to rotate in the preset learning direction according to the folding command.

[0107] As an optional embodiment, it is necessary to record the number of first Hall pulses output by the seat motor from the start time to the time when the seat motor stalls; and convert the number of first Hall pulses into a first Hall value according to a preset ratio.

[0108] As an optional embodiment, determining whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance includes: calculating the difference Hall distance between the first Hall value and the preset Hall value corresponding to the desired stopping point; and determining whether the difference Hall distance is less than the preset Hall distance.

[0109] In practice, when the seat motor starts rotating from startup, the system begins recording the number of Hall pulses output by the motor. These Hall pulses are generated by the Hall sensor during motor rotation and correspond to the motor's rotation angle or position. The first Hall pulse count refers to the total number of Hall pulses recorded by the system from motor startup to stall. The system converts the first Hall pulse count into a first Hall value according to a preset ratio (this ratio can be determined based on the motor design and the characteristics of the Hall sensor). The Hall value is a relatively abstract representation, representing the relative position or angle of the motor's rotation. Through this conversion, the system can transform the physical quantity of the Hall pulse count into a more easily processed and comparable value. Further, after determining the first Hall value, the system needs to calculate the difference Hall distance between it and the preset Hall value corresponding to the desired stopping point. The desired stopping point is the position where the seat motor should stop in the preset learning direction, and the preset Hall value is the Hall value corresponding to this position. The difference Hall distance is the difference between the first Hall value and the preset Hall value; it represents the relative distance (on the scale of the Hall value) between the actual stopping position and the desired stopping position. Finally, the system checks whether this difference Hall distance is less than a preset Hall distance threshold. This threshold is determined based on the accuracy requirements of the seat motor, the resolution of the Hall sensor, and the overall system design requirements. If the difference Hall distance is less than the preset Hall distance, the system considers the difference between the actual stopping position and the desired stopping position to be acceptable, and therefore updates the desired stopping point to the first stopping point (or the position corresponding to the first Hall value).

[0110] As an optional embodiment, in response to the distance between the first stop point and the desired stop point being not less than a preset Hall distance, it is determined whether the number of times the seat motor stalls within a preset time interval reaches a preset number threshold; in response to the number of times the seat motor stalls within a preset time interval reaching the preset number threshold, the second stop point at the last time the seat motor stalls is determined; the desired stop point is updated to the second stop point; wherein, the second stop point represents the stop point at which the seat motor will next rotate in a preset learning direction.

[0111] Specifically, when the system detects that the distance between the first stop point and the desired stop point is not less than a preset Hall distance, it further checks whether the number of times the seat motor stalls within a preset time interval has reached a preset threshold. This preset time interval and threshold are determined based on the characteristics of the seat motor, the system design requirements, and the actual application scenario. If the number of stalls does not reach the threshold, the system may continue to try adjusting the motor's rotation parameters or performing other operations to try to get closer to the desired stop point. If the number of times the seat motor stalls within the preset time interval reaches the preset threshold, the system determines the second stop point where the seat motor last stalled. The second stop point is the position where the motor finally stops after multiple attempts, and it may be closer to the desired stop point. Furthermore, the system updates the desired stop point to the second stop point. This means that in subsequent seat folding operations, when the seat motor rotates in the preset learning direction, it will attempt to stop at the second stop point. The purpose of updating the desired stop point is to adjust the system's expectations based on the actual performance of the motor to ensure that the seat can be accurately folded to the expected position. The second stop point not only represents the stop point where the seat motor will next rotate in the preset learning direction but also reflects the optimal stopping position of the motor under the current conditions. By updating the desired stop point to the second stop point, the system can more accurately control the folding position of the seat, improving the overall system performance and reliability.

[0112] It should be noted that by checking the number of times the motor stalls within a preset time interval, the system can also assess the motor's operating status and performance. An excessive number of stalls may indicate a motor malfunction or the need for maintenance.

[0113] In summary, by determining the second stop point, the system can adjust the desired stop point based on the motor's actual performance, ensuring the seat folds accurately to the intended position. Updating the desired stop point is a crucial step in the seat motor's self-learning calibration. It enables the system to optimize its control strategy based on the motor's actual operating conditions and changes in the external environment, improving the overall system performance and reliability.

[0114] As an optional embodiment, determining the second stop point when the seat motor last stalls includes: recording the number of second Hall pulses output by the seat motor from the start time to the last time the seat motor stalls; and determining the second stop point based on the number of second Hall pulses.

[0115] Specifically, when the seat motor starts rotating from startup and the system detects the last time the motor stalls, it records the number of Hall pulses output from startup to the stall point, which can be called the second Hall pulse count. The Hall pulse count is generated by the Hall sensor during motor rotation, and it corresponds to the motor's rotation angle or position. By recording these pulse counts, the system can track the motor's rotation. Based on the recorded second Hall pulse count, the system can determine the stopping position of the seat motor during its last stall, i.e., the second stopping point. Similarly, this process involves converting the Hall pulse count into the motor's rotation angle or position information, which can be achieved through a preset ratio or mapping relationship. The second stopping point represents the position where the motor can stably stop under current conditions. By recording the second Hall pulse count, the system can accurately track the motor's rotation and determine the motor's position during its last stall.

[0116] In the previous steps, the system has determined the first stop point and checked its distance from the desired stop point. If the distance between the first stop point and the desired stop point is not less than a preset Hall distance, the system will further check the number of times the motor stalls. When the number of stalls reaches a preset threshold, the system will execute the steps in this optional embodiment to determine the second stop point and update the desired stop point accordingly.

[0117] refer to Figure 7 This is a schematic diagram of the overall process of the self-learning calibration method for the seat motor provided in an embodiment of the present invention.

[0118] As an optional embodiment, when the controller receives a folding command, it first checks whether the target seat is occupied. If the target seat is occupied, the system considers the folding conditions unmet and immediately terminates the entire operation. If the target seat is not occupied, the system further checks whether the motor driving the seat motor has started. Simultaneously, the system also checks whether the seat motor has stored the desired stop point. If the seat motor has not started or has not stored the desired stop point, the system also terminates the entire operation. If the motor has started and the seat motor has stored the desired stop point, the system further determines whether the current position of the target seat backrest meets the motion conditions. Motion conditions include conditions for seat forward / backward and up / down movement, as well as conditions for seat backrest folding / folding. For example, the target seat backrest needs sufficient space during rotation and should not be obstructed by adjacent seats or components. If the rotational travel of the target seat backrest is obstructed by adjacent seats, the system will attempt to drive the adjacent seats to meet the target seat's motion conditions. Before driving the adjacent seats, it is also necessary to check whether the adjacent seats meet the motion conditions. If adjacent seats do not meet the movement conditions, the system will send a prompt to the vehicle's central control system and continuously monitor whether adjacent seats meet the conditions. Once all conditions are met, the system will drive the seat motor according to the folding command. During the driving process, the system will continuously monitor whether the seat motor stalls. If the seat motor stalls, the system will immediately stop driving the motor. Next, the system will check whether the differential Hall distance of the seat motor is less than a preset Hall distance (used to compare the difference between the actual stop position and the expected stop position). If the differential Hall distance is less than the preset value, the system will recalibrate the stop point of the seat motor and use the current stop point as the stop point for the next rotation in the preset learning direction. If the differential Hall distance is not less than the preset value, the system will continue to monitor whether the seat motor stalls a preset number of times within a preset time interval. For example, if it stalls 3 times within 5 seconds, the stop point of the seat motor will also be recalibrated. If the seat motor does not stall 3 times within 5 seconds, the system will consider the folding operation to be successfully completed and end the entire operation process. Through the above series of checks and monitoring steps, the safety and effectiveness of the seat folding operation are ensured. Meanwhile, by recalibrating the stop point of the seat motor, the system can adapt to different usage scenarios and conditions, improving the accuracy and reliability of seat folding.

[0119] As can be seen from the above, the self-learning calibration method for a seat motor provided by the present invention first drives the seat motor of the target seat to rotate in a preset learning direction according to the folding command until the seat motor stalls. Further, it determines the first stop point of the seat motor rotor when the seat motor stalls, and determines whether the distance between the first stop point and the desired stop point is less than a preset Hall distance. The desired stop point is a pre-calibrated stop point of the seat motor rotor in the preset learning direction. In response to the distance between the first stop point and the desired stop point being less than the preset Hall distance, the desired stop point is updated to the first stop point. The first stop point represents the stop point of the seat motor's next rotation in the preset learning direction. The present invention solves the problem of inaccurate Hall sensor counting in the seat motor by continuously calibrating the stop point of the seat motor, effectively improving the accuracy of seat adjustment and its self-learning.

[0120] It should be noted that the method of this embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this embodiment, and the multiple devices will interact with each other to complete the self-learning calibration method for the seat motor.

[0121] It should be noted that the above description describes some embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0122] Based on the same inventive concept, corresponding to the method provided in any of the above embodiments, the present invention also provides a self-learning calibration device for a seat motor.

[0123] refer to Figure 8 This is a schematic diagram of a self-learning calibration device for a seat motor provided in an embodiment of the present invention.

[0124] The device includes:

[0125] The control module is configured to drive the seat motor of the target seat to rotate in a preset learning direction according to the folding command until the seat motor stalls.

[0126] The first determining module is configured to determine the first stop point of the seat motor rotor when the seat motor stalls;

[0127] The second determining module is configured to determine whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance; wherein, the desired stopping point is the stopping point of the rotor of the seat motor pre-calibrated in a preset learning direction;

[0128] The calibration module is configured to update the desired stop point to the first stop point in response to the distance between the first stop point and the desired stop point being less than a preset Hall distance; wherein the first stop point represents the stop point at which the seat motor will next rotate in the preset learning direction.

[0129] In one possible implementation, the first determining module is further configured to:

[0130] In response to receiving the folding command, determine whether the target seat meets the folding conditions;

[0131] In response to the target seat meeting the folding condition, it is determined that the seat motor of the target seat will be controlled to rotate in a preset learning direction according to the folding command.

[0132] In one possible implementation, the first determining module is further configured to:

[0133] Determine whether the target seat is occupied;

[0134] In response to the target seat being occupied, it is determined that the target seat does not meet the folding condition.

[0135] In one possible implementation, the first determining module is further configured to:

[0136] Determine whether there are any obstacles within the range of the target seat's rotation in the preset learning direction;

[0137] If an obstacle exists within the travel range of the target seat when it rotates toward the preset learning direction, it is determined that the target seat does not meet the folding condition.

[0138] In one possible implementation, the obstacle includes other seats, and the first determining module is further configured to:

[0139] In response to the target seat's rotation range toward the preset learning direction being blocked by other seats, the other seats are adjusted to move away from the range of motion.

[0140] In one possible implementation, the first determining module is further configured to:

[0141] Determine whether the engine used to drive the seat motor is running, and determine whether the seat motor stores the desired stop point;

[0142] In response to the engine being started and the seat motor storing the desired stop point, it is determined that the seat motor driving the target seat will rotate in a preset learning direction.

[0143] In one possible implementation, the control module is further configured as follows:

[0144] Record the number of the first Hall pulses output by the seat motor from the start-up time to the time when the seat motor stalls;

[0145] The first Hall pulse count is converted into the first Hall value according to a preset ratio.

[0146] In one possible implementation, the control module is further configured as follows:

[0147] Calculate the difference Hall distance between the first Hall value and the preset Hall value corresponding to the desired stopping point;

[0148] Determine whether the difference Hall distance is less than the preset Hall distance.

[0149] In one possible implementation, the calibration module is further configured as follows:

[0150] In response to the fact that the distance between the first stop point and the desired stop point is not less than the preset Hall distance, it is determined whether the number of times the seat motor stalls within a preset time interval reaches a preset number threshold.

[0151] In response to the seat motor stalling a number of times within a preset time interval, a second stopping point is determined when the seat motor stalls for the last time.

[0152] The desired stopping point is updated to the second stopping point; wherein the second stopping point represents the stopping point of the seat motor when it rotates in the preset learning direction next.

[0153] In one possible implementation, the calibration module is further configured as follows:

[0154] Record the number of second Hall pulses output by the seat motor from the start-up time to the last time the seat motor stalls;

[0155] The second stop point is determined based on the second Hall pulse count.

[0156] For ease of description, the above system is described by dividing it into various modules based on their functions. Of course, in implementing this invention, the functions of each module can be implemented in one or more software and / or hardware components.

[0157] The system described above is used to implement the self-learning calibration method of the corresponding seat motor in any of the foregoing embodiments, and has the beneficial effects of the corresponding self-learning calibration method embodiments of the seat motor, which will not be repeated here.

[0158] Based on the same inventive concept, corresponding to the self-learning calibration method of the seat motor described in any of the above embodiments, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the self-learning calibration method of the seat motor described in any of the above embodiments.

[0159] Figure 9 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1110, a memory 1120, an input / output interface 1130, a communication interface 1140, and a bus 1150. The processor 1110, memory 1120, input / output interface 1130, and communication interface 1140 are interconnected internally via the bus 1150.

[0160] The processor 1110 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0161] The memory 1120 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1120 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1120 and is called and executed by the processor 1110.

[0162] Input / output interface 1130 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0163] The communication interface 1140 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0164] Bus 1150 includes a pathway for transmitting information between various components of the device, such as processor 1110, memory 1120, input / output interface 1130, and communication interface 1140.

[0165] It should be noted that although the above-described device only shows the processor 1110, memory 1120, input / output interface 1130, communication interface 1140, and bus 1150, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0166] The electronic devices described above are used to implement the self-learning calibration method for the corresponding seat motor in any of the foregoing embodiments, and have the beneficial effects of the corresponding self-learning calibration method embodiments for the seat motor, which will not be repeated here.

[0167] Based on the same inventive concept, corresponding to the self-learning calibration method for the seat motor described in any of the above embodiments, the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the self-learning calibration method for the seat motor as described in any of the above embodiments.

[0168] The aforementioned non-transitory computer-readable storage media can be any available medium or data storage device that a computer can access, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0169] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the self-learning calibration method for the seat motor as described in any of the embodiments in the exemplary method section above, and have the beneficial effects of the corresponding self-learning calibration method embodiments for the seat motor, which will not be repeated here.

[0170] Based on the same inventive concept, corresponding to the self-learning calibration method of the seat motor described in any of the above embodiments, the present invention also provides a seat motor.

[0171] Figure 10 A schematic diagram of a seat motor provided in this embodiment is shown. The device may include the electronic equipment described above and has the beneficial effects of the corresponding embodiments, which will not be repeated here.

[0172] Based on the same inventive concept, corresponding to the self-learning calibration method of the seat motor described in any of the above embodiments, the present invention also provides a vehicle.

[0173] Figure 11 A schematic diagram of a vehicle provided in this embodiment is shown. The device may include the seat motor described above and has the beneficial effects of the corresponding embodiment, which will not be repeated here.

[0174] Furthermore, although the operations of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowchart may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0175] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0176] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this invention should have the ordinary meaning understood by those skilled in the art. The terms "first," "second," and similar terms used in the embodiments of this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0177] While the spirit and principles of the invention have been described with reference to several specific embodiments, it should be understood that the invention is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for ease of description. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. The scope of the appended claims is to be interpreted in the broadest sense, thereby encompassing all such modifications and equivalent structures and functions.

Claims

1. A self-learning calibration method for a seat motor, characterized in that, include: The seat motor of the target seat is driven to rotate in the preset learning direction according to the folding command until the seat motor stalls. Determine the first stop point of the rotor of the seat motor when the seat motor stalls; Determine whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance; wherein, the desired stopping point is the stopping point pre-calibrated by the rotor of the seat motor in the preset learning direction; In response to the distance between the first stopping point and the desired stopping point being less than the preset Hall distance, the desired stopping point is updated to the first stopping point; wherein, the first stopping point represents the stopping point of the seat motor when it rotates in the preset learning direction next.

2. The self-learning calibration method for the seat motor according to claim 1, characterized in that, Before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes: In response to receiving the folding command, determine whether the target seat meets the folding conditions; In response to the target seat meeting the folding condition, it is determined that the seat motor of the target seat will be controlled to rotate in a preset learning direction according to the folding command.

3. The self-learning calibration method for the seat motor according to claim 2, characterized in that, Determining whether the target seat meets the folding conditions includes: Determine whether the target seat is occupied; In response to the target seat being occupied, it is determined that the target seat does not meet the folding condition.

4. The self-learning calibration method for the seat motor according to claim 2, characterized in that, The step of determining whether the target seat meets the folding conditions also includes: Determine whether there are any other obstacles within the range of the target seat's rotation toward the preset learning direction; If there are other obstacles within the travel range of the target seat rotating in the preset learning direction, it is determined that the target seat does not meet the folding condition.

5. The self-learning calibration method for the seat motor according to claim 4, characterized in that, The obstacle includes other seats; The method further includes: In response to the target seat's rotation range toward the preset learning direction being blocked by other seats, the other seats are adjusted to move away from the range of motion.

6. The self-learning calibration method for the seat motor according to claim 1, characterized in that, Before driving the seat motor of the target seat to rotate in a preset learning direction according to the folding command, the method further includes: Determine whether the engine used to drive the seat motor is running, and determine whether the seat motor stores the desired stop point; In response to the engine being started and the seat motor storing the desired stop point, it is determined that the seat motor driving the target seat will rotate in a preset learning direction.

7. The self-learning calibration method for the seat motor according to claim 1, characterized in that, The method further includes: Record the number of the first Hall pulses output by the seat motor from the start-up time to the time when the seat motor stalls; The first Hall pulse count is converted into the first Hall value according to a preset ratio.

8. The self-learning calibration method for the seat motor according to claim 7, characterized in that, Determining whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance includes: Calculate the difference Hall distance between the first Hall value and the preset Hall value corresponding to the desired stopping point; Determine whether the difference Hall distance is less than the preset Hall distance.

9. The self-learning calibration method for the seat motor according to claim 1, characterized in that, The method further includes: In response to the fact that the distance between the first stop point and the desired stop point is not less than the preset Hall distance, it is determined whether the number of times the seat motor stalls within a preset time interval reaches a preset number threshold. In response to the seat motor stalling a number of times within a preset time interval, a second stopping point is determined when the seat motor stalls for the last time. The desired stopping point is updated to the second stopping point; wherein the second stopping point represents the stopping point of the seat motor when it rotates in the preset learning direction next.

10. The self-learning calibration method for a seat motor according to claim 9, characterized in that, Determining the second stop point when the seat motor last stalled includes: Record the number of second Hall pulses output by the seat motor from the start-up time to the last time the seat motor stalls; The second stop point is determined based on the second Hall pulse count.

11. A self-learning calibration device for a seat motor, characterized in that, include: The control module is configured to drive the seat motor of the target seat to rotate in a preset learning direction according to the folding command until the seat motor stalls. The first determining module is configured to determine the first stop point of the rotor of the seat motor when the seat motor stalls; The second determining module is configured to determine whether the distance between the first stopping point and the desired stopping point is less than a preset Hall distance; wherein, the desired stopping point is a stopping point pre-calibrated by the rotor of the seat motor in the preset learning direction; The calibration module is configured to update the desired stopping point to the first stopping point in response to the distance between the first stopping point and the desired stopping point being less than the preset Hall distance; wherein the first stopping point represents the stopping point of the seat motor in the next rotation toward the preset learning direction.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the self-learning calibration method for a seat motor as described in any one of claims 1 to 10.

13. A non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the self-learning calibration method for a seat motor according to any one of claims 1 to 10.

14. A seat motor, characterized in that, Including the electronic device as described in claim 12.

15. A vehicle, characterized in that, Includes the seat motor as described in claim 14.

Images