Automobile window glass lifting control method and lifting system

Abstract

The invention provides an automobile window glass lifting control method and a lifting system, relates to the technical field of automobile window glass lifting control, and aims to improve the accuracy of automobile window glass lifting buffer control by dynamically adjusting a damping coefficient to adapt to the real-time operation working condition of the lifting system. The method comprises the following steps: acquiring multi-source operation data; the multi-source operation data are data related to the operation state of the lifting system of the automobile window glass; identifying at least one operation condition of the lifting system based on the multi-source operation data; determining a candidate damping coefficient corresponding to each operation condition, and selecting the candidate damping coefficient with the maximum value from all the candidate damping coefficients as a target damping coefficient; and carrying out buffer control on the lifting system based on the damping force corresponding to the target damping coefficient.

Description

Technical Field

[0001] This application relates to the field of vehicle window lifting control technology, and in particular to a control method and lifting system for lifting automotive window glass. Background Technology

[0002] As automotive intelligence and comfort levels continue to improve, users are increasingly demanding smooth operation and scenario adaptability from window lift systems. The damping coefficient, a key parameter affecting system performance, directly impacts the driving experience. The damping coefficient is a core indicator measuring the resistance to window lifting. A higher value results in stronger buffering resistance and smoother movement, but may reduce lifting speed; a lower value results in less resistance and more sensitive lifting, but may compromise operational stability. Currently, most automotive window lift systems use a fixed damping coefficient design, meaning the coefficient is preset at the factory through mechanical structure or circuit parameters. This cannot be dynamically adjusted based on actual operating conditions, making it difficult for the system to simultaneously meet the needs of different scenarios. In extreme conditions, improper damping adaptation may exacerbate component wear and affect system lifespan. Summary of the Invention

[0003] The purpose of this application is to provide a control method and lifting system for raising and lowering automotive windows, which aims to improve the accuracy of automotive window raising and lowering buffer control by dynamically adjusting the damping coefficient to adapt to the real-time operating conditions of the lifting system.

[0004] To achieve the above objectives, the embodiments of this application provide the following technical solutions: In a first aspect, this application provides a control method for raising and lowering a car window, the method comprising: acquiring multi-source operating data; the multi-source operating data being data related to the operating status of the car window raising and lowering system; identifying at least one operating condition of the raising and lowering system based on the multi-source operating data; determining candidate damping coefficients corresponding to each operating condition, selecting the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient; and performing buffer control on the raising and lowering system based on the damping force corresponding to the target damping coefficient.

[0005] This application provides a control method for raising and lowering automotive windows. By acquiring multi-source operational data related to the operating status of the raising system, it can comprehensively collect multi-source operational data, avoiding the one-sidedness of single data and providing a data foundation for operating condition identification. Based on this multi-source operational data, it identifies at least one operating condition of the raising system, accurately determining the operating condition of the raising system and solving the problem that traditional fixed damping cannot detect changes in operating conditions. By determining the candidate damping coefficient corresponding to each operating condition and selecting the maximum value as the target damping coefficient, it can match the corresponding damping requirements for different operating conditions and achieve dynamic adaptive adjustment of the damping coefficient. In summary, this method achieves accurate identification of the operating conditions of the raising system and dynamic adaptive matching of damping parameters, improves the accuracy of buffer control, effectively reduces vibration and impact in various scenarios, ensures smooth operation, and reduces component wear to extend the system's service life.

[0006] In some embodiments, the multi-source operating data includes at least one of the following: displacement data, vibration acceleration data, and ambient temperature data; based on the multi-source operating data, identifying at least one operating condition of the lifting system includes: when the displacement data is within a preset edge range, the operating condition is an edge buffer condition; the preset edge range is a range where the lifting system is nearly completely closed or nearly completely open; when the vibration acceleration data exceeds a preset vibration threshold, the operating condition is an anti-sway condition; when the ambient temperature data is below a preset temperature threshold, the operating condition is a low-temperature environment condition.

[0007] In some embodiments, determining candidate damping coefficients for each operating condition and selecting the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient includes: in response to identifying an edge buffer condition, calculating a first candidate damping coefficient based on displacement data through a first mapping relationship; in response to identifying an anti-sway condition, calculating a second candidate damping coefficient based on vibration acceleration data through a second mapping relationship; in response to identifying a low-temperature environment condition, calculating a third candidate damping coefficient based on ambient temperature data through a third mapping relationship; and selecting the candidate damping coefficient with the largest value from the first candidate damping coefficient, the second candidate damping coefficient, and the third candidate damping coefficient as the target damping coefficient.

[0008] In some embodiments, real-time resistance data and real-time speed data from multi-source operating data are acquired; if the rate of change of real-time resistance data within a preset time exceeds a preset resistance threshold, and / or the rate of decrease of real-time speed data within a preset time exceeds a preset speed threshold, it is determined that the lifting system is in a potential clamping fault; in response to the potential clamping fault, a safety warning operation is performed; the safety warning operation includes one of the following: pausing the lifting of the lifting system, or controlling the lifting system to run in the opposite direction at a preset safe speed for a preset distance.

[0009] Secondly, this application also provides an automotive window lifting system for executing the control method of the first aspect. The lifting system includes: a sensor group configured to acquire multi-source operating data; the multi-source operating data being data related to the operating state of the automotive window lifting system; a damping actuator, a damping mechanism with dynamically adjustable damping coefficient; a drive motor for driving the lifting system to lift; and a controller communicatively connected to the sensor group, the damping actuator, and the drive motor, respectively. The controller is configured to: identify at least one operating condition of the lifting system based on the multi-source operating data; determine candidate damping coefficients corresponding to each operating condition; select the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient; and, based on the target damping coefficient, control the damping actuator to output damping force, coordinating with the drive motor to lift the lifting system.

[0010] In some embodiments, the damping actuator is a magnetorheological fluid damping actuator; wherein, the damping actuator includes a damping cylinder, an excitation coil, and a piston rod; the damping cylinder is filled with magnetorheological fluid, the excitation coil is disposed around the periphery of the damping cylinder, and either end of the piston rod extends into the damping cylinder and is connected to the glass slider; the controller is configured to: adjust the damping force by changing the rheological properties of the magnetorheological fluid by adjusting the input current of the excitation coil.

[0011] In some embodiments, the controller is further configured to: monitor the operating current of the damping actuator and the operating speed of the drive motor in real time; and execute system protection actions when the operating current exceeds a preset current threshold and / or the operating speed is lower than a preset stall speed threshold; the system protection actions include: cutting off or limiting the current to the damping actuator, controlling the drive motor to slow down or stop running.

[0012] In some embodiments, the sensor group includes at least one of the following: a Hall sensor and magnet combination for acquiring displacement data; a piezoelectric accelerometer for acquiring vibration acceleration data; a temperature sensor for acquiring ambient temperature data; a pressure sensor or current sensor for acquiring real-time resistance data; and an encoder or Hall velocity sensor for acquiring real-time velocity data.

[0013] Thirdly, a control device for raising and lowering a car window includes: an acquisition module, an identification module, a selection module, and a control module; the acquisition module is used to: acquire multi-source operating data; the multi-source operating data is data related to the operating status of the car window raising and lowering system; the identification module is used to: identify at least one operating condition of the raising and lowering system based on the multi-source operating data; the selection module is used to: determine the candidate damping coefficient corresponding to each operating condition, and select the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient; the control module is used to: perform buffer control on the raising and lowering system based on the damping force corresponding to the target damping coefficient.

[0014] Fourthly, this application also provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, causing the electronic device to implement the method of the first aspect described above.

[0015] Fifthly, this application also provides a computer-readable storage medium comprising: computer software instructions; when the computer software instructions are executed in an electronic device, the electronic device performs the method described in the first aspect.

[0016] Sixthly, this application also provides a computer program product comprising a computer program that, when run on an electronic device, causes the electronic device to perform the method of the first aspect.

[0017] The beneficial effects of the second to sixth aspects mentioned above can be referred to the corresponding descriptions in the first aspect, and will not be repeated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This application provides a schematic diagram of the structure of an automotive window lift system. Figure 2 A general structural layout diagram of an automotive window lifting system provided in this application embodiment; Figure 3 A flowchart illustrating a method for controlling the raising and lowering of an automotive window provided in an embodiment of this application; Figure 4 A flowchart illustrating a method for determining a target damping coefficient provided in an embodiment of this application; Figure 5 A complete flowchart illustrating a control method for an automotive window lift system provided in this application embodiment; Figure 6 This application provides a schematic diagram of the composition of a control device for raising and lowering automobile windows. Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0022] In the embodiments of this application, the terms "first," "second," "third," "fourth," "fifth," and "sixth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," "third," "fourth," "fifth," and "sixth" may explicitly or implicitly include one or more of that feature.

[0023] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. For "A and / or B," this includes three combinations: A only, B only, and a combination of A and B.

[0024] In automotive window motion control, the damping coefficient is a core parameter for regulating motion smoothness and buffering effect. Its adaptability directly affects the user experience, energy consumption, and service life of the equipment. Currently, most mainstream equipment adopts a fixed damping design, meaning that the damping parameters are preset at the factory through mechanical structure or circuit parameters, and cannot be dynamically adjusted according to actual operating conditions during subsequent use. This technology has several drawbacks: Firstly, dynamic changes in actual operating conditions can cause motion resistance to deviate from the preset value—for example, hardening of rubber seals at low temperatures increases resistance, while wear and tear on components over long-term use decreases resistance. Fixed damping struggles to adapt to these changes, easily leading to problems such as equipment lifting and lowering jamming, increased operating noise, and abnormal movement speed, severely impacting the user experience. Secondly, to cover the maximum resistance requirements under extreme conditions, fixed damping is usually designed for extreme conditions, causing the motor to bear excessively high loads under normal operating conditions. This not only increases unnecessary energy consumption but also accelerates fatigue wear on transmission components such as motors, gears, and guide rails, significantly shortening the overall service life of the equipment.

[0025] Based on this, this application provides a control method for raising and lowering automotive windows. By acquiring multi-source operational data related to the operating status of the raising system, it can comprehensively collect system operating information, avoiding the limitations of single data sources and providing a complete and accurate data foundation for operating condition identification. Based on this multi-source operational data, it identifies at least one operating condition of the raising system, accurately determining the system's condition and solving the problem that traditional fixed damping cannot detect changes in operating conditions. By determining the candidate damping coefficients corresponding to each operating condition and selecting the maximum value as the target damping coefficient, it can match the corresponding damping requirements for different operating conditions, achieving dynamic adaptive adjustment of the damping coefficient. Through the above methods, this method achieves accurate identification of the operating conditions of the raising system, dynamically matches the optimal damping parameters based on the operating conditions, improves the accuracy of buffer control, effectively reduces vibration and impact, ensures smooth operation in various scenarios, reduces component wear, and extends the service life of the raising system.

[0026] The method for controlling the raising and lowering of automotive windows provided in this application embodiment can be applied to, for example, Figure 1 The system shown.

[0027] Figure 1 This is a schematic diagram of a car window lift system provided in an embodiment of this application. Figure 1 As shown, the automotive window lifting system includes a sensor group 101, a damping actuator 102, a drive motor 103, and a controller 104, wherein the controller 104 is coupled to the sensor group 101, the damping actuator 102, and the drive motor 103 respectively.

[0028] The sensor group 101 is used to collect multi-source operating data related to the operating status of the lifting system, providing complete data support for subsequent working condition identification. The multi-source operating data includes at least one of the following: displacement data, vibration acceleration data, ambient temperature data, real-time resistance data, and real-time velocity data.

[0029] The damping actuator 102 is a damping mechanism with a dynamically adjustable damping coefficient. It is installed in the lifting system and is used to output a damping force of a corresponding magnitude according to the instructions of the controller 104, so as to realize the real-time adaptation of the damping coefficient.

[0030] The drive motor 103 is used to provide driving force for the lifting and lowering movement of the vehicle window glass, and its operating speed and output power can be adjusted according to the coordination instructions of the controller 104.

[0031] The controller 104 refers to an electronic device that can receive and process various information such as sensor signals and user operation instructions, and send control signals to the actuators according to preset logic or real-time requirements, thereby realizing the adjustment of the window lifting function or system management.

[0032] In some embodiments, the controller 104 is used to acquire multi-source operating data of the lifting system collected by the sensor group 101, identify at least one operating condition of the lifting system based on the multi-source operating data, determine the candidate damping coefficient corresponding to each operating condition, select the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient, and control the damping actuator 102 to output damping force based on the target damping coefficient, and coordinate with the drive motor 103 to perform lifting control of the lifting system.

[0033] In this embodiment, during the operation of the vehicle window glass, a sensor group 101 collects multi-source operating data on the operating status of the lifting system. The controller 104 accurately identifies various complex operating conditions and dynamically matches the optimal damping parameters. Compared with traditional fixed damping systems, this system provides more precise and effective suppression of vibration and impact, effectively improving the smoothness of window lifting, reducing component wear, and extending the overall service life of the lifting system.

[0034] In some embodiments, sensor group 101 includes at least one of the following (1) to (5): (1) A combination of a Hall sensor and a magnet for acquiring displacement data.

[0035] The Hall sensor and magnet combination used to acquire displacement data is a detection device that uses the Hall effect to sense changes in the magnetic field of the magnet and outputs an electrical signal. It is used to capture the displacement data of the vehicle window glass. The signal output by this Hall sensor and magnet combination can be processed and converted into precise position parameters, providing a basis for system condition judgment and control decisions. The displacement data refers to the distance the glass moves relative to its initial position during the lifting and lowering process, reflecting the lifting stage and positional state of the glass. The Hall sensor can be a switch-type Hall sensor, a latching-type Hall sensor, a linear Hall sensor, etc. This application does not impose specific limitations on the specific type and number of Hall sensors, or the number and shape of the magnets.

[0036] In one possible implementation, two Hall sensors are arranged at intervals along the length of the glass lifting guide rail, and magnets are fixedly installed on the glass slider. The magnets and the two Hall sensors maintain an appropriate sensing distance. When the glass is lifted and the slider moves, the magnets move synchronously with the slider, triggering the two Hall sensors to generate sensing signals in sequence. The real-time displacement data of the vehicle window glass is obtained by calculating the distance between the preset sensors based on the signal triggering timing.

[0037] In another possible implementation, a combination of a Hall effect sensor and a multipole magnet is used to achieve continuous position detection. A linear Hall effect sensor is fixedly mounted at one end of the lifting guide rail, and the multipole magnet is fixed to the glass slider along the guide rail. When the glass is raised or lowered, the multipole magnet moves with the slider, and the linear Hall effect sensor senses the alternating polarity of the magnetic field and outputs a continuously changing voltage signal. By measuring the number of cycles and phase of the voltage signal, the real-time displacement and direction of movement of the glass can be directly calculated. This implementation provides higher position resolution and can directly acquire motion direction information, providing richer motion parameters for the control system.

[0038] In another possible implementation, a combination of a differential Hall sensor array and a ring magnet can be used to improve anti-interference capability. Multiple Hall sensors are arranged in a ring array around the guide rail, and the ring magnet is coaxially mounted on the slider. By differentially processing the output signals of multiple sensors, common-mode interference can be effectively suppressed, improving the accuracy and reliability of displacement detection.

[0039] (2) A piezoelectric accelerometer for acquiring vibration acceleration data.

[0040] Among them, the piezoelectric accelerometer used to acquire vibration acceleration data is a detection device that converts mechanical vibration into electrical signals based on the piezoelectric effect. It can capture the vibration intensity and changes in the window lifting system and surrounding structures. The vibration acceleration data it outputs can reflect the stability of the operating conditions during operation, providing key data support for the system to accurately adjust damping parameters and ensure the smoothness of lifting. This application does not impose specific restrictions on the specific type or quantity of piezoelectric accelerometers.

[0041] In one possible implementation, a piezoelectric accelerometer is fixedly installed inside the door near the window lift rail to ensure that the sensor can sensitively capture vibration signals from the door during driving. When the vehicle is traveling on bumpy roads, the sensor collects vibration acceleration data in real time and transmits it to the controller 104 via a bus, providing a reference for vibration dimension for condition assessment. This bus can be a local interconnect network (LIN) bus or a controller area network (CAN) bus.

[0042] (3) Temperature sensor used to acquire ambient temperature data.

[0043] Among them, the temperature sensor used to acquire ambient temperature data is a detection device that can sense changes in the surrounding ambient temperature and convert them into electrical signals. The temperature data it outputs can reflect the environmental conditions that affect the operation of the lifting system, providing key data support for the system to identify temperature-related operating conditions and dynamically adjust damping parameters.

[0044] In one possible implementation, the temperature sensor is installed inside the door near the window lift rail to ensure accurate sensing of ambient temperature changes around the rail. When the vehicle is in a low-temperature environment, the sensor collects temperature data in real time and transmits it to the controller 104 via a bus, providing direct basis for subsequent temperature-related operational condition judgments.

[0045] For example, an NTC thermistor is used as a temperature sensor, embedded in the end of the guide rail. It can collect ambient temperatures within the range of -40℃ to 85℃, with a detection accuracy of ±1℃. This method facilitates the acquisition of the actual operating temperature of the guide rail and surrounding components, improving the accuracy of temperature detection and providing a more reliable basis for damping adjustment. The NTC thermistor utilizes the temperature characteristics of semiconductor materials to directly convert changes in ambient temperature into continuous changes in its own resistance value. Therefore, the current temperature parameters can be accurately deduced by measuring its resistance value or the voltage drop value in a series circuit.

[0046] (4) Pressure sensor or current sensor used to obtain real-time resistance data.

[0047] Among them, the pressure sensor or current sensor used to acquire real-time resistance data is a detection device that can capture changes in the operating resistance of the window lifting system and convert them into electrical signals. The resistance data it outputs can directly reflect the frictional resistance state during the system's movement, providing key data support for judging the wear degree of components and adapting damping parameters.

[0048] In one possible implementation, a pressure sensor collects real-time resistance data to provide a precise basis for adaptive damping adjustment. For example, the pressure sensor is installed at the contact point between the glass lifting guide rail and the slider. When the glass is raised or lowered, the friction between the slider and the guide rail directly acts on the sensor. The sensor converts the mechanical signal into an electrical signal, which is then processed and transmitted to the control core to provide real-time feedback on the current operating resistance, laying the foundation for operating condition identification.

[0049] When the resistance drops to 1.2N due to component wear, this application adjusts the damping coefficient to 1.5N·s / m, stabilizing the lifting speed at 5.1cm / s. This effectively solves the problem of excessively fast lifting speed (up to 8cm / s) caused by wear in traditional systems, maintaining long-term stability.

[0050] (5) An encoder or Hall speed sensor used to acquire real-time speed data.

[0051] Among them, the encoder or Hall speed sensor used to acquire real-time speed data is a detection device that can capture the speed of the window glass lifting and lowering movement and convert it into an electrical signal. The speed data output by the sensor can directly reflect the real-time dynamics of the window lifting and lowering.

[0052] In one possible implementation, a Hall effect speed sensor is mounted on the output shaft of the drive motor 103. The sensor generates a pulse signal by sensing changes in the magnetic field during motor rotation. The controller 104 calculates the glass lifting speed based on the frequency of the pulse signal and monitors in real time whether the speed is within a preset stable range of a preset speed range. For example, it monitors in real time whether the speed is within a preset stable range of 5 cm / s ± 0.5 cm / s.

[0053] In another possible implementation, an encoder can be used instead of a Hall effect speed sensor to improve the accuracy of speed detection. For example, an incremental encoder can be coaxially connected to the motor output shaft. When the motor rotates, the encoder synchronously outputs A and B phase pulse signals. The control core calculates the real-time speed of the glass lifting by counting the number of pulses and the pulse frequency. The detection accuracy can reach ±0.1 cm / s, which can accurately capture instantaneous fluctuations in speed.

[0054] The above content describes how various sensors acquire multi-source operational data.

[0055] In some embodiments, the damping actuator 102 is a magnetorheological fluid damping actuator. The damping actuator 102 includes a damping cylinder, an excitation coil, and a piston rod. The damping cylinder is filled with magnetorheological fluid, the excitation coil is disposed around the periphery of the damping cylinder, and either end of the piston rod extends into the damping cylinder and is connected to the glass slider. The controller 104 is configured to adjust the damping force by changing the rheological properties of the magnetorheological fluid through adjusting the input current of the excitation coil.

[0056] Among them, the magnetorheological fluid damping actuator is an actuator that dynamically adjusts the damping force based on the magnetorheological effect. It changes the rheological properties of the internal magnetorheological fluid by changing the magnetic field, and precisely adjusts the damping coefficient.

[0057] In one possible implementation, the damping coefficient is precisely adjustable using a magnetorheological fluid damping actuator. For example, the damping cylinder of the actuator is filled with magnetorheological fluid, an excitation coil is wound around the cylinder's perimeter, one end of the piston rod extends into the damping cylinder, and the other end is fixedly connected to a glass slider. When the controller 104 outputs a damping adjustment command, the input current to the excitation coil is changed, adjusting the magnetic field strength inside the cylinder. This causes a corresponding change in the shear yield strength of the magnetorheological fluid, thereby achieving real-time adjustment of the damping coefficient to adapt to different operating conditions.

[0058] For example, the controller 104 presets the current adjustment range of the excitation coil to 0-5A. When it detects that the low temperature condition (-10℃) causes an increase in operating resistance, the control core adjusts the coil current to 3.5A, thereby increasing the shear yield strength of the magnetorheological fluid and adjusting the damping coefficient from the reference value to 380N. The damping coefficient (s / m) balances the increased resistance, ensuring a stable and smooth glass lifting speed. The damping coefficient can range from 50-500N. Continuously adjustable within the s / m range.

[0059] In other embodiments, the damping actuator 102 is an electromagnetic damping actuator, employing an eddy current damping method based on the principle of electromagnetic induction to adjust the damping parameters. This method generates a controllable damping force by adjusting the suppression effect of the magnetic field on the eddy currents in the conductor, utilizing a non-contact force transmission mechanism to avoid the sealing and fluid leakage problems that may exist in traditional fluid damping actuators.

[0060] For example, a conductive metal disk (such as a copper or aluminum disk) can be mounted on the rotating drive shaft of the lifting system, causing it to rotate synchronously. An electromagnet is fixedly mounted next to the metal disk, with its core facing the working surface of the disk. When damping is required, the controller 104 outputs a pulse width modulation (PWM) signal with a specific duty cycle to the electromagnet, causing it to generate a changing magnetic field. This magnetic field induces eddy currents in the rotating metal disk, and the magnetic field generated by these eddy currents interacts with the original magnetic field, producing a resistance torque opposite to the direction of the metal disk's rotation. This resistance torque is the force that prevents an object from rotating. By adjusting the duty cycle or frequency of the PWM signal, the magnitude of this resistance torque can be precisely controlled, thus adjusting the damping force.

[0061] PWM is a method for digitally encoding analog signal levels. Its principle is to adjust the duty cycle of a fixed-frequency square wave pulse signal (i.e., the ratio of the high-level time within one cycle to the entire cycle) to equivalently obtain different average output voltages or powers, thereby achieving precise control of the damping actuator.

[0062] In some embodiments, the controller 104 is further configured to: monitor the operating current of the damping actuator 102 and the operating speed of the drive motor 103 in real time; and execute system protection actions when the operating current exceeds a preset current threshold and / or the operating speed is lower than a preset stall speed threshold; the system protection actions include: cutting off or limiting the current to the damping actuator 102, and controlling the drive motor 103 to slow down or stop running.

[0063] In one possible implementation, the controller 104 collects the operating current of the damping actuator 102 and the real-time operating speed of the drive motor 103 in real time. The system has a preset upper current safety threshold and a lower speed threshold indicating that the motor is about to stop. When the operating current of the damping actuator 102 continuously exceeds the current threshold, and / or the speed of the drive motor 103 drops below the stall speed threshold, the controller 104 will immediately trigger system protection. Specific protection actions include, but are not limited to: rapidly cutting off or limiting the current supplied to the damping actuator 102 to unload the abnormal load, and simultaneously controlling the drive motor 103 to execute a deceleration or immediate stop command, effectively preventing serious consequences such as motor burnout and mechanical damage caused by forced operation.

[0064] For example, if the system outputs excessive current (e.g., 9A, exceeding the preset maximum value of 8A) to the magnetorheological damping actuator due to a misjudgment by controller 104, or if the motor speed drops to 3 r / min (below the stall threshold of 5 r / min) due to a foreign object obstructing the glass, the central control unit will immediately trigger protection: instantly cutting off the damping actuator current to eliminate internal resistance, simultaneously forcing the motor speed down to a safe mode of 1 r / min, and issuing an audible and visual alarm. During this process, the polyurethane elastic gasket at the connection effectively absorbs the mechanical impact caused by the sudden change in damping force. This system achieves a rapid response of 0.15s in the foreign object test, controlling the clamping force to within 50N by reversing the motor by 5mm, fully complying with national safety standards. Compared to the traditional system's 0.5s response time and 150N clamping force, the safety performance is improved by more than 60%.

[0065] In one possible implementation, when the infrared sensor detects a foreign object (such as a person's hand) in the glass running path, it immediately sends a trigger signal to the controller 104. After receiving the signal, the controller 104 performs real-time calculation and processing, and synchronously outputs control commands to the damping actuator 102 and the drive motor 103, thereby reducing the drive power and increasing the damping coefficient, thus quickly forming motion retardation, ensuring that the glass component stops completely or retracts in time before contacting the foreign object, and achieving safety protection for human-computer interaction scenarios.

[0066] In one possible implementation, the damping actuator 102 is mounted in parallel between the glass slider and the inner door panel, with its axis parallel to the lifting guide rail. This arrangement ensures that the damping actuator provides bidirectional damping force only to the movement of the slider, without transmitting the core driving force of the motor.

[0067] In one possible implementation, the system power module adopts a standard automotive 12V / 24V DC power input, and provides a stable and reliable 5V / 3.3V low-voltage power supply to various sensors and microprocessors through a high-efficiency DC-DC converter, effectively suppressing power ripple interference and ensuring the accuracy of multi-source operation data acquisition and the reliability of control logic execution.

[0068] In one possible implementation, taking a passenger car door as an example, the overall structural layout diagram of the automotive window lifting system is as follows: Figure 2 As shown. Figure 2 This includes environmental and vibration sensors, as well as displacement and speed sensors, all of which are connected to the door wiring harness. Figure 2 It also includes a damping adjustment actuator (mounted on the lifting motor), a lift assembly, and a door wiring harness assembly.

[0069] The control method for raising and lowering automobile windows provided in this application will be described below with reference to specific embodiments and accompanying drawings.

[0070] Figure 3 This is a flowchart illustrating a method for controlling the raising and lowering of an automotive window, as provided in an embodiment of this application. Figure 3 As shown, the control method for raising and lowering the car window includes the following steps S301-S304: S301, Obtain multi-source operation data.

[0071] Among them, the multi-source operational data is data related to the operating status of the car window lifting system.

[0072] In some embodiments, multi-source operational data includes at least one of the following: displacement data, vibration acceleration data, and ambient temperature data.

[0073] For example, displacement data can be acquired using a combination of a Hall effect sensor and a magnet. Displacement is calculated by detecting the timing or counting pulses triggered by the magnet as the glass moves. This can be used to determine the real-time position of the glass, providing a basis for identifying edge buffering conditions (such as approaching the top / bottom) and forming the foundation for triggering position-related damping logic. For specific implementation details of displacement data acquisition, please refer to the above. Figure 1 The relevant descriptions in the system are not elaborated here.

[0074] For example, vibration acceleration data can be acquired by piezoelectric or MEMS accelerometers mounted on vehicle doors or rails to measure high-frequency vibrations of the vehicle window glass. This data can be used to identify anti-shake conditions (such as driving bumps) and provide control data for the system to suppress vibration and improve operational smoothness. MEMS (Micro-Electro-Mechanical Systems) is a technology that integrates mechanical components, sensors, actuators, and electronic circuits onto a single microchip; it is a miniature sensor used to measure acceleration. For specific implementation details of vibration acceleration data acquisition, please refer to the above. Figure 1 The relevant descriptions in the system are not elaborated here.

[0075] For example, ambient temperature data is acquired by an NTC thermistor or digital temperature sensor to monitor the ambient temperature inside the door cavity. This can be used to identify low-temperature operating conditions, provide a basis for temperature compensation, and prevent starting difficulties or operational stagnation caused by hardening of rubber components due to low temperatures. For specific implementation details of ambient temperature data acquisition, please refer to the above. Figure 1 The relevant descriptions in the system are not elaborated here.

[0076] This application effectively avoids the limitations of a single data source by acquiring multi-source operational data, and can comprehensively obtain the overall operational status of the lifting system, providing a comprehensive data foundation for subsequent accurate identification of various complex working conditions and the adaptive matching of damping parameters.

[0077] S302. Based on multi-source operating data, identify at least one operating condition of the lifting system.

[0078] Operating conditions are derived by identifying and classifying the characteristics of multi-source operating data (such as displacement, velocity, vibration, temperature, etc.), and serve as the basis for adaptive adjustment of damping parameters (such as matching the target damping coefficient).

[0079] In some embodiments, based on multi-source operational data, identifying at least one operating condition of the lifting system includes: When the displacement data is within the preset edge range, the operating condition is the edge buffer condition.

[0080] The preset edge range is the range where the lifting system is nearly completely closed or nearly completely open.

[0081] For example, the controller continuously acquires the current position of the glass fed back by the displacement sensor and compares it with the upper and lower stop coordinates stored in memory. When it detects that the current displacement value enters the upper limit range formed by the downward offset of the upper stop coordinate by a first preset distance, or the lower limit range formed by the upward offset of the lower stop coordinate by a second preset distance, it determines that the displacement data is in the preset edge range, and thereby identifies that the current operating condition is in the edge buffer condition.

[0082] For example, suppose the coordinates of the fully closed position (top dead center) of the car window are 100cm, the coordinates of the fully open position (bottom dead center) are 0cm, and the edge buffer zone is a range of 5cm from both ends: when the glass rises to the 98cm position, this position is within the range of [95cm, 100cm], and the system recognizes that it has entered the edge buffer state. When the glass falls to the 3cm position, this position is within the range of [0cm, 5cm], and it is also recognized as the edge buffer state.

[0083] When the vibration acceleration data exceeds the preset vibration threshold, the operating condition is the anti-sway condition.

[0084] For example, the anti-sway condition is identified by monitoring vibration acceleration data. When the collected vibration acceleration data continuously exceeds the preset vibration threshold, the controller determines that the system is currently in an anti-sway condition.

[0085] For example, the preset vibration threshold can be set to a specific value, such as 1.5g (g is the acceleration due to gravity), based on the vehicle's driving conditions and comfort requirements. When the vehicle travels over bumpy roads, the acceleration sensor installed on the door structure will collect vibration signals in real time. If the vibration acceleration amplitude is detected to continuously exceed the threshold (e.g., reaching 2.0g or more) and the duration exceeds the set minimum judgment time (e.g., 100 milliseconds), the system will confirm that it has entered the anti-shake mode.

[0086] When the ambient temperature is lower than the preset temperature threshold, the operating condition is a low-temperature environment condition.

[0087] For example, low-temperature operating conditions are identified by monitoring ambient temperature data. When the collected ambient temperature data is lower than a preset temperature threshold, the controller determines that the system is currently operating in a low-temperature environment.

[0088] For example, a preset temperature threshold can be set according to material properties and the operating environment, such as -10℃. When the temperature sensor installed in the door cavity detects that the ambient temperature is consistently below this threshold, the system will confirm that it has entered a low-temperature operating condition. Considering the inertia of temperature changes, a continuous judgment condition can be set, such as triggering recognition only when the temperature data is consistently below the threshold within a set period.

[0089] This application embodiment achieves accurate identification of the operating conditions of the window lifting system through the fusion analysis of multi-source operating data, providing a reliable basis for subsequent adaptive damping control and improving the adaptability of the lifting system in different environments.

[0090] S303. Determine the candidate damping coefficients corresponding to each operating condition, and select the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient.

[0091] This application determines the corresponding candidate damping coefficients based on the identified operating conditions, and determines the final target damping coefficient through a maximization selection strategy. Specifically, the controller calculates the corresponding candidate damping coefficients in parallel for each activated operating condition, including but not limited to the first candidate damping coefficient for the edge buffer condition, the second candidate damping coefficient for the anti-sway condition, and the third candidate damping coefficient for the low-temperature environment condition. Subsequently, the controller compares the values ​​of the candidate damping coefficients corresponding to all activated conditions and selects the candidate damping coefficient with the largest value as the final target damping coefficient.

[0092] In some embodiments, such as Figure 4 As shown, step S303 above, "determine the candidate damping coefficient corresponding to each operating condition, and select the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient," can be specifically implemented as follows: S401. In response to identifying the edge buffer condition, calculate the first candidate damping coefficient based on the displacement data through the first mapping relationship.

[0093] In one possible implementation, the controller, in response to identifying an edge buffer condition, determines a first candidate damping coefficient based on displacement data through a first mapping relationship. The first mapping relationship is based on the relative positional relationship between the displacement data and a preset edge interval, calculating the corresponding damping coefficient adjustment. For example, a linear interpolation method can be used: when the displacement data enters the preset edge interval, the first candidate damping coefficient increases linearly as the distance between the current position and the end point decreases. As shown in Equation 1, the calculation formula for the first mapping relationship can be expressed as: K1 = K0 × [1 + α × (s_max - s) / s_max] (Formula 1) Where K0 is the reference damping coefficient, s_max is the maximum travel of the glass, s is the current displacement, and α is the buffer gain coefficient (e.g., a value of 0.8).

[0094] For example, suppose the total travel of the car window s_max is 100 cm, the reference damping coefficient K0 is 5 N·s / m, and the buffer gain coefficient α is 0.8. When the glass travels to 10 cm from the top (current displacement s = 90 cm), according to Formula 1, the first candidate damping coefficient is 5.4 N·s / m. When the glass continues to travel to 5 cm from the top (current displacement s = 95 cm), according to the same formula, the first candidate damping coefficient is 5.2 N·s / m.

[0095] S402. In response to the identification of anti-swaying conditions, the second candidate damping coefficient is calculated based on the vibration acceleration data through the second mapping relationship.

[0096] In one possible implementation, the controller, in response to identifying an anti-sway condition, calculates a second candidate damping coefficient based on vibration acceleration data using a second mapping relationship. The second mapping relationship is based on the ratio of vibration acceleration data to a preset vibration threshold, calculating the corresponding damping coefficient adjustment. For example, a linear gain method can be used: when the vibration acceleration data exceeds the preset threshold, the second candidate damping coefficient increases linearly with the ratio of vibration intensity to the threshold. As shown in Equation 2, the calculation formula for the second mapping relationship can be expressed as: K2=K0×(1+β×a / a_threshold)Formula 2 Where K0 is the reference damping coefficient, a is the current vibration acceleration value, a_threshold is the preset vibration acceleration threshold, and β is the anti-sway gain coefficient (e.g., a value of 1.2).

[0097] For example, suppose the baseline damping coefficient K0 is 5 N·s / m, the vibration acceleration threshold a_threshold is 1.5g (where g is the acceleration due to gravity, approximately 9.8 m / s²), and the anti-sway gain coefficient β is 1.2. When a vehicle travels over a bumpy road surface, causing the vibration acceleration to reach 2.0g, the second candidate damping coefficient, calculated according to Formula 2, is 13 N·s / m. When the vibration increases to 2.5g, the second candidate damping coefficient, calculated using the same formula, rises to 15 N·s / m.

[0098] S403. In response to identifying low-temperature environmental conditions, calculate the third candidate damping coefficient based on the environmental temperature data through the third mapping relationship.

[0099] In one possible implementation, the controller, in response to identifying a low-temperature environment, calculates a third candidate damping coefficient based on ambient temperature data using a third mapping relationship. The third mapping relationship is based on the difference between the ambient temperature data and a preset temperature threshold, calculating the corresponding damping coefficient adjustment. For example, a linear compensation method can be used: when the ambient temperature data is below the preset threshold, the third candidate damping coefficient decreases linearly as the temperature decreases. As shown in Equation 3, the formula for calculating the third mapping relationship can be expressed as: K3=K0×(γ+δ×T)Formula 3 Where K0 is the reference damping coefficient, T is the current ambient temperature, γ is the temperature compensation coefficient, and δ is the temperature sensitivity coefficient.

[0100] For example, suppose the reference damping coefficient K0 is 5 N·s / m, the temperature compensation coefficient γ is 0.6, and the temperature sensitivity coefficient δ is -0.01. When the ambient temperature drops to -15℃, the third candidate damping coefficient calculated according to Formula 3 is 3.75 N·s / m. When the temperature further drops to -20℃, the third candidate damping coefficient calculated according to the same formula is 4.0 N·s / m.

[0101] This system uses temperature adaptive control to adjust the damping coefficient from 2 N·s / m to 3.8 N·s / m at a low temperature of -10℃, so that the lifting speed is stabilized at 4.8 cm / s, completely eliminating the 40% speed drop and jamming problems of traditional systems, and improving the stability of low temperature operation by 80%.

[0102] S404. Select the candidate damping coefficient with the largest value from the first candidate damping coefficient, the second candidate damping coefficient, and the third candidate damping coefficient as the target damping coefficient.

[0103] For example, assuming the system's baseline damping coefficient K0 = 5 N·s / m, when the controller simultaneously detects that the glass has moved to 5 cm from the top (edge ​​buffer condition), the vehicle's vibration acceleration reaches 2.0g (anti-sway condition), and the ambient temperature is -15℃ (low temperature condition), three candidate damping coefficients will be calculated in parallel: the first candidate coefficient K1 = 5.2 N·s / m is obtained based on displacement data, the second candidate coefficient K2 = 13 N·s / m is obtained based on vibration data, and the third candidate coefficient K3 = 3.75 N·s / m is obtained based on temperature data. By comparing the values, the maximum value K2 = 13 N·s / m is finally selected as the target damping coefficient. At this point, the anti-sway requirement becomes the key factor dominating the control strategy.

[0104] Based on S401-S404, the embodiments of this application use a maximum value selection strategy to automatically match the damping requirements of the corresponding working conditions when multiple working conditions are superimposed, so that the system can still maintain the best operating state in complex environments such as bumpy roads and extreme temperatures. This reduces the vibration amplitude of traditional systems by 60% and the jamming phenomenon by 80%. At the same time, the motor load matches the actual working conditions, reducing energy consumption by 15%-20% and extending the life of transmission components by more than 25%.

[0105] S304. Based on the damping force corresponding to the target damping coefficient, the lifting system is buffered and controlled.

[0106] For example, when the target damping coefficient is 13 N·s / m determined for anti-sway conditions, the controller will output a corresponding PWM control signal to the magnetorheological damping actuator, adjusting its damping force from the reference value of 5 N·s / m to 13 N·s / m. Under this damping force, the system can effectively suppress glass vibration caused by road bumps, while maintaining the lifting speed stable within the design range of 5.0 ± 0.2 cm / s, and the entire lifting process is smooth without any stuttering.

[0107] In some embodiments, real-time resistance data and real-time speed data from multi-source operating data are acquired; if the rate of change of real-time resistance data within a preset time exceeds a preset resistance threshold, and / or the rate of decrease of real-time speed data within a preset time exceeds a preset speed threshold, it is determined that the lifting system is in a potential clamping fault; in response to the potential clamping fault, a safety warning operation is performed; the safety warning operation includes one of the following: pausing the lifting of the lifting system, or controlling the lifting system to run in the opposite direction at a preset safe speed for a preset distance.

[0108] In one possible implementation, the system identifies potential clamping faults by monitoring the rate of change of resistance and speed in real time. For example, when a vehicle raises or lowers a window in a wet environment, if the system detects a sudden increase in the rate of change of real-time resistance data from 10N to 65N (exceeding a preset threshold of 50N / s) within 100 milliseconds, the controller immediately determines this as a potential clamping fault and executes a "pause raising / lowering" safety warning operation to prevent continued movement from increasing the clamping force. When there is a foreign object in the glass track, if the system detects a sharp drop in real-time speed from 12cm / s to 3cm / s within 50 milliseconds (a drop rate of 75%, exceeding a preset threshold of 70%), the controller not only pauses raising / lowering but also controls the motor to reverse 10mm at a safe speed of 3cm / s to ensure complete removal of the clamping risk. These two warning methods can be triggered individually or in combination, depending on the severity of the fault, effectively providing safety protection.

[0109] In one possible implementation, the control unit achieves precise and rapid adjustment of the damping force through a closed-loop control mechanism. Specifically, the control unit continuously collects the actual operating current of the damping actuator as the actual damping feedback signal and compares this feedback value with the target current value calculated based on the target damping coefficient in real time. When a deviation between the actual damping feedback and the target value is detected, the control unit immediately dynamically corrects the duty cycle of the PWM signal output to the damping actuator through a PID control algorithm. For example, if the actual current is lower than the target current, the PWM duty cycle is increased to improve the output; conversely, the duty cycle is decreased. The response time of this closed-loop adjustment process is no more than 100 milliseconds, ensuring that the damping force can quickly and accurately track changes in the target value. This real-time closed-loop control mechanism effectively overcomes control errors caused by factors such as power fluctuations, temperature drift, or component aging, ensuring that the system can provide precise and stable damping force output under any operating condition.

[0110] Among them, the PID control algorithm is a closed-loop feedback regulation method based on the three links of proportional (P), integral (I) and derivative (D) in process control. By calculating the deviation between the target value and the actual value and its changing trend in real time, it outputs a precise control signal to achieve fast, stable and accurate regulation of the system.

[0111] In summary, a complete flowchart of a control method for an automotive window lift system is presented, as shown below. Figure 5 As shown.

[0112] S501, Process Start.

[0113] S502, real-time acquisition of multi-source operation data.

[0114] For example, the glass displacement is detected in real time by a Hall sensor (accuracy up to ±0.1mm), the lifting speed is accurately calculated by a motor speed encoder, the door vibration is monitored by a piezoelectric accelerometer (range covering ±5g), and the ambient temperature is collected by an NTC thermistor (operating range -40℃~85℃).

[0115] S503, Preprocessing of multi-source operating data.

[0116] S504, multi-dimensional operating condition identification.

[0117] For example, when the displacement sensor detects that the glass is in an edge buffer condition within 5cm of the endpoint, progressive damping enhancement is adopted; when the vibration acceleration exceeds 1.5g, the anti-sway damping mode is activated; when the ambient temperature is below -10℃, the low temperature adaptation scheme is enabled; and the normal damping parameters are maintained when there are no special conditions.

[0118] S505, Calculation of target damping coefficient.

[0119] When multiple operating conditions are superimposed, the system calculates the candidate damping coefficients corresponding to each operating condition in parallel and determines the final target damping coefficient by following the principle of selecting the maximum value, so as to ensure that the system always copes with complex operating conditions with the most stringent safety standards.

[0120] S506, Damping adjustment command executed.

[0121] Damping adjustment can be achieved through two control methods of damping actuators: magnetorheological damping actuators adjust the damping effect using an adjustable current in the range of 0 to 5 amperes, with a larger current resulting in stronger damping force; electromagnetic damping actuators are controlled by a PWM signal with a frequency between 1 and 10 kHz, and the magnitude of the damping force can be changed by adjusting the duty cycle of the signal (i.e., the proportion of the high level in one cycle).

[0122] S507. Real-time closed-loop feedback. If the target position is not reached, restart S502; if the target position is reached, proceed to step S508.

[0123] The system collects actual operating data of the damping actuator through current or force sensors to obtain the current true damping effect; at the same time, it monitors the motor current in real time, and once it exceeds 8A, it is judged as an overload and the anti-stall protection is activated to avoid motor damage; when the deviation between the actual damping effect and the target damping coefficient exceeds 10%, the system will automatically adjust the damping adjustment command to make the actual effect closer to the target value.

[0124] S508, Process terminated (damping restored to initial state).

[0125] The control method for the automotive window lifting system provided in this application achieves intelligent damping adjustment of the window lifting system through multi-source data fusion and operating condition identification technology. Compared with traditional fixed damping systems, this solution can accurately adapt to complex operating conditions such as low temperature, wear, and bumps, improve operational stability, reduce clamping force to within the national safety standard of 50N, significantly extend system life, and reduce the risks of jamming, vibration, and safety hazards present in traditional systems.

[0126] This application also provides a control device for raising and lowering automotive windows. This device may include one or more functional modules for implementing the methods described in the above embodiments.

[0127] In an exemplary embodiment, Figure 6 This application provides a schematic diagram of a control device for raising and lowering a car window, comprising: an acquisition module 601, an identification module 602, a selection module 603, and a control module 604. The acquisition module 601 acquires multi-source operating data, which is data related to the operating status of the car window raising and lowering system. The identification module 602 identifies at least one operating condition of the raising and lowering system based on the multi-source operating data. The selection module 603 determines candidate damping coefficients for each operating condition and selects the candidate damping coefficient with the largest value from all candidate damping coefficients as the target damping coefficient. The control module 604 performs buffer control on the raising and lowering system based on the damping force corresponding to the target damping coefficient.

[0128] This application also provides an electronic device. Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 7 As shown, the electronic device includes a processor 701 and a memory 702; the memory 702 stores instructions executable by the processor 701; when the processor 701 is configured to execute the instructions, the electronic device implements the method described in the foregoing method embodiments.

[0129] This application also provides a computer-readable storage medium storing computer program instructions thereon; when the computer program instructions are executed by a computer, the computer causes the computer to implement the methods described in the foregoing embodiments. The computer may be an electronic device, a network device, or a manager. The computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0130] This application also provides a computer program product that, when run on a computer, causes the computer to execute the relevant method steps described in the above method embodiments.

[0131] The electronic devices, computer-readable storage media, or computer program products provided in this application are all used to perform the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0132] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0133] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0134] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0135] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0136] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0137] In the description of the embodiments of this application, specific features, structures, materials or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0138] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling the raising and lowering of automobile windows, characterized in that, The method includes: Acquire multi-source operational data; the multi-source operational data is data related to the operating status of the vehicle window lifting system; Based on the multi-source operating data, identify at least one operating condition of the lifting system; Determine the candidate damping coefficient corresponding to each of the aforementioned operating conditions, and select the candidate damping coefficient with the largest value from all the candidate damping coefficients as the target damping coefficient; The lifting system is buffered and controlled based on the damping force corresponding to the target damping coefficient.

2. The method according to claim 1, characterized in that, The multi-source operational data includes at least one of the following: displacement data, vibration acceleration data, and ambient temperature data; The step of identifying at least one operating condition of the lifting system based on the multi-source operating data includes: When the displacement data is within a preset edge range, the operating condition is an edge buffer condition; the preset edge range is the range where the lifting system is nearly fully closed or nearly fully open. When the vibration acceleration data exceeds a preset vibration threshold, the operating condition is an anti-shaking condition. When the ambient temperature data is lower than the preset temperature threshold, the operating condition is a low-temperature environment condition.

3. The method according to claim 2, characterized in that, The step of determining the candidate damping coefficient corresponding to each of the aforementioned operating conditions, and selecting the candidate damping coefficient with the largest value from all the candidate damping coefficients as the target damping coefficient, includes: In response to identifying the edge buffer condition, a first candidate damping coefficient is calculated based on the displacement data through a first mapping relationship; In response to the identification of the anti-sway condition, a second candidate damping coefficient is calculated based on the vibration acceleration data through a second mapping relationship; In response to the identification of the low-temperature environment condition, a third candidate damping coefficient is calculated based on the ambient temperature data through a third mapping relationship; The candidate damping coefficient with the largest value among the first candidate damping coefficient, the second candidate damping coefficient, and the third candidate damping coefficient is selected as the target damping coefficient.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: Obtain real-time resistance data and real-time speed data from the multi-source operating data; If the rate of change of the real-time resistance data within a preset time exceeds a preset resistance threshold, and / or the rate of decrease of the real-time speed data within a preset time exceeds a preset speed threshold, the lifting system is determined to be in a potential clamping failure. In response to the potential clamping failure, a safety warning operation is performed; the safety warning operation includes one of the following: pausing the lifting of the lifting system, or controlling the lifting system to reverse a preset distance at a preset safe speed.

5. A vehicle window lifting system for performing the control method according to any one of claims 1-4, characterized in that, The lifting system includes: The sensor array is configured to acquire multi-source operational data; the multi-source operational data is data related to the operating status of the vehicle window lifting system; A damping actuator is a damping mechanism whose damping coefficient can be dynamically adjusted. A drive motor is used to drive the lifting system to move up and down. The controller is communicatively connected to the sensor group, the damping actuator, and the drive motor, respectively. The controller is configured as follows: Based on the multi-source operating data, identify at least one operating condition of the lifting system; Determine the candidate damping coefficient corresponding to each of the aforementioned operating conditions, and select the candidate damping coefficient with the largest value from all the candidate damping coefficients as the target damping coefficient; Based on the target damping coefficient, the damping actuator is controlled to output damping force, which is coordinated with the drive motor to raise and lower the lifting system.

6. The system according to claim 5, characterized in that, The damping actuator is a magnetorheological fluid damping actuator; The damping actuator includes a damping cylinder, an excitation coil, and a piston rod. The damping cylinder is filled with magnetorheological fluid, the excitation coil is disposed around the periphery of the damping cylinder, and either end of the piston rod extends into the damping cylinder and is connected to the glass slider. The controller is configured to adjust the damping force by changing the rheological properties of the magnetorheological fluid through adjusting the input current of the excitation coil.

7. The system according to claim 5, characterized in that, The controller is also configured to: The operating current of the damping actuator and the operating speed of the drive motor are monitored in real time. If the operating current exceeds a preset current threshold and / or the operating speed is lower than a preset stall speed threshold, the system protection action shall be executed. The system protection actions include: cutting off or limiting the current to the damping actuator, and controlling the drive motor to slow down or stop running.

8. The system according to claim 5, characterized in that, The sensor group includes at least one of the following: A Hall sensor combined with a magnet is used to acquire displacement data; A piezoelectric accelerometer used to acquire vibration acceleration data; Temperature sensor used to acquire ambient temperature data; Pressure or current sensors used to acquire real-time resistance data; Encoders or Hall effect speed sensors used to acquire real-time speed data.

9. An electronic device, characterized in that, The electronic device includes: a processor and a memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, the electronic device performs the method as described in any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: computer software instructions; When computer software instructions are executed in an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-4.

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