Vehicle window control system testing method and vehicle window control system testing device

Abstract

The invention provides a vehicle window control system testing method and a vehicle window control system testing device, and the method comprises the steps: transmitting a control instruction to a to-be-tested vehicle window control system, so as to drive a vehicle window motor in the to-be-tested vehicle window control system to operate; synchronously acquiring a current signal of the car window motor in the operation process and a digital signal output by a digital pulse channel of the car window control system to be tested; identifying the detection type of the to-be-detected vehicle window control system based on the current signal and the digital signal; according to the identified detection type, loading a corresponding test case from a preset test case library; and executing the test case, and generating a test result of the to-be-tested vehicle window control system based on test data collected in the execution process. In the mode, the vehicle window detection type can be automatically identified, and the adaptive test strategy is executed, so that the full-process automation of the vehicle window control system test is realized, the equipment cost is reduced, and the test efficiency is improved.

Description

Technical Field

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

[0002] With the development of automotive electronics technology, power window systems with anti-pinch function have become an important part of automobiles. Currently, mainstream anti-pinch window control systems are mainly divided into two categories based on their position detection principles: ripple current detection type based on current commutation ripple counting, and Hall sensor detection type based on physical sensor output pulse signals.

[0003] In testing automotive window control systems, existing methods typically rely on manual operation or the use of incompatible, independent testing equipment. Testers must use handheld tools or simple oscilloscopes to perform discrete tests on different types of windows. Because ripple windows and Hall effect windows exhibit drastically different signal characteristics, existing testing platforms cannot achieve hardware and logic universality. This often necessitates building two independent testing environments for specific products, and manual reconfiguration of test plans is required when switching products on the production line. This not only increases equipment investment costs but also severely limits the level of automation and data consistency in testing. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a testing method and a testing device for a vehicle window control system. By synchronously acquiring the current signal of the window motor and the digital signal of the digital pulse channel and performing feature analysis to automatically identify the window detection type, the device can call and execute test strategies adapted to ripple current detection type or Hall sensor detection type from a preset test case library, thereby realizing full automation of the testing process of the vehicle window control system, reducing equipment costs and improving testing efficiency.

[0005] Firstly, this application provides a testing method for a vehicle window control system, comprising: Send control commands to the window control system under test to drive the window motor in the window control system under test.

[0006] The current signal of the window motor during operation and the digital signal output by the digital pulse channel of the window control system under test are collected simultaneously.

[0007] Based on current signals and digital signals, the detection type of the window control system under test is identified; the detection types include ripple current detection type and Hall sensor detection type.

[0008] Based on the identified detection type, load the corresponding test cases from the preset test case library.

[0009] Execute test cases and generate test results for the window control system under test based on the test data collected during execution.

[0010] In an optional implementation, the step of identifying the detection type of the window control system under test based on current signals and digital signals includes: Perform time-domain feature analysis on digital signals to calculate the number of effective pulses within a preset time window and the consistency parameter of the pulse period.

[0011] If the number of valid pulses is greater than or equal to the preset pulse number threshold, and the consistency parameter meets the preset stability condition, the detection type is determined to be Hall sensor detection type.

[0012] If the number of effective pulses is less than the preset pulse number threshold, the current signal is frequency domain transformed to obtain spectrum data; the spectrum data is searched within the preset motor commutation frequency range, and if a characteristic spectrum component with an energy amplitude exceeding the preset background noise threshold is detected, the detection type is determined to be ripple current detection type.

[0013] In an optional implementation, the step of determining the detection type as ripple current detection further includes: Extract the center frequency of the characteristic spectral components.

[0014] Calculate the slope of the center frequency change during the operation of the window motor.

[0015] If the slope of the change is consistent with the preset motor speed increase curve, the detection type is determined to be ripple current detection type.

[0016] In an optional implementation, the step of loading the corresponding test case from a preset test case library based on the identified detection type includes: When the detection type is Hall sensor detection, load the first test case set and common test cases; the first test case set includes: Hall pulse step loss detection, pulse duty cycle consistency test, and absolute position control accuracy test based on pulse counting; common test cases include anti-pinch function test, power fluctuation stress test, window position control accuracy test, and lifting time test.

[0017] When the detection type is identified as ripple current detection, the second test case set and common test cases are loaded. The second test case set includes: ripple count cumulative error test, ripple signal-to-noise ratio test under power supply voltage drop conditions, and stall threshold calibration test based on current amplitude change.

[0018] In an optional implementation, the steps of executing test cases and generating test results for the window control system under test based on the test data collected during execution include: When the detection type is Hall sensor detection, the first test case set is executed. Based on the digital signals collected during the execution of the first test case set, the pulse loss rate, pulse duty cycle variance, and positioning deviation based on pulse count are calculated to generate Hall performance evaluation results.

[0019] When the detection type is ripple current detection, the second test case set is executed. Based on the current signal collected during the execution of the second test case set, the cumulative error rate of ripple count, the ripple signal-to-noise ratio during the power supply voltage drop, and the current amplitude when the stall is triggered are calculated to generate ripple performance evaluation results.

[0020] In an optional implementation, when the test case is an anti-pinch function test, the steps of executing the test case and generating the test results of the window control system under test based on the test data collected during the execution include: When the detection type is Hall sensor detection, the external mechanical loading mechanism is controlled to apply physical resistance to the window travel of the window control system under test, and the readings of the external force sensor and the position data in the digital signal are collected simultaneously. The peak clamping force and response time when the anti-pinch is triggered are calculated to generate Hall anti-pinch performance test results.

[0021] When the detection type is ripple current detection, the control power supply equipment applies current interference or reverse electromagnetic torque to the window motor, monitors the moment of sudden change in the amplitude of the current signal, and calculates the time difference from the application of interference to the reversal of the window motor to generate ripple anti-pinch performance test results; the application of current interference or reverse electromagnetic torque is based on a preset nonlinear impedance model, which is used to simulate the torque change process when a flexible object is clamped.

[0022] In an optional implementation, when the test case is a power fluctuation stress test, the steps of executing the test case and generating the test results of the window control system under test based on the test data collected during the execution include: The power supply equipment that supplies power to the window control system under test is controlled to perform voltage change operations; voltage change operations include voltage transient drops or voltage surges.

[0023] When the detection type is Hall sensor detection, the working status of the window control system under test is monitored during voltage changes. The system identifies whether there is a power supply interruption or controller reset in the working status, and generates Hall sensor adaptability test results based on the first identification result.

[0024] When the detection type is ripple current detection, the working status of the window control system under test is monitored during voltage changes. The system identifies whether the window motor stops or the controller resets during the working status, and generates ripple power supply adaptability test results based on the second identification result.

[0025] In an optional implementation, after the steps of executing test cases and generating test results for the window control system under test based on the test data collected during execution, the method further includes: The test results, the original waveform data of the current signal, and the original data of the digital signal are correlated and packaged to generate an initial data package.

[0026] Assign data identifiers to the initial data, obtain the data to be stored, and store the data to be stored in the preset database.

[0027] Secondly, this application provides a testing device for a vehicle window control system, including: a data acquisition device, a communication device, and a control module.

[0028] The data acquisition device is configured to connect to the signal output terminal of the window control system under test, so as to synchronously acquire the current signal of the window motor of the window control system under test and the digital signal output by the digital pulse channel of the window control system under test.

[0029] A communication device configured to connect to the communication bus of the window control system under test in order to send control commands.

[0030] The control module, connected to the data acquisition device and the communication device respectively, is configured to perform a test method for the window control system as described in any of the aforementioned embodiments.

[0031] In an optional embodiment, the device further includes: a power supply, an external mechanical loading mechanism, a current sensor, and a signal conditioning circuit.

[0032] The current sensor is installed in the power supply circuit of the window motor and connected to the data acquisition device to collect current signals.

[0033] The signal conditioning circuit is located between the digital pulse channel and the data acquisition device to filter and shape the digital signal.

[0034] The power supply device is connected to the control module and is configured to supply power to the window control system under test in response to the instructions of the control module and perform voltage change operations.

[0035] An external mechanical loading mechanism is connected to the control module and is configured to apply physical resistance during the window travel of the window control system under test in response to instructions from the control module.

[0036] This application provides a testing method and device for a vehicle window control system. By synchronously acquiring the current signal and digital pulse channel signal of the window motor, the type of the vehicle window control system can be automatically and accurately identified based on time-frequency domain characteristics and the slope of change. Based on this, test cases containing specific performance evaluations and common function verifications are adaptively loaded, thereby achieving fully automated testing compatible with multiple technical solutions and improving testing efficiency and equipment utilization. Simultaneously, this application introduces a nonlinear impedance model in the anti-pinch test to simulate the clamping conditions of real flexible objects, monitors specific fault modes for different types of power supply stress tests, and associates and packages the original waveforms and results at the end of the test, thereby improving the realism of the test verification, the accuracy of fault diagnosis, and the traceability of quality data.

[0037] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application are realized and obtained through the structures particularly pointed out in the description, claims and drawings.

[0038] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating the testing method for the vehicle window control system provided in this application embodiment; Figure 2 This is a flowchart of the detection type identification method provided in the embodiments of this application; Figure 3 This is a flowchart of the ripple current detection type determination method provided in the embodiments of this application; Figure 4 A flowchart illustrating the test result storage method provided in this application embodiment; Figure 5 A schematic diagram of a test apparatus for a vehicle window control system provided in an embodiment of this application; Figure 6 A schematic diagram of a test apparatus for another vehicle window control system provided in an embodiment of this application.

[0041] Icons: 1-Data acquisition equipment; 2-Communication equipment; 3-Control module; 4-Power supply equipment; 5-External mechanical loading mechanism; 6-Current sensor; 7-Signal conditioning circuit. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions 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, 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.

[0043] To help those skilled in the art better understand this application, a brief introduction to its application scenarios and design concepts is provided.

[0044] With the continuous improvement of automotive intelligence, anti-pinch systems for power windows have become standard equipment. Currently, the mainstream solutions on the market mainly include ripple windows based on ripple current detection and Hall effect windows based on Hall sensor detection. Ripple windows use current fluctuations generated by motor commutation to calculate position, which is low-cost but susceptible to interference. Hall effect windows use sensor pulse counting, offering high accuracy but at a relatively higher cost.

[0045] Existing testing technologies typically have significant limitations when testing these two types of car windows: First, the testing methods are relatively outdated, relying heavily on manual subjective judgment using tools such as stopwatches and calipers, or using only oscilloscopes for semi-automatic capture, resulting in low testing efficiency and poor consistency of results.

[0046] Secondly, the test platform lacks compatibility. Due to the significant differences in signal characteristics between ripple windows and Hall effect windows, existing technologies often require the construction of two independent test environments for verification, resulting in severe discretization testing. This not only increases equipment investment costs but also makes it difficult to unify evaluation standards between different product lines.

[0047] Finally, the data mining capabilities are weak. Traditional testing often stops at a simple pass or fail judgment, lacking in-depth analysis and electronic archiving of massive waveform data, making it difficult to achieve full life cycle traceability of product quality and root cause analysis of failures.

[0048] Based on this, this application provides a testing method and a testing device for a vehicle window control system. By constructing a unified hardware platform including high-precision data acquisition and a programmable power supply, it can simultaneously acquire the current characteristics and digital pulse signals during vehicle window operation, automatically identify whether the window under test is of the ripple current detection type or the Hall sensor detection type, and automatically call the matching test cases accordingly. This application requires no manual replacement of equipment or reconstruction of the environment; a single system can cover mainstream vehicle window technologies and flexibly meet the production testing needs of multiple products on the same production line. Furthermore, this application establishes a traceable electronic quality archive by packaging and storing the original waveform data, providing strong data support for subsequent design optimization and after-sales analysis.

[0049] To facilitate understanding of this embodiment, the embodiments of this application will be described in detail below.

[0050] This application provides a testing method for a vehicle window control system, referring to... Figure 1 The testing method for the vehicle window control system provided in this application includes: Step S101: Send a control command to the window control system under test to drive the window motor in the window control system under test.

[0051] Here, the testing equipment for the vehicle window control system first needs to establish a communication or control connection with the window control system under test. The window control system under test typically includes a window controller and a window motor.

[0052] Control commands can be sent via bus communication. The test device for the window control system connects to the communication network of the window control system under test via a bus interface card. Control commands are sent in the form of standard messages (such as CAN (Controller Area Network) / LIN (Linux Local Interconnect Network) messages), and the command content includes controlling the window to rise, fall, stop, or automatically raise or lower. The bus protocol here is not limited to CAN or LIN; it can also be automotive Ethernet (such as Some / IP (IP-based scalable service-oriented middleware) protocol) or FlexRay bus.

[0053] Control commands can also be sent based on physical signal simulation. For window controllers that lack a bus interface or are in the early stages of development, the test device for the window control system can use a relay matrix or analog switch circuit to directly apply high and low level signals to the physical button input terminals of the window controller, simulating the user's action of pressing a physical switch, thereby triggering the window motor to run.

[0054] While sending commands, the power supply equipment (such as a programmable DC regulated power supply) in the test device for the window control system supplies power to the window control system under test. The power supply equipment can simulate the voltage output of the vehicle battery, such as the standard operating voltage of 13.5V, or simulate abnormal conditions such as voltage drops and overvoltages according to test requirements, to ensure that the motor can respond to control commands under various power supply environments.

[0055] Step S102: Synchronously acquire the current signal of the window motor during operation and the digital signal output by the digital pulse channel of the window control system under test.

[0056] Here, data is acquired using a high-precision data acquisition card, with a sampling rate that can be set above 100 kS / s to capture the transient ripple details during motor commutation.

[0057] A current sensor is connected in series in the power supply circuit of the window motor. A Hall effect current sensor is preferred, converting the large current into an analog voltage signal (e.g., + / -5V or + / -10V) that can be recognized by the data acquisition card. The current signal reflects the motor's load torque, commutation ripple, and circuit on / off status.

[0058] The window control system under test usually has a reserved signal interface (i.e., digital pulse channel) for feedback of position or speed. The signal output from the digital pulse channel is filtered, level converted or shaped by the signal conditioning circuit before being input to the digital I / O (input / output) port or high-speed counter port of the data acquisition card.

[0059] Regardless of the type of window under test, the test platform defaults to acquiring data from the digital pulse channel. For Hall effect windows, the digital pulse channel will output regular square wave pulses. For ripple windows, the digital pulse channel may output constant high / low levels or irregular noise signals; all of these are considered valid digital signal data and recorded.

[0060] Step S103: Based on the current signal and digital signal, identify the detection type of the window control system under test; the detection types include ripple current detection type and Hall sensor detection type.

[0061] In a preferred embodiment, the time-domain characteristics of the digital signal are first analyzed. The number of valid pulses acquired within a preset time window after motor startup (e.g., within 2 seconds) is calculated, and the consistency parameters (such as variance) of these pulse periods are also calculated. If the number of pulses is sufficient and the period is stable (i.e., the frequency is proportional to the motor speed), it is directly determined to be a Hall sensor detection type.

[0062] If no valid pulse is detected in the digital signal, the frequency domain characteristics of the current signal are further analyzed. A Fast Fourier Transform or Wavelet Analysis is performed on the current signal to convert the time-domain waveform into spectral data. A search is conducted within a preset motor commutation frequency range (e.g., 100Hz to 1kHz, depending on the number of pole pairs and speed of the motor). If a characteristic spectral component with an energy amplitude significantly higher than the background noise is found, and the trend of this characteristic frequency over time matches the acceleration curve during motor startup (i.e., the frequency gradually increases), then it is determined to be a ripple current detection type.

[0063] In another implementation, a machine learning model can be used for identification. A large number of startup current waveforms of different types of car windows are pre-collected, and a one-dimensional convolutional neural network classifier is trained. During testing, the collected current waveform segments are directly input into the model, which outputs the classification result (ripple current detection type, Hall sensor detection type, or unknown type).

[0064] Step S104: Load the corresponding test cases from the preset test case library according to the identified detection type.

[0065] Here, the preset test case library contains dedicated test sets for different technical solutions as well as general common test sets.

[0066] When the identification result is a Hall sensor detection type, the first test case set is automatically loaded. The first test case set focuses on the sensor's signal quality, such as Hall pulse step loss detection, pulse duty cycle consistency test (detecting the uniformity of magnetic ring magnetization), and absolute position control accuracy test based on pulse counting.

[0067] When the identification result is ripple current detection type, the second test case set is automatically loaded. The second test case set focuses on the robustness of the ripple extraction algorithm, such as ripple counting cumulative error test, ripple signal-to-noise ratio test under power supply voltage drop conditions (verifying whether the ripple is submerged in noise under low voltage), and stall threshold calibration test based on current amplitude change.

[0068] Regardless of the type, common test cases will also be loaded, including tests for the entire lifting and lowering process, energy consumption, and anti-pinch functionality. Even for common tests, the specific execution parameters may differ for different types, and the system will automatically match the configuration.

[0069] Step S105: Execute the test cases and generate test results for the window control system under test based on the test data collected during the execution process.

[0070] Here, for ripple signals, a sliding window peak detection algorithm or an adaptive threshold zero-crossing detection algorithm can be used to calculate the number of ripples, and digital filtering can be used to eliminate glitch interference, thereby evaluating the accuracy of the position calculation.

[0071] For Hall signals, edge detection technology is used to calculate the number of pulses and frequency jitter to diagnose whether the sensor is faulty.

[0072] For anti-pinch testing, the system comprehensively analyzes the slope of current jumps or the rate of change of position. In particular, when simulating anti-pinch conditions, the test platform can not only record the reversal time, but also combine a preset nonlinear impedance model (simulating flexible objects such as human arms) to evaluate the protective performance of the car window under complex forces.

[0073] The final test results not only include pass / fail conclusions, but also key performance indicators, labeled raw current / voltage waveforms, and statistical process control data. This data is packaged and associated with unique identifiers (such as product serial numbers) and stored in a database to establish a complete electronic product quality profile, facilitating subsequent quality traceability and batch consistency analysis.

[0074] In one embodiment, reference is made to Figure 2 Step S103 includes the following steps S201-S203.

[0075] Step S201: Perform time-domain feature analysis on the digital signal to calculate the number of effective pulses and the consistency parameter of the pulse period within the preset time window.

[0076] Here, to ensure the accuracy of data analysis and avoid interference from unstable signals at the moment of motor startup, preferably, after sending the drive command to the window control system under test, a delay time (e.g., 500 milliseconds) is set to allow the motor speed to stabilize before data acquisition begins. The data acquisition time window can be set to last for 2 seconds or other durations sufficient to cover the stable operation phase of the motor.

[0077] The system performs time-domain edge detection on the acquired digital pulse channel signals. Specifically, the number of valid pulses can be counted by measuring the number of rising or falling edges within a time window. Simultaneously, to distinguish genuine Hall pulses from random noise interference, the system also needs to calculate the consistency parameter of the pulse period. The consistency parameter characterizes the uniformity of the pulse sequence and can be obtained by calculating the time intervals between adjacent pulses and further determining the variance or standard deviation of these time intervals. If the signal is a regular, uniform square wave pulse sequence, the consistency parameter will exhibit extremely high stability.

[0078] Step S202: If the number of effective pulses is greater than or equal to the preset pulse number threshold, and the consistency parameter meets the preset stability condition, the detection type is determined to be Hall sensor detection type.

[0079] Here, the preset pulse count threshold can be set based on the number of pulses per revolution of the motor and the test window duration, for example, set to 50 pulses. If the number of valid pulses counted exceeds the preset pulse count threshold, and the consistency parameter of the pulse period is less than the preset tolerance range (i.e., the preset stability condition is met), it indicates that there is a regular square wave signal on the digital signal channel that is proportional to the motor speed.

[0080] At this point, it was determined that the window control system under test integrated a Hall sensor, which directly detected the change in magnetic field generated by the rotation of the motor shaft using the Hall element. Therefore, the detection type was determined to be Hall sensor detection type.

[0081] Step S203: If the number of effective pulses is less than the preset pulse number threshold, the current signal is frequency domain transformed to obtain spectrum data; the spectrum data is searched within the preset motor commutation frequency range, and if a characteristic spectrum component with an energy amplitude exceeding the preset background noise threshold is detected, the detection type is determined to be ripple current detection type.

[0082] Here, when the digital signal channel does not detect enough pulses (e.g., the pulse count is 0 or there is only a small amount of noise), it automatically switches to the analysis process of the analog current signal.

[0083] First, the acquired time-domain current signal undergoes frequency-domain transformation. This process can employ either a Fast Fourier Transform (FFT) algorithm or a wavelet analysis algorithm to convert the current waveform into spectral data. To improve analysis efficiency and signal-to-noise ratio, a bandpass filter can be applied before or after the transformation, focusing on specific high-frequency bands where the motor commutation ripple is concentrated, such as the frequency ranges from 5kHz to 15kHz or 10kHz to 20kHz.

[0084] Next, the system searches for significant spectral components within a preset motor commutation frequency range. The system pre-determines or sets a background noise threshold for a silent state (e.g., the noise level corresponding to 0.1A). If the energy amplitude or root mean square current value at a specific frequency point exceeds a set multiple of the background noise threshold (e.g., 3 times), it indicates the presence of periodic ripple components in the current signal generated by the DC motor brush commutation.

[0085] When such a continuous characteristic spectral component in a specific frequency band is detected, it is determined that the window control system under test calculates the position by collecting current ripple, and therefore the detection type is determined to be ripple current detection type.

[0086] In one embodiment, reference is made to Figure 3In step S203, the step of determining the detection type as ripple current detection type also includes the following steps S301-S303.

[0087] Step S301: Extract the center frequency of the characteristic spectral components.

[0088] Here, within a preset bandpass filtering range (e.g., 5kHz to 15kHz or 10kHz to 20kHz frequency band), the spectral peak with the largest energy amplitude is searched.

[0089] The frequency point corresponding to the peak value of the spectrum is the center frequency of the characteristic spectrum component. Since the commutation ripple frequency of a DC brushed motor is directly related to the motor speed, the center frequency physically corresponds to the current real-time speed characteristic of the motor.

[0090] Step S302: Calculate the slope of the center frequency change during the operation of the window motor.

[0091] Here, because the window motor needs to undergo a physical acceleration process (i.e., the start-up transient) to reach a stable operating speed from a standstill, its rotational speed gradually increases over time. According to the physical characteristics of a DC motor, the ripple frequency is proportional to the rotational speed; therefore, the center frequency of the actual ripple signal should also show a corresponding upward trend on the time axis.

[0092] Specifically, within a specific time period after motor startup (e.g., within a few hundred milliseconds after startup), the center frequency values ​​at multiple moments are continuously extracted to form a frequency trajectory curve that varies with time. Then, the slope of this frequency trajectory curve (i.e., the rate of frequency change) is calculated using differential calculations or linear fitting algorithms. The slope reflects how quickly the motor speed is established.

[0093] Step S303: If the slope of change is consistent with the preset motor speed increase curve, the detection type is determined to be ripple current detection type.

[0094] In a real-world automotive electrical environment, there may be fixed-frequency noise sources such as switching power supply noise and electromagnetic interference. Judging solely by the frequency spectrum amplitude might lead to these high-energy fixed-frequency noises being misidentified as motor ripple.

[0095] Therefore, the calculated frequency change slope is compared with the preset motor speed rise curve. The preset speed rise curve is a reference model calibrated based on the motor's inherent mechanical time constant and load characteristics.

[0096] If the calculated slope of change indicates that the center frequency rises dynamically over time, and the rising trend matches the preset model (i.e., conforms to the physical laws of motor starting), then it proves that the spectral component is indeed a ripple signal generated by motor rotation and brush commutation, rather than external static noise, confirming that the detection type of the window control system under test is ripple current detection type.

[0097] In one embodiment, step S104 includes: When the detection type is Hall sensor detection, load the first test case set and common test cases; the first test case set includes: Hall pulse step loss detection, pulse duty cycle consistency test, and absolute position control accuracy test based on pulse counting; common test cases include anti-pinch function test, power fluctuation stress test, window position control accuracy test, and lifting time test.

[0098] Here, the first test case set is designed for a window system with a physical position sensor, and the test items included are designed to verify the integrity of the sensor signal and the accuracy of the position calculation.

[0099] Hall effect pulse step loss detection: The digital pulse channel is monitored in real time during the operation of the vehicle window to detect any interruptions or abnormal loss of pulse sequences. If the pulses suddenly stop or the count falls below the theoretical value while the motor is running continuously, it usually indicates a sensor malfunction or poor wiring harness contact.

[0100] Pulse duty cycle consistency test: This test analyzes the width and interval of continuous pulses to verify the uniformity of magnetization of the magnetic ring and the output stability of the Hall element. Unexpected and severe fluctuations in pulse frequency or excessive duty cycle deviation will be considered abnormal signal quality.

[0101] Absolute position control accuracy test based on pulse counting: Utilizing the high-resolution characteristics of Hall pulses, the window position is calculated using the formula position = (cumulative pulse count / single-cycle pulse count) × lead, and the window is instructed to stop at a specific position (such as a slight opening), verifying whether the deviation between the actual stopping position and the target position is within the allowable range.

[0102] When the detection type is identified as ripple current detection, the second test case set and common test cases are loaded. The second test case set includes: ripple count cumulative error test, ripple signal-to-noise ratio test under power supply voltage drop conditions, and stall threshold calibration test based on current amplitude change.

[0103] Here, the second test case set is designed for a sensorless window system that uses current ripple to calculate position, and the test items it includes focus on verifying the robustness of the algorithm under various operating conditions.

[0104] Ripple count cumulative error test: This test verifies whether the cumulative error of the ripple count after multiple lifting cycles will cause the soft stop position of the window to shift, i.e., it tests the long-term stability of the ripple count.

[0105] Ripple signal-to-noise ratio test under power supply voltage drop conditions: The control power supply equipment simulates a sudden voltage drop (e.g., dropping to 9V). Under this low-voltage condition, the motor current ripple is often weaker and easily overwhelmed by noise. Verify whether the ripple extraction algorithm can still maintain a sufficient signal-to-noise ratio under this condition, so as to clearly separate the effective ripple signal.

[0106] Stall threshold calibration test based on current amplitude variation: By recording the current variation curves of the motor under different loads, the reasonableness of the set stall judgment threshold can be calibrated or verified.

[0107] In addition to the aforementioned dedicated test suites, common test cases are also loaded.

[0108] Anti-pinch function test: Verify whether the window will reverse to protect the object when it encounters an obstacle during its ascent.

[0109] Power supply fluctuation stress test: The programmable power supply is used to perform voltage transient drops or load surges to verify the controller's reset characteristics and function retention capabilities when the power supply is unstable.

[0110] Window position control accuracy test: Verify the consistency of the window stopping at any target position after repeated operation.

[0111] Lifting and lowering time test: Record the time required for the window to go from fully closed to fully open and compare it with the nominal value to evaluate the resistance state of the mechanical system and the performance of the motor.

[0112] In one embodiment, step S105 includes: When the detection type is Hall sensor detection, the first test case set is executed. Based on the digital signals collected during the execution of the first test case set, the pulse loss rate, pulse duty cycle variance, and positioning deviation based on pulse count are calculated to generate Hall performance evaluation results.

[0113] Here, the steps for calculating the pulse loss rate include counting the total number of pulses actually collected during the entire operation of the window motor or a specific time period, and comparing this count with the theoretical number of pulses calculated based on the motor speed and operating time. If discontinuities or missing counts are found in the pulse sequence, the proportion of lost pulses will be calculated. For example, if continuous pulse loss is detected, it can be used to diagnose sensor malfunction or poor wiring harness contact.

[0114] The steps for calculating the pulse duty cycle variance include edge detection of the acquired square wave signal, precise measurement of the high-level duration and low-level duration of each pulse, and calculation of its duty cycle. The frequency uniformity of the pulse signal is evaluated by statistically analyzing the variance or standard deviation of the duty cycle data over a period of time. The frequency uniformity of the pulse signal reflects the consistency of the Hall sensor's magnetic ring magnetization and whether there are any abnormal jitters in the signal.

[0115] The steps for calculating the positioning deviation based on pulse count include: converting the pulse count into physical position using a preset kinematic formula, for example, using the formula: Position = (cumulative pulse count / number of pulses per revolution of the motor) × lead screw. The calculated position value is then compared with the actual physical position reached by the window (which can be calibrated using an external laser rangefinder or a standard limit switch) to obtain the positioning deviation value, thereby verifying the accuracy of the closed-loop control of the window position.

[0116] Based on pulse loss rate, pulse duty cycle variance, and positioning deviation based on pulse count, Hall performance evaluation results including pulse quality score and position control accuracy are generated.

[0117] When the detection type is ripple current detection, the second test case set is executed. Based on the current signal collected during the execution of the second test case set, the cumulative error rate of ripple count, the ripple signal-to-noise ratio during the power supply voltage drop, and the current amplitude when the stall is triggered are calculated to generate ripple performance evaluation results.

[0118] Here, the step of calculating the cumulative error rate of ripple counting includes processing the raw current waveform using a dedicated digital signal processing algorithm, such as applying a sliding window peak detection algorithm or an adaptive threshold zero-crossing detection algorithm to identify and count current ripples, while using a digital filtering algorithm to eliminate glitches. The number of ripples extracted by the algorithm is compared with the actual number of commutator segments rotated by the motor, and the cumulative counting error is calculated after multiple rising and falling cycles to evaluate the long-term stability of the position estimation.

[0119] The steps for calculating the ripple signal-to-noise ratio (SNR) during power supply voltage dips include performing frequency domain analysis or time domain feature extraction on the weak current signal acquired during low-voltage (e.g., 9V) testing, and calculating the ratio of the energy amplitude of the ripple signal component to the background noise amplitude (i.e., the SNR). The SNR is used to assess whether the ripple signal can still be effectively separated to maintain functionality under harsh power supply conditions.

[0120] The steps for calculating the current amplitude triggered by stall include real-time monitoring of the root mean square or peak value of the current signal during simulated stall or anti-pinch tests. When a sharp increase in current amplitude is detected and exceeds a dynamic threshold (e.g., 1.5 times the stable operating current), the current amplitude data is recorded. This current amplitude data is used to calibrate or verify whether the stall detection logic of the system under test conforms to design specifications.

[0121] Based on the cumulative error rate of ripple counting, the ripple signal-to-noise ratio during power supply voltage drops, and the current amplitude when stall is triggered, a ripple performance evaluation result containing algorithm robustness and electrical characteristic data is generated.

[0122] Whether it is a ripple current detection type or a Hall sensor detection type, the generated test results are compiled into a detailed test report, which not only includes the aforementioned quantitative key performance indicators, but also the pass or fail judgment, the original waveform of current and / or voltage, and statistical process control data.

[0123] In one embodiment, when the test case is an anti-pinch function test, step S105 includes: When the detection type is Hall sensor detection, the external mechanical loading mechanism is controlled to apply physical resistance to the window travel of the window control system under test, and the readings of the external force sensor and the position data in the digital signal are collected simultaneously. The peak clamping force and response time when the anti-pinch is triggered are calculated to generate Hall anti-pinch performance test results.

[0124] Here, during the window's upward movement, the control mechanism inserts a standard force gauge or force sensor (with a range of, for example, 200N) between the window glass and the window frame. Simultaneously, the testing device for the window control system collects data from two channels: the real-time reading from the external force sensor and the real-time window position data fed back by the window control system under test via a digital signal channel.

[0125] A threshold for triggering the anti-pinch function is set (e.g., 100N). Timing begins when the reading from the external force sensor exceeds this threshold and continues until a control signal or bus message indicating window reversal is detected from the window control system under test. During this process, the peak clamping force (i.e., the maximum force applied to the object before the window reverses) and the response time delay are calculated. If the response time exceeds the regulatory or design limit (e.g., 100ms), the anti-pinch performance is deemed unqualified.

[0126] When the detection type is ripple current detection, the control power supply equipment applies current interference or reverse electromagnetic torque to the window motor, monitors the moment of sudden change in the amplitude of the current signal, and calculates the time difference from the application of interference to the reversal of the window motor to generate ripple anti-pinch performance test results; the application of current interference or reverse electromagnetic torque is based on a preset nonlinear impedance model, which is used to simulate the torque change process when a flexible object is clamped.

[0127] Here, the test device for the window control system controls the power supply equipment to apply current interference to the power supply circuit of the window motor, or simulates the application of reverse electromagnetic torque by controlling the motor load.

[0128] To overcome the limitations of traditional tests that simply use current steps to simulate rigid collisions, the applied current interference or reverse electromagnetic torque in this embodiment is based on a preset nonlinear impedance model. The nonlinear impedance model (such as a spring-damped model) is used to simulate the torque change process when a flexible object, such as a human arm, is clamped; that is, the resistance does not reach its peak instantaneously, but rather exhibits a nonlinear, gradual increase.

[0129] While applying interference, the waveform changes of the window motor current signal are monitored in real time at high frequency, paying particular attention to sudden changes in current amplitude. When the current amplitude at consecutive sampling points (e.g., three consecutive points) exceeds the dynamic threshold (e.g., 1.5 times the stable operating current), or when an abnormally steep rising edge appears in the current change rate, it is determined that the simulated anti-pinch condition has been triggered, and this moment is recorded as the start time. Subsequently, monitoring continues until the motor current polarity is reversed or a falling edge is detected (representing the window starting to move in the opposite direction), and the time difference from the application of interference to the reversal of the window motor is calculated. The time difference reflects the recognition speed and processing efficiency of the ripple algorithm for the anti-pinch condition, and is used to evaluate the safety of the rippled window.

[0130] In one embodiment, when the test case is a power fluctuation stress test, step S105 includes: The power supply equipment that supplies power to the window control system under test is controlled to perform voltage change operations; voltage change operations include voltage transient drops or voltage surges.

[0131] Here, a high-performance programmable DC regulated power supply (such as the Keysight N6700 series) is preferred for the power supply, which features a fast voltage conversion rate. The test setup simulates the actual vehicle power supply curve by programming the power supply. For example, it simulates the transient voltage drop during a cold start, rapidly reducing the supply voltage from the standard 13.5V to 9V or even lower within milliseconds, and maintaining this voltage for a period before recovering. Alternatively, it simulates the voltage surge when a high-power load is disconnected, instantly raising the voltage to above 16V. Throughout this process, the test setup continuously sends raising and lowering commands to the window control system of the vehicle under test, keeping it in a loaded operating state.

[0132] When the detection type is Hall sensor detection, the working status of the window control system under test is monitored during voltage changes. The system identifies whether there is a power supply interruption or controller reset in the working status, and generates Hall sensor adaptability test results based on the first identification result.

[0133] Here, since the Hall sensor itself is an active device that requires power, when the power supply voltage drops to a certain threshold (such as the lower limit of the Hall operating voltage), even if the motor is still rotating, the Hall sensor may stop outputting pulses due to insufficient power supply, resulting in position loss. The sensor power supply interruption fault is identified by comparing the current signal (representing motor rotation) with the digital pulse signal in real time.

[0134] Simultaneously, controller resets are identified by monitoring messages on the communication bus. If, during voltage fluctuations, the bus experiences prolonged silence or suddenly receives an initialization or wake-up message from the controller, an unexpected controller reset / restart is determined. The voltage threshold and duration of the fault are recorded to generate Hall sensor adaptability test results.

[0135] When the detection type is ripple current detection, the working status of the window control system under test is monitored during voltage changes. The system identifies whether the window motor stops or the controller resets during the working status, and generates ripple power supply adaptability test results based on the second identification result.

[0136] Here, for rippled windows, low voltage causes a decrease in motor output torque, and the signal-to-noise ratio of the ripple signal also decreases significantly. The focus is on monitoring the window motor for stalling; that is, during voltage drops, analyzing the current signal to determine if the motor has unexpectedly stalled due to insufficient torque. Additionally, monitoring bus messages is used to determine if there are any controller resets.

[0137] The adaptability test results for ripple windows can also include an evaluation of the stability of the ripple recognition algorithm. The recognition rate of the ripple signal during voltage drops is calculated. If voltage fluctuations cause the ripple features to be submerged in noise, leading to position calculation failure, this will also be recorded in the ripple power supply adaptability test results. This serves to evaluate the overall hardware and software performance of the system under electrical stress.

[0138] In one embodiment, reference is made to Figure 4 After step S105, the method further includes the following steps S401-S402.

[0139] Step S401: Associate and package the test results, the original waveform data of the current signal, and the original data of the digital signal to generate an initial data package.

[0140] Here, the raw waveform data of the current signal (i.e., the millisecond- or even microsecond-level current change curves acquired at a high sampling rate) and the raw data of the digital signal (i.e., the timing level changes of the digital pulse channel) are extracted. The raw data includes the inrush current at the moment of motor startup, the microscopic characteristics of commutation ripple, and the details of pulse jitter from the sensor.

[0141] The test results are correlated with the original data to ensure a one-to-one correspondence between the results and the supporting evidence. To facilitate transmission and parsing, these multi-source heterogeneous data can be serialized and encapsulated using structured data formats (such as JSON, XML, or binary Blob format) to generate a complete initial data packet.

[0142] Step S402: Assign a data identifier to the initial data, obtain the data to be stored, and store the data to be stored in the preset database.

[0143] Here, a unique data identifier is assigned to the generated initial data packet. The data identifier is preferably a combination of the product serial number of the window control system under test, the test date and timestamp, and the test station number, ensuring that each test record is unique throughout its entire lifecycle.

[0144] Subsequently, the data to be stored, each with a unique identifier, is written to a pre-defined database. This pre-defined database can be a relational database (such as MySQL or SQL Server) deployed on a local industrial control machine, or a distributed database deployed in the cloud.

[0145] Based on a pre-set database, users can achieve full lifecycle data traceability. For example, by entering the product serial number, users can retrieve the original current waveform of the product at the time of manufacture for after-sales fault analysis. Alternatively, by querying by time period, users can perform historical data comparison and trend analysis, and statistically analyze the consistency changes of different batches of motors, thereby empowering intelligent manufacturing and quality control. In addition, the cloud storage architecture also supports remote collaboration, allowing engineers in different locations to access the same set of test data for offline analysis and algorithm verification.

[0146] Based on the above embodiments, this application provides a testing device for a vehicle window control system, referring to... Figure 5 The testing device for the vehicle window control system includes: data acquisition equipment 1, communication equipment 2, and control module 3.

[0147] Data acquisition device 1 is configured to connect to the signal output terminal of the window control system under test, so as to synchronously acquire the current signal of the window motor of the window control system under test and the digital signal output by the digital pulse channel of the window control system under test.

[0148] Communication device 2 is configured to connect to the communication bus of the window control system under test in order to send control commands.

[0149] The control module 3 is connected to the data acquisition device 1 and the communication device 2 respectively, and is configured to perform the test method of the window control system as described in any of the above embodiments.

[0150] In one embodiment, reference is made to Figure 6 The testing device for the window control system also includes: power supply equipment 4, external mechanical loading mechanism 5, current sensor 6, and signal conditioning circuit 7.

[0151] The current sensor 6 is installed in the power supply circuit of the window motor and connected to the data acquisition device 1 to collect current signals.

[0152] The signal conditioning circuit 7 is located between the digital pulse channel and the data acquisition device 1, and is used to filter and shape the digital signal.

[0153] The power supply device 4 is connected to the control module 3 and is configured to supply power to the window control system under test in response to the instructions of the control module 3 and perform voltage change operations.

[0154] The external mechanical loading mechanism 5 is connected to the control module 3 and is configured to apply physical resistance during the window travel of the window control system under test in response to the instructions of the control module 3.

[0155] Here, the testing device for the vehicle window control system adopts an integrated hardware platform architecture, which is compatible with the automated testing of both ripple current detection type and Hall sensor detection type vehicle window control systems. The testing device mainly consists of hardware components such as control module 3, data acquisition device 1, communication device 2, power supply device 4, current sensor 6, signal conditioning circuit 7, and external mechanical loading mechanism 5.

[0156] The control module 3 is the core processing unit of the entire testing device, establishing communication connections with the data acquisition device 1, communication device 2, power supply device 4, and external mechanical loading mechanism 5. Physically, the control module 3 can be a high-performance industrial control computer, such as a chassis-type system equipped with a PXIe-8840 controller, or a general-purpose personal computer or a server deployed in the cloud. The control module 3 internally runs host computer control software, which can be developed based on languages ​​such as LabVIEW, C#, or Python, integrating test management, equipment control, and data analysis functions. The control module 3 is configured to execute the test process in the method embodiment, that is, by coordinating various hardware devices, it completes automatic identification of the type of the system under test, adaptive loading of test cases, test execution, and result generation.

[0157] Power supply device 4 provides operating power to the window control system under test. Power supply device 4 preferably employs a programmable DC regulated power supply, such as the Keysight N6700 series or a similar product. Power supply device 4 connects to control module 3 via a GPIB or LAN interface, and outputs a set voltage (such as the standard 13.5V vehicle voltage) in response to commands from control module 3. Furthermore, power supply device 4 also has transient waveform output capability, enabling it to perform voltage change operations, such as simulating transient voltage drops during vehicle startup (e.g., a drop to 9V) or sudden voltage spikes during load changes, to cooperate with control module 3 in completing power supply fluctuation stress testing.

[0158] Communication device 2 acts as a bridge for command transmission between control module 3 and the window control system under test. Communication device 2 is configured to physically connect to the communication bus (such as CAN bus or LIN bus) of the window control system under test. In specific implementations, interface cards such as Vector CANcaseXL can be used, along with the CANoe software environment or CAPL dynamic link library, to interact with control module 3. Communication device 2 receives control commands (such as window raising / lowering commands) issued by control module 3 and converts them into messages conforming to the vehicle bus protocol, sending them to the system under test. Simultaneously, communication device 2 can also read status messages fed back from the bus and upload them to control module 3.

[0159] Data acquisition device 1 is used to achieve high-precision synchronous acquisition of multi-channel signals. Data acquisition device 1 preferably uses a PXIe-4300 high-precision analog input module in conjunction with a PXIe-6341 digital I / O module, possessing at least 16-bit resolution and a sampling rate higher than 100 kS / s, ensuring the capture of minute ripple characteristics during motor commutation. Data acquisition device 1 is configured to connect to the signal output terminal of the window control system under test, specifically achieving signal acquisition through the following two paths: The first path is used to acquire current signals. Current sensor 6 is installed in the power supply circuit of the window motor and connected to data acquisition device 1. Preferably, current sensor 6 is a LEM HAL 50-S type open-type Hall current sensor, capable of converting the large current of the motor into an analog voltage signal (e.g., + / -5V range) recognizable by data acquisition device 1. Data acquisition device 1 records this current signal in real time through the analog input channel, providing it to control module 3 for ripple characteristic analysis or anti-pinch current monitoring.

[0160] The second path is used for acquiring digital signals. Signal conditioning circuit 7 is located between the digital pulse channel of the window control system under test and the data acquisition device 1. Since the original digital pulse signal may contain noise or level mismatch, signal conditioning circuit 7 filters and shapes the signal output from the digital pulse channel, converting it into a standard digital square wave signal, which is then transmitted to the digital input channel or counter port of data acquisition device 1. Control module 3 uses this signal for Hall pulse counting or time-domain characteristic analysis.

[0161] An external mechanical loading mechanism 5 is used to assist in the anti-pinch test of the Hall effect window. Connected to the control module 3, the external mechanical loading mechanism 5 is configured to apply physical resistance during the window's travel in response to commands. Its specific structure may include a servo motor-driven robotic arm or a standard force-measuring rod, with an external force sensor of suitable range (e.g., 200N) integrated at the contact end. The external mechanical loading mechanism 5 feeds back the force sensor readings to the data acquisition device 1 or the control module 3 in real time to achieve closed-loop force control and anti-pinch force measurement.

[0162] In terms of system integration, the aforementioned test setup can adopt a compact chassis-type structure based on PXI (PCI for Instruments) / LXI (Local Area Network for Instruments) standards to achieve high-speed interconnection at the board level. Alternatively, discrete instruments can be integrated virtually via USB or Ethernet. For systems under test lacking a bus interface, the test setup can also be expanded with a relay matrix or analog switch module, driven by control module 3 to simulate physical button signals, thereby replacing the function of communication device 2.

[0163] The computer program product provided in this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0164] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0165] Furthermore, in the description of the embodiments of this application, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0166] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0167] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0168] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

Claims

1. A test method for a vehicle window control system, characterized in that, include: Send control commands to the window control system under test to drive the window motor in the window control system under test to run; The current signal of the window motor during operation and the digital signal output by the digital pulse channel of the window control system under test are collected simultaneously. Based on the current signal and the digital signal, the detection type of the window control system under test is identified; the detection type includes ripple current detection type and Hall sensor detection type. Based on the identified detection type, load the corresponding test cases from the preset test case library; The test cases are executed, and the test results of the window control system under test are generated based on the test data collected during the execution process.

2. The test method for the vehicle window control system according to claim 1, characterized in that, The step of identifying the detection type of the window control system under test based on the current signal and the digital signal includes: Perform time-domain feature analysis on the digital signal to calculate the number of effective pulses and the consistency parameter of the pulse period within a preset time window; If the number of effective pulses is greater than or equal to a preset pulse number threshold, and the consistency parameter meets a preset stability condition, the detection type is determined to be the Hall sensor detection type. If the number of effective pulses is less than the preset pulse number threshold, the current signal is frequency domain transformed to obtain spectrum data; the spectrum data is searched within the preset motor commutation frequency range, and if a characteristic spectrum component with an energy amplitude exceeding the preset background noise threshold is detected, the detection type is determined to be the ripple current detection type.

3. The test method for the vehicle window control system according to claim 2, characterized in that, The step of determining the detection type as the ripple current detection type further includes: Extract the center frequency of the characteristic spectral component; Calculate the slope of the change in the center frequency during the operation of the window motor; If the slope of the change is consistent with the preset motor speed increase curve, the detection type is determined to be the ripple current detection type.

4. The test method for the vehicle window control system according to claim 1, characterized in that, The step of loading the corresponding test cases from the preset test case library according to the identified detection type includes: When the detection type is identified as the Hall sensor detection type, a first test case set and common test cases are loaded; the first test case set includes: Hall pulse step loss detection, pulse duty cycle consistency test, and absolute position control accuracy test based on pulse counting; the common test cases include anti-pinch function test, power fluctuation stress test, window position control accuracy test, and lifting time test. When the detection type is identified as the ripple current detection type, the second test case set and the common test case are loaded; the second test case set includes: ripple count cumulative error test, ripple signal-to-noise ratio test under power supply voltage drop conditions, and stall threshold calibration test based on current amplitude change.

5. The test method for the vehicle window control system according to claim 4, characterized in that, The steps of executing the test cases and generating test results for the window control system under test based on the test data collected during execution include: When the detection type is the Hall sensor detection type, the first test case set is executed, and the pulse loss rate, pulse duty cycle variance, and positioning deviation based on pulse count are calculated based on the digital signals collected during the execution of the first test case set to generate Hall performance evaluation results. When the detection type is the ripple current detection type, the second test case set is executed. Based on the current signal collected during the execution of the second test case set, the cumulative error rate of ripple count, the ripple signal-to-noise ratio during the power supply voltage drop, and the current amplitude when stall is triggered are calculated to generate ripple performance evaluation results.

6. The test method for the vehicle window control system according to claim 4, characterized in that, When the test case is the anti-pinch function test, the step of executing the test case and generating the test result of the window control system under test based on the test data collected during the execution includes: When the detection type is the Hall sensor detection type, the external mechanical loading mechanism is controlled to apply physical resistance to the window travel of the window control system under test, and the readings of the external force sensor and the position data in the digital signal are collected simultaneously to calculate the peak clamping force and response time when the anti-pinch is triggered, so as to generate Hall anti-pinch performance test results. When the detection type is the ripple current detection type, the control power supply device applies current interference or reverse electromagnetic torque to the window motor, monitors the moment of abrupt change in the amplitude of the current signal, and calculates the time difference from the application of interference to the reversal of the window motor to generate ripple anti-pinch performance test results; wherein the application of current interference or reverse electromagnetic torque is based on a preset nonlinear impedance model, and the nonlinear impedance model is used to simulate the torque change process when a flexible object is clamped.

7. The test method for the vehicle window control system according to claim 4, characterized in that, When the test case is the power fluctuation stress test, the step of executing the test case and generating the test result of the window control system under test based on the test data collected during the execution includes: The power supply device that supplies power to the window control system under test is controlled to perform voltage change operations; the voltage change operations include voltage transient drops or voltage surges. When the detection type is the Hall sensor detection type, the working state of the window control system under test is monitored during the voltage change process, the Hall sensor power supply interruption or controller reset is identified in the working state, and the Hall sensor adaptability test result is generated based on the first identification result. When the detection type is the ripple current detection type, the working state of the window control system under test is monitored during the voltage change process, and it is identified whether the window motor stops or the controller is reset in the working state. Based on the second identification result, a ripple power supply adaptability test result is generated.

8. The test method for the vehicle window control system according to claim 1, characterized in that, After the steps of executing the test cases and generating test results for the window control system under test based on the test data collected during the execution, the method further includes: The test results, the original waveform data of the current signal, and the original data of the digital signal are correlated and packaged to generate an initial data package; Assign a data identifier to the initial data to obtain the data to be stored, and store the data to be stored in a preset database.

9. A testing device for a vehicle window control system, characterized in that, include: Data acquisition equipment, communication equipment, and control modules; The data acquisition device is configured to connect to the signal output terminal of the window control system under test, so as to synchronously acquire the current signal of the window motor of the window control system under test and the digital signal output by the digital pulse channel of the window control system under test. The communication device is configured to connect to the communication bus of the window control system under test in order to send control commands; The control module is connected to the data acquisition device and the communication device respectively, and is configured to perform the test method of the window control system as described in any one of claims 1 to 8.

10. The testing apparatus for the vehicle window control system according to claim 9, characterized in that, The device also includes: a power supply, an external mechanical loading mechanism, a current sensor, and a signal conditioning circuit. The current sensor is installed in the power supply circuit of the window motor and connected to the data acquisition device to collect the current signal; The signal conditioning circuit is disposed between the digital pulse channel and the data acquisition device, and is used to filter and shape the digital signal; The power supply device is connected to the control module and is configured to supply power to the window control system under test in response to the instructions of the control module, and to perform voltage change operations. The external mechanical loading mechanism is connected to the control module and is configured to apply physical resistance during the window travel of the window control system under test in response to the instructions of the control module.

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