OBD-based power window intelligent calibration method and handheld device

Abstract

The invention discloses an OBD-based intelligent calibration method for a power window and handheld equipment, and the method comprises the steps: selecting a proper communication protocol according to the identity information of a vehicle, building communication with the vehicle, and obtaining a coding serial number of an ECU. A standard control instruction is sent, the limiting state of the door and window is obtained in real time, then the limiting threshold value is adjusted, and a calibration result is returned. According to the invention, the handheld device improves the efficiency through one-button calibration, and reduces the time and economic cost.

Description

Technical Field

[0001] The present application relates to the field of automobile diagnostic technology, and in particular to an OBD-based electric window intelligent calibration method and a handheld device. Background Art

[0002] With the rapid development of the automotive industry and the increasing degree of electronicization, power windows have become standard features in modern vehicles. Their functions (including standardized parameter settings, anti-pinch verification, and self-learning value reset) directly affect window operation safety and user experience. Window function calibration can ensure that the speed and force of window opening and closing are appropriate, avoiding damage or safety hazards caused by careless operation.

[0003] In related technologies, window calibration is performed using specialized engineer software provided by major manufacturers. Users undergo manufacturer training and, relying on their expertise, manually select the brand, model series, model year, and configuration information that exactly matches the vehicle being repaired. The software then communicates with the vehicle's ECU based on a pre-defined diagnostic protocol and calibration command sequence unique to that specific vehicle model, completing the calibration process.

[0004] However, the calibration process is deeply tied to specific hardware, complex processes, and manual operations, resulting in a closed diagnostic system. At the same time, incorrect calibration may cause the windows to lose control, making calibration difficult for non-professionals and posing a safety hazard. Summary of the Invention

[0005] The present application provides an OBD-based electric window intelligent calibration system and method, which is used to achieve the accuracy and reliability of the calibration process while significantly improving efficiency and reducing time and economic costs through one-click calibration on a handheld device.

[0006] In the first aspect, the present application provides an OBD-based electric window intelligent calibration method, which is applied to a handheld device, and the method includes: sending a handshake request of a first communication protocol to the vehicle to be tested according to the identity information of the vehicle to be tested, and the first communication protocol is one of multiple communication protocols adopted by the brand of the vehicle to be tested; receiving a protocol reply value of the vehicle to be tested, and judging whether the vehicle to be tested supports the first protocol according to the protocol reply value, and if not, switching to a second protocol to send a handshake request until communication is established; after establishing communication, sending a diagnostic command to the vehicle to be tested to obtain the coding serial number of the vehicle ECU; after successfully matching the coding serial number with the built-in support list of the vehicle to be tested, sending a standard control instruction for driving the door and window to be raised and lowered to the ECU and obtaining the limit status of the target door and window in real time; based on the built-in standard value and limit status of the vehicle to be tested, adjusting the limit threshold of the target door and window and returning the calibration result, and the limit threshold is used to ensure that the state detection result of the ECU matches the actual state; after the calibration result successfully matches the system preset target value, exiting the calibration mode.

[0007] In the above embodiment, based on sending standard control instructions and obtaining the limit status of doors and windows in real time, the calibration process can dynamically adjust the limit threshold to ensure that the state detection result of the ECU matches the actual state. Finally, after the calibration result successfully matches the system preset target value, the calibration mode is exited, effectively solving the problem of complex and inefficient calibration process in the existing technology, thereby achieving accurate and efficient calibration of electric windows. One-click calibration through handheld devices improves efficiency and reduces time and economic costs. In combination with some embodiments of the first aspect, in some embodiments, the step of sending a handshake request of a first communication protocol to the vehicle to be tested based on the identity information of the vehicle to be tested, where the first communication protocol is one of multiple communication protocols adopted by the brand of the vehicle to be tested, specifically includes: parsing the vehicle identification code of the vehicle to be tested based on the identity information of the vehicle to be tested, and retrieving a preferred protocol list that matches the manufacturer of the vehicle to be tested and is pre-sorted by historical connection success rate from a built-in protocol database based on the vehicle identification code; sending a handshake request of the first communication protocol to the vehicle to be tested, where the first communication protocol is the first-ranked protocol selected from the preferred protocol list; In the above embodiment, by parsing vehicle identity information to obtain the vehicle identification code, and then retrieving a list of preferred protocols from a protocol database based on the vehicle identification code, sorted by historical connection success rates, the system can quickly find the protocol with the highest communication success rate with the vehicle. By selecting the protocol with the highest ranking to send a handshake request, the time and failure rate for communication establishment are effectively reduced. This mechanism effectively solves the problems of blind communication protocol selection and inefficient communication establishment in the prior art, thereby achieving fast and reliable communication establishment, providing a solid foundation for the subsequent calibration process and improving the efficiency and reliability of the entire calibration system.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of receiving the protocol response value of the vehicle to be tested, judging whether the vehicle to be tested supports the first protocol based on the protocol response value, and if not, switching to the second protocol to send a handshake request until communication is established, specifically includes: receiving the protocol response value of the vehicle to be tested, judging whether the vehicle to be tested supports the first communication protocol based on the protocol response value, and if not, selecting the second-ranked protocol from the preferred protocol list as the second communication protocol to send a handshake request until communication is established.

[0009] In the above embodiment, after receiving the vehicle's protocol response value, the system can determine whether the vehicle supports the current protocol based on the response value. If not, it selects the next protocol from the preferred protocol list and continues to try until communication is established. This mechanism ensures that even if the preferred protocol is not supported, communication can be successfully established through the alternative protocol, enhancing the system's fault tolerance and adaptability. This effectively solves the communication failure problem caused by communication protocol mismatch in the prior art, thereby achieving a stable and reliable communication connection, ensuring the smooth progress of the calibration process, and improving the system's robustness and user experience.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after successfully matching the coded serial number with the built-in support list of the vehicle to be tested, sending standard control instructions to the ECU to drive the door and window lifting and obtaining the limit status of the target door and window in real time, the method also includes: during the journey in which the standard control instructions drive the target door and window to move from the starting position to the end position, obtaining the characteristic parameters of the target door and window for door and window lifting at a preset acquisition frequency; after comparing the characteristic parameters with the benchmark parameter model corresponding to the vehicle to be tested, generating a calibration quality quantification score through a weighted algorithm based on the deviation of the comparison result; when the calibration quality quantification score is lower than the health threshold corresponding to the benchmark parameter model, matching and generating calibration optimization suggestions from the preset expert rule library based on the characteristic parameters with the largest deviation.

[0011] In the above-described embodiment, during the calibration process, characteristic parameters of door and window lifts are acquired through frequency sampling and compared with a baseline parameter model to generate a quantitative calibration quality score, enabling the system to monitor the quality of the calibration process in real time. When the score falls below a healthy threshold, calibration optimization suggestions are generated based on the characteristic parameters with the largest deviation, providing the operator with clear optimization directions. This mechanism effectively addresses the existing problem of a lack of real-time quality monitoring and optimization suggestions during the calibration process, thereby enabling refined management of the calibration process, improving calibration accuracy and reliability, ensuring optimal performance of the vehicle's power window system, and enhancing the overall quality of the vehicle.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, after comparing the characteristic parameters with the reference parameter model corresponding to the vehicle under test, the step of generating a calibration quality quantization score using a weighted algorithm based on the deviation of the comparison result specifically includes: aligning and mapping the time series of the characteristic parameters to generate a quality fingerprint curve describing the motor load state; performing morphological matching and difference analysis on the quality fingerprint curve and the reference parameter model corresponding to the vehicle under test to obtain the deviation of key feature points on the quality fingerprint curve relative to corresponding feature points of the reference parameter model; and generating a calibration quality quantization score using a weighted algorithm based on the deviation; In the above-described embodiment, by aligning and mapping the time series of characteristic parameters to generate a quality fingerprint curve, and then performing morphological matching and difference analysis with the baseline parameter model to generate a calibration quality quantification score, the system can more accurately assess calibration quality. This morphological analysis captures key changes in characteristic parameters, providing a scientific basis for calibration optimization. This mechanism effectively addresses the existing issues of inaccurate and lacking scientific evidence for calibration quality assessment, enabling refined assessment and optimization of calibration quality, further improving calibration accuracy and stability, and ensuring high-performance operation of the vehicle power window system.

[0013] In conjunction with some embodiments of the first aspect, in some embodiments, before the step of adjusting the limit threshold of the target door and window based on the built-in standard value and limit status of the vehicle to be tested and returning a calibration result, wherein the limit threshold is used to ensure that the state detection result of the ECU matches the actual state, the method further includes: initiating a query request to a cloud server based on the identity information of the vehicle to be tested, the identity information including vehicle model, age, and mileage information; and calibrating the built-in standard value using a dynamic reference value corresponding to the vehicle condition of the vehicle to be tested, which is returned by the cloud server based on the identity information; In the above embodiment, a query request is sent to a cloud server based on the vehicle's identity information to obtain a dynamic benchmark value corresponding to the vehicle's condition. This is then used to calibrate the internal standard value, enabling the calibration process to dynamically adjust the calibration standard based on the vehicle's actual usage. This mechanism effectively addresses the problem of fixed calibration standards in existing technologies that cannot adapt to changes in the vehicle's actual condition. It further enables dynamic adjustment and optimization of the calibration process, improves the adaptability and accuracy of the calibration, ensures consistent performance under different usage conditions, and enhances vehicle reliability and user experience.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the limit threshold of the target door and window is adjusted based on the built-in standard value and limit status of the vehicle to be tested and the calibration result is returned. The limit threshold is used to ensure that the state detection result of the ECU matches the actual state. The steps specifically include: when the target door and window are driven to rise and fall for the first time, a positive offset is applied to the built-in standard value as the first limit threshold, the door and window are driven to rise and fall and the first error between the first limit state and the target position is recorded; a negative offset is applied to the built-in standard value as the second limit threshold, the door and window are driven to rise and fall and the second error between the second limit state and the target position is recorded; based on the initial boundary range established by the first limit threshold and the second limit threshold, the limit threshold of the target door and window is adjusted using the golden section method until the error between the limit state of the final limit threshold and the built-in standard value is less than the preset accuracy; and a calibration result of the final limit threshold is generated.

[0015] In the above embodiment, by applying positive and negative offsets to establish the initial boundary range during the first drive and adjusting the limit threshold using the golden section method until the error is less than the preset precision, the system can efficiently find the optimal limit threshold. The golden section optimization algorithm reduces the number of adjustments and improves calibration efficiency. This mechanism effectively solves the problems of complex and inefficient calibration processes in existing technologies, thereby achieving rapid and precise adjustment of the limit threshold, ensuring the accuracy and reliability of the calibration results, and improving the performance and efficiency of the entire calibration system.

[0016] In a second aspect, an embodiment of the present application provides a handheld device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the handheld device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0017] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on a handheld device, enables the handheld device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a handheld device, enables the handheld device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0019] It is understandable that the handheld device provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding methods and will not be repeated here.

[0020] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By sending standard control commands and acquiring the window and door limit status in real time, the calibration process dynamically adjusts the limit thresholds, ensuring that the ECU's status detection results match the actual status. Calibration mode is exited after the calibration result successfully matches the system's preset target value. This effectively solves the complex and inefficient calibration process in existing technologies, thereby achieving accurate and efficient calibration of power windows. One-click calibration via a handheld device significantly improves efficiency and reduces time and economic costs.

[0021] 2. By aligning and mapping the time series of characteristic parameters to generate a quality fingerprint curve, and performing morphological matching and difference analysis with the benchmark parameter model to generate a calibration quality quantification score, the system can more accurately assess calibration quality. This morphological analysis captures key changes in characteristic parameters, providing a scientific basis for calibration optimization. This mechanism effectively addresses the existing issues of inaccurate and lacking scientific evidence for calibration quality assessment, enabling refined assessment and optimization of calibration quality, further improving calibration accuracy and stability, and ensuring high-performance operation of the vehicle's power window system.

[0022] 3. By using the golden section method to adjust the limit threshold until the error is less than the preset accuracy, the system can efficiently find the optimal limit threshold. This golden section method reduces the number of adjustments and improves calibration efficiency. This mechanism effectively solves the problems of complex adjustment and low efficiency in the existing calibration process, thereby achieving rapid and precise adjustment of the limit threshold, ensuring the accuracy and reliability of the calibration results, and improving the performance and efficiency of the entire calibration system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of an OBD-based smart calibration method for electric windows in an embodiment of the present application; Figure 2 This is another flow chart of an OBD-based smart calibration method for electric windows in an embodiment of the present application; Figure 3 This is a schematic diagram of a physical device structure of a handheld device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations of one or more of the listed items.

[0025] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0026] See also Figure 1 , which is a flow chart of an OBD-based electric window intelligent calibration method in an embodiment of the present application.

[0027] S101: Send a handshake request of a first communication protocol to the vehicle to be tested according to the identity information of the vehicle to be tested.

[0028] When a user prepares to perform intelligent vehicle calibration, they first need to obtain the vehicle's identity information. This information can be read through the vehicle's built-in OBD interface or manually entered. Based on this identity information, the handheld device searches its built-in protocol database for communication protocols that match the vehicle's brand, selects one as the first communication protocol, generates a handshake request signal, and sends it to the vehicle under test via the OBD interface. This handshake request signal contains basic device information and the intent of the communication request. The vehicle's identity information represents various data used to uniquely identify the vehicle, such as the vehicle identification number (VIN), model, age, and mileage. This information is used to determine the vehicle's specific model and configuration.

[0029] S102: Receive a protocol response value from the vehicle under test, determine whether the vehicle under test supports the first protocol based on the protocol response value, and if not, switch to the second protocol and send a handshake request until communication is established.

[0030] After sending a handshake request, the device waits for a response from the vehicle under test to determine whether communication can be established. After the handheld device sends a handshake request using the first communication protocol to the vehicle under test, the vehicle's electronic system parses the request and checks whether the communication protocol used in the request matches one supported by the vehicle. If the vehicle supports the protocol, it returns a protocol response value, informing the handheld device that the communication protocol matches, and a communication link is established between the handheld device and the vehicle. However, if the vehicle does not support the protocol, it also returns a protocol response value, but this time indicating a protocol mismatch. Upon receiving this response value, the handheld device uses its built-in protocol selection logic to select the next protocol, the second protocol, from among the multiple communication protocols used by the vehicle brand and resends the handshake request. This process repeats until a vehicle-supported communication protocol is found and communication is successfully established.

[0031] In some embodiments, the acquired vehicle identification information is used to accurately parse the vehicle identification number (VIN). This VIN is then used to search the device's built-in protocol database to find a "preferred protocol list" that matches the vehicle manufacturer. This list is not randomly sorted; rather, it is pre-sorted by connection success rate, based on statistical analysis of historical connection data.

[0032] The device selects the first-ranked protocol from the preferred protocol list as the primary communication protocol and sends a handshake request to the vehicle under test. If the received protocol response indicates that the vehicle does not support the protocol, the device selects the second-ranked protocol in the preferred protocol list as the second communication protocol and sends another request. This process continues until communication with the vehicle is successfully established.

[0033] S103: After establishing communication, a diagnostic command is sent to the vehicle to be tested to obtain the coding serial number of the vehicle ECU.

[0034] After successfully establishing communication with the vehicle under test, it is necessary to obtain relevant information about the vehicle ECU for subsequent calibration operations. The encoded serial number is very important for determining the specific model and version of the ECU, because different ECUs may have different functions and parameter settings.

[0035] Specifically, once a stable communication link is established between the handheld device and the vehicle under test, it selects a diagnostic command from its stored diagnostic command library that is appropriate for the vehicle's brand. This command, written in accordance with the vehicle manufacturer's specified communication protocol format, requests the vehicle's ECU to return its encoded serial number. The handheld device then sends the diagnostic command to the vehicle's ECU via the communication link. Upon receiving the command, the ECU reads the encoded serial number from its internal memory and returns it to the handheld device as a response.

[0036] S104 , after the coded serial number is successfully matched with the built-in support list of the vehicle to be tested, a standard control instruction for driving the door and window to be raised or lowered is sent to the ECU and the limit status of the target door and window is obtained in real time.

[0037] After successful matching, the handheld device sends specific control commands to the ECU according to a standardized diagnostic protocol to initiate the calibration process. This process includes specific operating requirements for door and window lifting, such as lifting speed and direction. Specifically, the ECU controls the door and window motor according to a preset program, driving the target door and window through a complete rotation until it reaches its highest and lowest physical points (i.e., upper and lower dead centers). During the lifting process, the ECU monitors the position of the door and window in real time and transmits this limit status information to the handheld device via a communication link. Upon receiving this limit status information, the handheld device analyzes and processes it to obtain real-time information about the movement of the door and window. This process is continuous; the handheld device continuously receives and processes limit status information throughout the entire lifting process.

[0038] S105 : Based on the built-in standard value of the vehicle to be tested and the limit status, adjust the limit threshold of the target door and window and return a calibration result.

[0039] After obtaining the target door and window position limits, the thresholds must be adjusted based on the actual position limits to ensure the vehicle's power window system operates properly. During this process, the device's user interface displays real-time data streams, including door and window position, during the calibration process, and clearly displays the final calibration results.

[0040] The built-in standard value of the vehicle under test refers to a set of standard parameters set by the vehicle manufacturer for the vehicle's power window system during the vehicle design and production process. These parameters include the normal operating range and limit positions of the doors and windows, and are used to ensure that the vehicle's power window system can operate normally according to design requirements. The limit threshold refers to a threshold set after adjusting the limit position of the doors and windows according to the actual limit status during the calibration process. This threshold is used to ensure that the ECU's status detection results match the actual status, thereby ensuring the safety and reliability of the vehicle's power window system in actual use. Specifically, after obtaining the limit status of the target door or window, this status information will be compared with the vehicle's built-in standard value. If there is a deviation between the limit status and the built-in standard value, the handheld device will calculate the limit threshold that needs to be adjusted based on a preset adjustment algorithm. After the adjustment is completed, the handheld device will send the new limit threshold to the vehicle's ECU, requesting the ECU to perform status detection and control according to the new threshold. The limit status of the target door or window is then obtained again to verify the effectiveness of the adjusted limit threshold. If the error between the adjusted limit status and the built-in standard value is within the allowable range, the handheld device will generate a calibration result, indicating that the calibration operation has been successfully completed. If the error is still large, the handheld device will repeat the above adjustment process until a satisfactory calibration result is achieved.

[0041] In some embodiments, a positive offset and a negative offset are applied to the vehicle's built-in standard value, respectively, to determine the first and second limit thresholds. For example, if the standard value is 1000 pulse units, the first threshold can be set to 1050 and the second threshold to 950. The device uses these two thresholds to drive the doors and windows up and down, recording the error between the actual limit state and the target position, namely the first error and the second error. These two points together establish the initial bounding range for optimization. Within this initial bounding range, iterative calculations are performed using the golden section method: an algorithm that efficiently finds the minimum value of a function in a linear search. The golden section method inserts two new test points within the current interval and compares their test results to continuously narrow the range containing the optimal solution. This process is repeated, with each iteration generating a more optimized limit threshold until a final limit threshold is found, at which the error between the actual limit state of the door or window and the built-in standard value is less than a preset accuracy requirement (for example, less than 2 pulse units). At this point, the algorithm converges and the handheld device generates a calibration result that includes this final limit threshold.

[0042] In other embodiments, the vehicle's built-in standard value is used as the initial limit threshold. The doors and windows are driven once, and the initial error between the actual stop position and the target position is measured (for example, stopping 10 pulse units early). An adjustment value is calculated based on this error. The adjustment value is typically the error value multiplied by a preset proportionality factor K (a constant less than 1, such as 0.8). The calculated adjustment value is applied to the current threshold to generate a new limit threshold. The doors and windows are driven again using this new limit threshold, and a new error is measured. If the new error is still greater than the preset accuracy requirement, the steps are repeated, and adjustments are made based on the new error until the error after a certain adjustment is less than the preset accuracy. At this point, the limit threshold is adopted as the final calibration result.

[0043] It is understandable that the threshold value may be calculated by other methods, which are not limited here.

[0044] S106: After the calibration result successfully matches the system preset target value, exit the calibration mode.

[0045] Throughout the calibration process, the handheld device continuously scans the data stream sent by the ECU for a termination signal. As soon as the ECU responds with a specific command or status code indicating "calibration completed" or "calibration failed," the handheld device immediately determines that the calibration process has concluded, terminates the current function, and exits calibration mode, restoring the vehicle's power window system to normal operation.

[0046] In some embodiments, if the error still cannot converge to the allowable range after a limited number of automatic adjustments or a limited time, a "Calibration Failed" prompt will be displayed, and the user will be provided with further operation options, such as "Recalibrate" or "Switch to Manual Calibration Mode", allowing technicians to manually perform corrections.

[0047] In the above embodiment, vehicle information is automatically identified by a handheld device, the optimal communication protocol is intelligently matched to quickly establish communication, and intelligent optimization algorithms such as the golden section method are used to automatically adjust the limit threshold. This effectively solves the problems of traditional calibration methods such as cumbersome processes, poor compatibility, reliance on manual experience, and safety risks. It thus realizes a one-click, automated, and intelligent power window calibration process. While ensuring the accuracy and reliability of the calibration results, it significantly improves calibration efficiency and reduces the professional skills requirements for operators as well as the time and economic costs.

[0048] During the actual calibration process, the window may struggle to operate in an area with high resistance, with the motor current approaching the protection threshold. However, the calibration may ultimately be completed. While successful, the window system is already in a sub-healthy state and may malfunction again during subsequent use. This could compromise the long-term validity of the window calibration and reduce the effectiveness of automated calibration.

[0049] See also Figure 2 , is another flow chart of an OBD-based electric window intelligent calibration method in an embodiment of the present application.

[0050] S201: Send a handshake request of a first communication protocol to the vehicle to be tested according to the identity information of the vehicle to be tested.

[0051] S202: Receive a protocol response value from the vehicle under test, determine whether the vehicle under test supports the first protocol based on the protocol response value, and if not, switch to the second protocol and send a handshake request until communication is established.

[0052] S203: After establishing communication, a diagnostic command is sent to the vehicle to be tested to obtain the coding serial number of the vehicle ECU.

[0053] S204 , after the coded serial number is successfully matched with the built-in support list of the vehicle to be tested, a standard control instruction for driving the door and window to be raised or lowered is sent to the ECU and the limit status of the target door and window is obtained in real time.

[0054] Steps S201 to S204 are similar to steps S101 to S104 and are not described in detail here.

[0055] S205 , during the travel period when the target door or window is driven by the standard control instruction to move from the starting position to the end position, characteristic parameters of the target door or window for door or window lifting and lowering are acquired at a preset acquisition frequency.

[0056] As the target door or window begins to move from its starting position to its final position according to standard control instructions, the handheld device periodically acquires characteristic parameters of the target door or window from the vehicle's ECU at a pre-set acquisition frequency. During the acquisition process, the handheld device stores the acquired characteristic parameters in a local cache or storage medium. These characteristic parameters include but are not limited to motor current, voltage, and speed, and the door or window's lifting and lowering speed and acceleration.

[0057] S206 , after comparing the characteristic parameters with the reference parameter model corresponding to the vehicle to be tested, generate a calibration quality quantitative score through a weighted algorithm according to the deviation of the comparison result.

[0058] After collecting the characteristic parameters of the target door and window, the device retrieves a benchmark parameter model corresponding to the vehicle under test from its stored database. This benchmark parameter model is based on standard data provided by the vehicle manufacturer or derived through extensive on-vehicle testing. It contains typical values ​​and variation ranges for various characteristic parameters under normal conditions. The handheld device then compares each collected characteristic parameter with the corresponding parameter in the benchmark parameter model, calculating the difference between the actual value and the benchmark value for each characteristic parameter, known as the deviation. After the comparison is complete, the handheld device weights the deviation of each characteristic parameter based on a preset weighting algorithm. The weighting algorithm assigns weights based on the characteristic parameter's importance and its impact on the door and window lifting performance. For example, the motor current parameter may have a greater impact on door and window lifting safety and therefore receive a higher weight; while the door and window lifting speed may have a greater impact on comfort and therefore receive a relatively lower weight. After weighting, the handheld device comprehensively calculates the weighted deviations of all characteristic parameters to generate a quantitative calibration quality score.

[0059] In some embodiments, the calibration quality quantization score can be generated by a weighted algorithm based on the deviation of the comparison results in various ways: Alternatively, a quality fingerprint assessment method based on morphological analysis can be used. The time series of collected characteristic parameters (especially motor current) are aligned and normalized to generate a quality fingerprint curve that accurately describes the load changes throughout the motor's travel. This measured fingerprint curve is then morphologically matched and analyzed for differences with the standard curve in the benchmark parameter model. For example, a dynamic time warping (DTW) algorithm is used to calculate the minimum distance between the two curves. Key feature points on the fingerprint curve are identified (such as the current spike at startup, the current plateau in the constant speed operating zone, and the stall current at the limit point). The deviations of these key points relative to the corresponding feature points in the benchmark model are calculated in terms of amplitude and time. Finally, a weighted sum is taken based on the importance of the deviations at each key point (for example, the stall current has the highest deviation weight) to generate the final calibration quality quantification score.

[0060] Optionally, the handheld device can also adopt a weighted algorithm based on fuzzy logic. In this way, the deviation of each characteristic parameter will be mapped to a fuzzy set, such as low deviation, medium deviation and high deviation. Then, the fuzzy deviation of each characteristic parameter is weighted according to the preset fuzzy rules and weight distribution scheme. For example, if the fuzzy deviation of the motor current is medium deviation, the weight is 0.4; the fuzzy deviation of the door and window lifting speed is low deviation, the weight is 0.3; the fuzzy deviation of the acceleration is medium deviation, the weight is 0.3. Then, the calibration quality quantization score can be obtained through fuzzy logic operation to obtain a comprehensive fuzzy evaluation result, and then this fuzzy evaluation result is converted into a specific quantitative score. It is understandable that other methods can also be used to achieve the generation of calibration quality quantization scores, such as automatically learning weight distribution through machine learning algorithms, etc., which are not limited here.

[0061] S207: When the calibration quality quantization score is lower than the health threshold corresponding to the benchmark parameter model, matching and generating calibration optimization suggestions from a preset expert rule library based on the characteristic parameter with the largest deviation.

[0062] When the calibration quality is determined to be substandard (i.e., the calibration quality quantification score is lower than the health threshold corresponding to the baseline parameter model), the following optimization recommendation process is initiated: Based on the various characteristic parameters of the calibration quality score (such as motor peak current, total operating time, number of limit point pulses, etc.), the deviation of each parameter relative to its standard model is calculated. The characteristic parameter with the largest deviation is found, as this parameter is most likely to point to the root cause of the problem and has the greatest impact on the overall calibration quality. This key parameter is then used as an index to match the built-in expert rule base. This rule base is compiled from expert knowledge in the field of vehicle maintenance and calibration and contains correspondences between various common problems and solutions. For example, if the characteristic parameter with the largest deviation is excessive motor current, the expert rule base may match the recommendation: check whether the motor load is too large (such as guide rail resistance) or check and clean the motor cooling system.

[0063] In some embodiments, the expert rule base is constructed as a logically rigorous decision tree structure. Each non-leaf node of the tree represents a characteristic parameter or a decision condition (for example, whether the motor current exceeds the threshold A), and each branch represents a judgment result, and the final leaf node corresponds to a specific optimization suggestion. When it is detected that the calibration quality is not up to standard, the handheld device will start from the root node of the decision tree, use the characteristic parameter with the largest deviation as the primary judgment basis, and perform a logical traversal along the branches of the tree. For example, if the characteristic parameter with the largest deviation is that the motor current is too high, it will navigate to the motor current node and select the corresponding branch based on the specific value of the current (such as whether it exceeds a certain dangerous threshold), and finally quickly locate a highly targeted optimization suggestion, such as a suggestion to check whether the motor is short-circuited or to appropriately adjust the ECU drive voltage.

[0064] S208: Initiate a query request to a cloud server based on the identity information of the vehicle to be tested.

[0065] The handheld device sends a query request to the cloud server via a network connection. Upon receiving the query request, the cloud server searches its extensive stored vehicle data for a dynamic baseline value corresponding to the vehicle's condition, based on the vehicle's identity information. This dynamic baseline value is dynamically generated based on the vehicle's actual usage and historical data, more accurately reflecting the vehicle's current operating status. Once the cloud server finds the corresponding dynamic baseline value, it returns it as response data to the handheld device. The handheld device then stores the received dynamic baseline value for use in subsequent calibration processes.

[0066] S209. Correcting the built-in standard value based on the dynamic reference value corresponding to the vehicle condition to be tested and returned by the cloud server according to the identity information.

[0067] After obtaining dynamic baseline values ​​from the cloud server, they are compared with the vehicle's built-in standard values. During actual use, due to component wear, environmental factors, and other factors, the vehicle's actual operating status may deviate from the built-in standard values. Built-in standard values ​​are pre-set by the vehicle manufacturer during the design and production process and represent the vehicle's ideal operating parameters. Based on the difference between the dynamic baseline values ​​and the built-in standard values, the built-in standard values ​​are adjusted according to pre-set calibration rules.

[0068] In some embodiments, the correction of the built-in standard value by the dynamic reference value can be achieved in a variety of ways: Optionally, after obtaining the dynamic reference value, the difference between the dynamic reference value and the built-in standard value is calculated. Then, based on this difference value, the built-in standard value is adjusted according to a preset proportional factor. Optionally, a correction method based on interpolation can also be used. In this way, the handheld device will construct an interpolation function based on the difference between the dynamic reference value and the built-in standard value. For example, if the difference between the dynamic reference value and the built-in standard value is a linear relationship, the handheld device will construct a linear interpolation function. Based on this interpolation function, a new built-in standard value is calculated, which is not limited here.

[0069] S210: Based on the built-in standard value of the vehicle to be tested and the limit status, adjust the limit threshold of the target door and window and return a calibration result.

[0070] Step S210 is similar to step S105 and will not be described in detail here.

[0071] S211 . After the calibration result successfully matches the system preset target value, exit the calibration mode.

[0072] When the calibration process is completed and the final calibration results are generated, a series of operations are immediately executed based on the calibration results to exit the calibration mode: first, a specific communication command is sent to the vehicle ECU to notify the ECU to end the diagnostic state; after receiving the command, the ECU will solidify the newly calibrated parameters (such as limit thresholds) into non-volatile memory and restore the normal user control logic of the power windows.

[0073] In the embodiment of the present application, by constructing a preferred protocol list based on historical successful first-time verification, rapid communication with the vehicle to be tested is achieved; by introducing a cloud server, the built-in standard value is dynamically corrected according to information such as vehicle model, age, mileage, etc., to make it more in line with the actual condition of the vehicle; characteristic parameters are collected during the calibration trip to generate a quality fingerprint curve, and compared with the benchmark model to generate a quantitative score and optimization suggestions; at the same time, the golden section method is used to accurately and efficiently adjust the limit threshold, further realizing fast, accurate, adaptive and intelligent calibration of electric windows, greatly improving the quality and efficiency of the calibration work.

[0074] The handheld device in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a handheld device in an embodiment of the present application.

[0075] It should be noted that Figure 3 The structure of the handheld device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0076] like Figure 3 As shown, the handheld device includes a CPU 301, which can perform various appropriate actions and processes based on programs stored in a ROM 302 or programs loaded from a storage unit 308 into a RAM 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0077] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, push button switches, and the like; an output section 307 including a liquid crystal display (LCD), an audio output device, indicator lights, and the like; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the removable media can be installed in the storage section 308 as needed.

[0078] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, the various functions defined in the present invention are performed.

[0079] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings.

[0080] Specifically, the handheld device of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, an OBD-based electric window intelligent calibration method provided in the above embodiment is implemented.

[0081] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the handheld device described in the above embodiments, or may exist independently and not incorporated into the handheld device. The storage medium carries one or more computer programs, which, when executed by a processor of the handheld device, enable the handheld device to implement the OBD-based power window intelligent calibration method provided in the above embodiments.

[0082] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0083] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

Claims

1. An intelligent calibration method for electric windows based on OBD, characterized in that: Applied to a handheld device, the method includes: Sending a handshake request of a first communication protocol to the vehicle under test according to the identity information of the vehicle under test, where the first communication protocol is one of multiple communication protocols adopted by the brand of the vehicle under test; receiving a protocol response value from the vehicle under test, determining whether the vehicle under test supports the first protocol according to the protocol response value, and if not, switching to the second protocol and sending a handshake request until communication is established; After establishing communication, a diagnostic command is sent to the vehicle to be tested to obtain the coded serial number of the vehicle ECU; After the coded serial number is successfully matched with the built-in support list of the vehicle to be tested, a standard control instruction for driving the door and window to be raised or lowered is sent to the ECU and the limit status of the target door and window is obtained in real time; Based on the built-in standard value of the vehicle to be tested and the limit state, adjust the limit threshold of the target door and window and return the calibration result, wherein the limit threshold is used to ensure that the state detection result of the ECU matches the actual state; After the calibration result successfully matches the system preset target value, exit the calibration mode.

2. The method according to claim 1, characterized in that The step of sending a handshake request of a first communication protocol to the vehicle under test according to the identity information of the vehicle under test, where the first communication protocol is one of multiple communication protocols adopted by the brand of the vehicle under test, specifically includes: Parsing the vehicle identification code of the vehicle to be tested based on the identity information of the vehicle to be tested, and retrieving a list of preferred protocols that match the manufacturer of the vehicle to be tested and are pre-sorted by historical connection success rate from a built-in protocol database based on the vehicle identification code; A handshake request of a first communication protocol is sent to the vehicle to be tested, where the first communication protocol is a protocol ranked first selected from the preferred protocol list.

3. The method according to claim 2, characterized in that The step of receiving a protocol response value of the vehicle under test, determining whether the vehicle under test supports the first protocol according to the protocol response value, and if not, switching to the second protocol and sending a handshake request until communication is established specifically includes: Receive a protocol response value from the vehicle under test, determine whether the vehicle under test supports the first communication protocol based on the protocol response value, and if not, select the second-ranked protocol from the preferred protocol list as the second communication protocol to send a handshake request until communication is established.

4. The method according to claim 1, wherein After the step of sending a standard control instruction for driving door and window lifting to the ECU and acquiring the limit status of the target door and window in real time after the coded serial number is successfully matched with the built-in support list of the vehicle to be tested, the method further includes: During the travel period when the target door or window is driven by the standard control instruction to move from the starting position to the end position, characteristic parameters of the target door or window for door or window lifting and lowering are acquired at a preset acquisition frequency; After comparing the characteristic parameters with the reference parameter model corresponding to the vehicle to be tested, a calibration quality quantitative score is generated through a weighted algorithm according to the deviation of the comparison result; When the calibration quality quantization score is lower than the health threshold corresponding to the benchmark parameter model, calibration optimization suggestions are matched and generated from a preset expert rule library based on the characteristic parameters with the largest deviation.

5. The method according to claim 4, characterized in that After comparing the characteristic parameters with the reference parameter model corresponding to the vehicle to be tested, the step of generating a calibration quality quantization score by a weighted algorithm according to the deviation of the comparison result specifically includes: Performing data alignment and mapping on the time series of the characteristic parameters to generate a quality fingerprint curve describing the load state of the motor; Analyzing the quality fingerprint curve and the reference parameter model corresponding to the vehicle under test through morphological matching and difference analysis, thereby obtaining the deviation of key feature points on the quality fingerprint curve relative to corresponding feature points of the reference parameter model; According to the deviation, a calibration quality quantization score is generated through a weighted algorithm.

6. The method according to claim 1, characterized in that Before the step of adjusting the limit thresholds of the target doors and windows based on the built-in standard value of the vehicle to be tested and the limit state and returning a calibration result, wherein the limit thresholds are used to ensure that the state detection result of the ECU matches the actual state, the method further includes: Initiate a query request to the cloud server based on the identity information of the vehicle to be tested, wherein the identity information includes vehicle model, age, and mileage information; The built-in standard value is corrected by the dynamic reference value corresponding to the vehicle condition to be tested and returned by the cloud server according to the identity information.

7. The method according to claim 1, characterized in that The step of adjusting the limit threshold of the target door and window based on the built-in standard value of the vehicle to be tested and the limit state and returning the calibration result, wherein the limit threshold is used to ensure that the state detection result of the ECU matches the actual state, specifically includes: When the target door or window is driven to be raised or lowered for the first time, a positive offset is applied to the built-in standard value as a first limit threshold, the door or window is driven to be raised or lowered, and a first error between the first limit state and the target position is recorded; Applying a negative offset to the built-in standard value as a second limit threshold, driving the door and window to move up and down and recording a second error between the second limit state and the target position; Based on the initial boundary range established by the first limit threshold and the second limit threshold, the limit threshold of the target door and window is adjusted using the golden section method until the error between the limit state of the final limit threshold and the built-in standard value is less than a preset accuracy; Generate the calibration result of the final limit threshold.

8. A handheld device, characterized in that: The handheld device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the handheld device to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a handheld device, the handheld device is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a handheld device, the handheld device is caused to execute the method according to any one of claims 1 to 7.

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