Vehicle body control function logic conflict detection method, device and equipment and storage medium

Abstract

According to the vehicle body control function logic conflict detection method, device and equipment and the storage medium, comprehensive verification of vehicle body control function logic in a multi-condition composite scene can be achieved by means of a pre-constructed logic model, and hidden conflict omission caused by scene coverage limitation in manual detection can be avoided; objective comparison of the data and the model is completed by means of a preset algorithm, the problem of misjudgment caused by judgment standard differences of different technicians can be eliminated, and conflict missing detection or false detection conditions are reduced; through the targeted conflict positioning and diagnosis process, the fault source can be quickly locked, repeated disassembly testing is not needed, and the troubleshooting period is greatly shortened; meanwhile, the method can realize automatic whole vehicle detection, breaks through the duration limit of 2-3 hours of manual detection, adapts to the batch detection demand of a vehicle production line, further improves the whole vehicle production efficiency and the quality control level, provides a guarantee for the operation safety of a vehicle body control system, and is suitable for popularization and application. And the quality control requirement of the whole vehicle manufacturing end and the driving experience requirement of the consumption end are both considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle body control systems, in particular to a vehicle body control function logic conflict detection method, device, equipment and storage medium. BACKGROUND

[0002] From the perspective of vehicle manufacturing, vehicle manufacturers continuously improve the product control standards for vehicle driving safety and system operation reliability; from the consumer end, users' demands for driving comfort and intelligent interaction experience continue to upgrade. Under the dual driving of these two factors, the logic complexity of vehicle body control functions is growing exponentially. An efficient and accurate vehicle body control function logic conflict detection technology has become a core requirement for guaranteeing product quality and meeting market demand in the vehicle body control field.

[0003] In related technologies, the detection of vehicle body control function logic conflicts mainly relies on traditional detection modes that simulate working conditions manually. Technical personnel manually operate vehicle function keys to simulate different driving scenarios, and then manually check whether the function execution logic meets the design specifications by combining sensor and control unit signals read by the vehicle diagnostic device.

[0004] However, due to the limitations of manpower and time cost, it is impossible to fully cover multiple conditional composite scenarios, which may miss hidden logic conflicts and cause safety hazards. Secondly, different technical personnel have different understanding and judgment standards for function logic, which may cause misjudgment of signal data and result in missed or false detection of conflicts. Finally, even if function logic abnormalities are found, it is difficult for humans to quickly locate the root cause of the fault, which requires repeated disassembly and testing, significantly prolonging the fault troubleshooting period. SUMMARY

[0005] The present application provides a vehicle body control function logic conflict detection method, device, equipment and storage medium, which can solve the technical problems of incomplete coverage of multiple conditional composite scenarios, subjective judgment of personnel, low fault root cause positioning efficiency, and detection speed that cannot match the demand for mass production of automobiles in the related art.

[0006] In a first aspect, the embodiments of the present application provide a vehicle body control function logic conflict detection method, which comprises: Collecting various types of data related to vehicle body control, comparing the collected real-time data with a vehicle body control function logic model constructed in advance based on vehicle design principles and control strategies, and detecting whether there is a logic conflict in the vehicle body control function through a preset algorithm; Locating and diagnosing the detected logic conflict, determining the cause and specific location of the conflict, feeding back the conflict information and diagnosis results, and processing the conflict according to a preset strategy.

[0007] In combination with the first aspect, in an implementation, the vehicle body control related data collected includes: The sensor data of the key parts of the vehicle body, the control signals of the vehicle body control system, and the vehicle running state information are collected, and different collection frequencies and accuracy standards are set according to the characteristics and importance of different types of data.

[0008] In combination with the first aspect, in an implementation, the sensor data of the key parts of the vehicle body includes at least one of vehicle speed, vehicle door opening and closing state, ambient light intensity, temperature, and pressure data. The control signals of the vehicle body control system include at least one of vehicle window lifting instructions, wiper control signals, and door lock control signals. The vehicle running state information includes at least one of engine working state, power storage component power, and vehicle driving mode information.

[0009] In combination with the first aspect, in an implementation, the vehicle body control function logic model constructed in advance based on vehicle design principles and control strategies includes: By studying vehicle design data, the function logic is analyzed, the function priority and execution rules under multiple scene superposition are sorted out, and appropriate modeling methods are used to complete the construction. Through comparison and verification with actual vehicle control behavior and optimization adjustment, the logical relationship and constraint conditions between each vehicle body control function are determined.

[0010] In combination with the first aspect, in an implementation, the real-time data collected are compared with the vehicle body control function logic model constructed in advance based on vehicle design principles and control strategies, and a preset algorithm is used to detect whether there is a logic conflict in the vehicle body control function, including: The collected raw data are preprocessed by cleaning, converting, and normalizing to eliminate noise and outliers in the data; The preprocessed data are substituted into the vehicle body control function logic model for inference calculation to obtain the theoretical running state of the vehicle body control function; The theoretical running state is compared with the actually collected control signals. If the difference between them exceeds the preset error range, it is determined that there is a logic conflict, and the specific type of the conflict is determined.

[0011] In combination with the first aspect, in an implementation, the detected logic conflict is located and diagnosed, including: Taking the conflict phenomenon as the top event, the fault tree analysis method is used to decompose layer by layer to obtain various potential fault causes; The signal transmission path in the vehicle body control system is tracked throughout the process to locate the key nodes of signal abnormalities; The expert system constructed in combination with historical conflict data and field expert experience performs comprehensive diagnosis on the conflict and generates a diagnosis report.

[0012] In combination with the first aspect, in an implementation manner, the feedback of the conflict information and the diagnosis result, and the processing of the conflict according to the preset strategy, include at least one of the following: The conflict information is fed back to a body control related unit through a vehicle internal communication network, and an emergency processing or an alarm reminding operation is performed by the control unit; A fault report containing a conflict type, a position of occurrence and a specific processing suggestion is generated, for a maintenance personnel to read and perform fault troubleshooting; For a simple logic conflict, an automatic repair is performed by automatically switching a backup sensor or adjusting a device operation parameter.

[0013] In the second aspect, the embodiments of the present application provide a vehicle body control function logic conflict detection device, and the vehicle body control function logic conflict detection device includes: A data acquisition and conflict detection module is configured to acquire various types of data related to vehicle body control, compare real-time data acquired with a vehicle body control function logic model constructed in advance based on vehicle design principles and control strategies, and detect whether there is a logic conflict in the vehicle body control function through a preset algorithm; A conflict positioning diagnosis and feedback processing module is configured to position and diagnose the detected logic conflict, determine a cause and a specific position of the conflict, feed back the conflict information and the diagnosis result, and process the conflict according to a preset strategy.

[0014] In the third aspect, the embodiments of the present application provide a vehicle body control function logic conflict detection device, which includes a processor, a memory, and a vehicle body control function logic conflict detection program stored in the memory and executable by the processor, wherein when the vehicle body control function logic conflict detection program is executed by the processor, the steps of the vehicle body control function logic conflict detection method described in the above embodiments are implemented.

[0015] In the fourth aspect, the embodiments of the present application provide a computer readable storage medium, which stores a vehicle body control function logic conflict detection program, wherein when the vehicle body control function logic conflict detection program is executed by a processor, the steps of the vehicle body control function logic conflict detection method described in the above embodiments are implemented.

[0016] The technical scheme provided by the embodiments of the present application has the following beneficial effects: The method can realize comprehensive verification of the body control function logic in a multi-condition complex scene by relying on a pre-constructed logical model, can avoid missing of implicit conflicts caused by scene coverage limitations of manual detection, can eliminate misjudgment problems caused by differences in judgment standards of different technical personnel by completing objective comparison of data and model with the help of a preset algorithm, can reduce conflict missing or misjudgment, can quickly lock the fault source through a targeted conflict positioning and diagnosis process without repeated disassembly and testing, greatly shortens the fault troubleshooting period, and can realize automatic whole vehicle detection, breaks through the time limit of 2-3 hours of manual detection, adapts to the batch detection demand of the automobile production line, and further improves the whole vehicle production efficiency and quality control level, provides a strong guarantee for the operation safety and reliability of the body control system, and meets the quality control requirements of the whole vehicle manufacturing end and the driving experience requirements of the consumer end. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 FIG. 1 is a flowchart of a body control function logic conflict detection method in an embodiment of the present application; Figure 2 FIG. 2 is a flowchart of data collection in the body control function logic conflict detection method in the embodiment of the present application; Figure 3 FIG. 3 is a flowchart of logical model construction in the body control function logic conflict detection method in the embodiment of the present application; Figure 4 FIG. 4 is a flowchart of a conflict detection algorithm in the body control function logic conflict detection method in the embodiment of the present application; Figure 5 FIG. 5 is a flowchart of a fault tree analysis example in the body control function logic conflict detection method in the embodiment of the present application; Figure 6 FIG. 6 is a flowchart of a feedback and processing mechanism in the body control function logic conflict detection method in the embodiment of the present application; Figure 7 FIG. 7 is a hardware structure diagram of a body control function logic conflict detection device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to enable personnel in the technical field to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0019] As the automotive industry undergoes a profound transformation towards intelligent and electric vehicles, the body control system, as a core component of the vehicle's electronic architecture, is continuously expanding its integrated functional dimensions. It now covers dozens of key functions, including door control, window operation, headlight adjustment, wiper control, central locking, and air conditioning management, with increasingly stringent requirements for the coordinated operation of these functions. From the perspective of vehicle manufacturing, automakers are constantly raising their quality control standards for vehicle driving safety and system reliability. From the consumer perspective, users' demands for driving comfort and intelligent interactive experiences are also continuously upgrading. Driven by these dual factors, the logical complexity of body control functions is increasing exponentially. An efficient and accurate body control function logic conflict detection technology has become a core necessity in the field of body control to ensure product quality and meet market demands.

[0020] In the industry, the detection of logical conflicts in vehicle body control functions mainly relies on the traditional testing mode of manually simulating working conditions. Technicians manually operate the various function buttons of the vehicle to simulate different driving scenarios, and then combine the sensor and control unit signals read by the on-board diagnostic equipment to manually check whether the function execution logic conforms to the design specifications.

[0021] However, due to limitations in manpower and time costs, it is impossible to fully cover complex scenarios with multiple conditions, which can easily lead to the omission of hidden logical conflicts and create potential safety hazards. Secondly, different technicians have different understandings and judgment standards of functional logic, which can easily lead to misjudgments of signal data, resulting in missed or false detections of conflicts. Thirdly, even if functional logic abnormalities are found, it is difficult for humans to quickly locate the root cause of the fault, requiring repeated disassembly and testing, which significantly prolongs the fault diagnosis cycle. Finally, it usually takes 2-3 hours for humans to complete a full vehicle inspection, and the inspection efficiency cannot match the batch inspection requirements of the automotive production line, which restricts the improvement of vehicle production efficiency and quality control level. To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0022] In a first aspect, embodiments of this application provide a method for detecting logical conflicts in vehicle body control functions.

[0023] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the vehicle body control function logic conflict detection method of this application. Figure 1 As shown, the method for detecting logic conflicts in vehicle body control functions includes: S100: Collects various data related to vehicle body control, compares the collected real-time data with the pre-built vehicle body control function logic model based on vehicle design principles and control strategies, and detects whether there are logical conflicts in the vehicle body control function through preset algorithms. S200: locating and diagnosing the detected logical conflict, determining the cause and specific location of the conflict, feeding back the conflict information and diagnosis result, and processing the conflict according to a preset strategy.

[0024] In this embodiment, first, various types of data related to body control are collected, the collected real-time data are compared with a body control function logic model constructed in advance based on vehicle design principles and control strategies, whether there is a logical conflict in the body control function is detected through a preset algorithm, the detected logical conflict is located and diagnosed to determine the cause and specific location of the conflict, the conflict information and diagnosis result are fed back, and the conflict is processed according to a preset strategy. This method can realize comprehensive verification of the body control function logic under multiple condition composite scenarios relying on the pre-constructed logic model, can avoid the omission of implicit conflicts caused by the scene coverage limitations of manual detection; with the help of the preset algorithm to complete the objective comparison of data and model, the misjudgment problem caused by the difference in judgment standards of different technical personnel can be eliminated, and the conflict missed detection or misjudgment situation can be reduced; through the targeted conflict positioning and diagnosis process, the fault root cause can be quickly locked, without repeated disassembly test, the fault troubleshooting cycle is greatly shortened; at the same time, this method can realize automatic whole vehicle detection, breaks through the time limit of 2-3 hours of manual detection, adapts to the batch detection demand of automobile production line, and further improves the whole vehicle production efficiency and quality control level, provides a strong guarantee for the operation safety and reliability of the body control system, and meets the quality control requirements of the whole vehicle manufacturing end and the driving experience demand of the consumer end.

[0025] Further, in an embodiment, in S100, the following steps are included: S101: collecting sensor data of key parts of the vehicle body, control signals of the vehicle body control system, and vehicle running state information, and setting differentiated collection frequency and accuracy standards for different types of data characteristics and importance.

[0026] In this embodiment, the sensor data of the key parts of the vehicle body, the control signals of the vehicle body control system and the vehicle running state information are collected, and different types of data are configured with different collection frequencies and precision standards according to their own characteristics and the importance of the vehicle body control logic detection. Through directional collection of multi-dimensional data strongly related to vehicle body control function, comprehensive coverage of vehicle body running state and control instruction can be realized. The design of different collection standards for different data can ensure the real-time and accuracy of core data, avoid system resource redundancy and data processing load caused by indiscriminate collection, provide high-quality data support for subsequent real-time data and preset logic model accurate comparison, reduce the conflict detection deviation caused by data missing, insufficient precision or frequency lag from the data source, and further improve the reliability and efficiency of the overall detection process.

[0027] Further, in an embodiment, the sensor data of the key parts of the vehicle body includes at least one of vehicle speed, door opening and closing state, ambient light intensity, temperature and pressure data; the control signals of the vehicle body control system include at least one of vehicle window lifting instruction, wiper control signal and door lock control signal; the vehicle running state information includes at least one of engine working state, power storage component power and vehicle driving mode information.

[0028] In this embodiment, the sensor data of the key parts of the vehicle body includes at least one of vehicle speed, door opening and closing state, ambient light intensity, temperature and pressure data, the control signals of the vehicle body control system include at least one of vehicle window lifting instruction, wiper control signal and door lock control signal, and the vehicle running state information includes at least one of engine working state, power storage component power and vehicle driving mode information. The directional and accurate collection of vehicle body control related data can ensure that the core data related to the vehicle body control function logic is not missed, and can cover the key data dimensions of the vehicle body running state, control instruction and core working condition. It also avoids the redundant occupation of system storage and operation resources caused by the collection of irrelevant data, and clearly defines the data range for the subsequent accurate comparison of real-time data and preset logic model, which can effectively reduce the invalid comparison and analysis deviation caused by ambiguous data category, improve the pertinence of conflict detection and the efficiency of the overall process, and ensure the accuracy of data matching and the effectiveness of conflict identification in the detection process.

[0029] Further, in an embodiment, in S100, the following steps are included: S102: Analyze the function logic by studying the vehicle design materials, sort out the function priority and execution rules under the superposition of multiple scenes, and complete the construction by using appropriate modeling methods. After comparison and verification with the actual vehicle control behavior and optimization adjustment, the logical relationship and constraint conditions between each vehicle body control function are determined.

[0030] In this embodiment, the internal logic of each control function of the vehicle body is analyzed by studying the vehicle design materials, and the priority order and execution rules of each function under the superposition of multiple scenes are sorted out. Then, the appropriate modeling method is selected to complete the construction of the logic model. The built model is compared and verified with the actual vehicle control behavior, and the model is optimized and adjusted according to the verification deviation. Finally, the logical relationship and constraint conditions between each vehicle body control function are determined in the model. It can ensure that the preset logic model called can accurately map the actual running logic of the vehicle body control function, especially can cover the function coordination rules under the superposition of multiple scenes, avoid the conflict missed detection caused by the missing or deviation of model logic, provide reliable reference for the accurate comparison of real-time data and model, and ensure the accuracy of the subsequent conflict detection link. At the same time, through the verification and optimization of the actual vehicle control behavior, the model can have stronger practicality and adaptability, and reduce the invalid detection caused by the disconnection between the model and the actual working condition.

[0031] Further, in an embodiment, in S100, S103 is included, which comprises the following steps: S103-1: The collected raw data is preprocessed by cleaning, converting and normalizing to eliminate noise and outliers in the data; S103-2: The preprocessed data is substituted into the vehicle body control function logic model for inference calculation to obtain the theoretical running state of the vehicle body control function; S103-3: Compare the theoretical running state with the actually collected control signal. If the difference between them exceeds the preset error range, it is determined that there is a logic conflict, and the specific type of the conflict is determined.

[0032] In this embodiment, the original data collected is first preprocessed by cleaning, conversion and normalization to eliminate mixed noise and abnormal values in the data, and then the standardized data after preprocessing is substituted into the pre-constructed body control function logic model to carry out reasoning calculation, so as to obtain the theoretical running state of the body control function, and finally the theoretical running state is compared with the actually collected control signal in all directions. If the deviation between the two exceeds the preset error range, it can be determined that there is a logic conflict in the body control function, and the specific type of the conflict is also determined. The standardized data preprocessing provides qualified data foundation for subsequent model reasoning, and the unified theoretical reference benchmark is established by means of model reasoning. Through the accurate comparison between theory and practice, the logic conflict can be effectively identified and the type is defined, which can ensure the rigor and accuracy of the conflict detection link and avoid invalid judgment caused by insufficient data quality or missing reference. It provides clear and reliable pre-determination basis for subsequent conflict positioning and processing.

[0033] Further, in one embodiment, in S200, S201 is included, which includes the following steps: S201-1: Taking the conflict phenomenon as the top event, the fault tree analysis method is used to decompose layer by layer to obtain various potential fault causes; S201-2: The signal transmission path in the body control system is tracked throughout the journey to locate the key node of signal anomaly; S201-3: Combined with the historical conflict data and the expert system constructed based on the experience of the field experts, comprehensive diagnosis is carried out on the conflict and a diagnosis report is generated.

[0034] In this embodiment, the detected body control function logic conflict phenomenon is taken as the top event, and the fault tree analysis method is used to decompose the top event layer by layer to sort out various potential fault causes that cause the conflict. The signal transmission path in the body control system is tracked throughout the journey to locate the key node of signal transmission anomaly. Finally, combined with the historical body control logic conflict data and the expert system built based on the experience of the field experts, the identified logic conflict is comprehensively diagnosed in multiple dimensions, and a diagnosis report containing the conflict causes, abnormal nodes and corresponding analysis conclusions is generated. Through the diagnosis logic of multiple methods, the accurate source of the conflict can be traced, the comprehensive analysis of the fault causes is realized through the fault tree analysis, the abnormal node is located through the signal tracking, and the reliability of the diagnosis conclusion is guaranteed by combining the historical data and the expert experience. It provides a clear and complete reference for the subsequent targeted processing of the conflict, which can effectively shorten the fault troubleshooting period and improve the overall efficiency of conflict processing.

[0035] Further, in one embodiment, in S200, S202 is included, which includes the following steps: S202-1: Feedback the conflict information to the body control related unit through the vehicle internal communication network, and execute emergency treatment or alarm reminder operation by the control unit; S202-2: Generate a fault report containing the conflict type, occurrence location and specific treatment suggestion for the maintenance personnel to read and carry out fault diagnosis; S202-3: For simple logic conflicts, automatically repair by automatically switching to backup sensors or adjusting device operating parameters.

[0036] In this embodiment, first, the identified logic conflict information is fed back to the body control related unit through the vehicle internal communication network, and the corresponding control unit executes emergency treatment operation or initiates alarm reminder to the driver and passenger according to the preset mechanism; then, a special fault report is generated for the located conflict, which clearly marks the specific type of conflict, the accurate location of occurrence and the specific fault treatment suggestion, so as to provide the maintenance personnel with clear guidance for directional fault diagnosis; at the same time, for the simple logic conflicts, automatic repair can be completed by automatically switching to backup sensors or adjusting device operating parameters. A multi-level conflict handling link is constructed, which not only realizes the immediate response to safety conflicts, but also provides clear guidance for professional maintenance, reduces the handling cost of simple faults through automatic repair mechanism, effectively shortens the conflict resolution period, guarantees the continuous and stable operation of the body control system, and improves the safety protection ability and operation convenience of the whole vehicle.

[0037] In summary, the implementation of the body control function logic conflict detection method follows the core steps of data collection start→logic model loading→conflict detection execution→conflict positioning and diagnosis→feedback and processing, and the technical content and corresponding implementation cases of each step are as follows: I. Data collection start (1) Core operation of the step Start trigger: When the vehicle starts or enters the detection mode, the data collection module is automatically started as shown in the following figure: Figure 2

[0038] Data collection range: Collect three types of data at a preset frequency and accuracy, which are body key part sensor data (such as vehicle speed, door opening and closing state, ambient light intensity, etc.), body control system control signal (such as window lifting instruction, wiper signal, door lock signal, etc.), and vehicle running state information (such as engine working state, battery capacity, driving mode, etc.).

[0039] Collection standard: Differentiate the frequency and accuracy for different data, such as safety critical data such as vehicle speed and steering angle, which are collected at a frequency of tens of times per second or more, and the accuracy of vehicle speed sensor can reach ±0.1 km / h; the collection frequency of stable data such as vehicle basic configuration is relatively low.

[0040] ​Data processing: The collected data is preliminarily sorted and cached, waiting for subsequent detection and analysis.

[0041] Specifically, the data acquisition module is the foundation of the entire detection system. Its main task is to collect various types of data related to body control, providing comprehensive and accurate data support for subsequent logic conflict detection. This module is responsible for collecting various types of data, including sensor data, control signals, and vehicle state information.

[0042] In terms of sensor data, it covers the output signals of sensors at various key positions of the vehicle body. For example, the vehicle speed sensor can monitor the vehicle's speed in real time, providing accurate speed data for vehicle body control functions related to speed; the door sensor can sense the opening and closing state of the door, ensuring the normal operation of the door control function; the light sensor is used to detect the intensity of ambient light, providing a basis for the automatic light control system, so that it can automatically turn on or off the headlights according to the change in light. In addition, there are temperature sensors, pressure sensors, etc., which collect information such as the temperature inside and outside the vehicle and tire pressure, etc. These data are crucial for the comfort and safety of the vehicle.

[0043] The collection of control signals is also an important task of the data acquisition module. Various control instructions in the body control system, such as window lifting instructions, wiper control signals, and door lock control signals, are accurately collected by this module. These control signals reflect the driver's operation intention and the decision output of the body control system. Through their collection and analysis, it can be determined whether each control function is executed as expected.

[0044] Vehicle state information is also indispensable, including the working state of the engine, the battery level, the driving mode of the vehicle (such as normal driving, reversing, parking, etc.). The information of the engine working state can help detect whether there is a logic conflict in the vehicle body control function related to the engine, such as the light control when the engine starts, the response of the air conditioning system, etc.; the battery level information is important for the detection of the vehicle's power distribution and energy-saving control function; and the recognition of the vehicle driving mode helps to determine whether the logic of the vehicle body control function is correct under different driving modes, for example, in the reversing mode, whether the reversing light and the reversing radar are working properly.

[0045] In order to ensure the accuracy and timeliness of the collected data, the data acquisition module has strict requirements for the frequency and accuracy of data acquisition. According to the characteristics and importance of different types of data, the corresponding acquisition frequency is set. For data such as vehicle speed and steering angle, which changes rapidly and is crucial to the safe driving of the vehicle, the acquisition frequency is relatively high, usually up to dozens of times per second or even higher, to capture the instantaneous changes of the vehicle state in real time. For some relatively stable vehicle state information, such as the basic configuration information of the vehicle, the acquisition frequency is relatively low. In terms of accuracy, high-precision sensors and data acquisition equipment are selected to ensure that the collected data can truly reflect the actual running state of the vehicle. For example, the accuracy of the vehicle speed sensor can reach ±0.1 km / h, which can accurately measure the speed of the vehicle and provide reliable data basis for logic conflict detection.

[0046] The data sources are extensive and complex. Sensor data comes directly from sensors installed on various parts of the vehicle. These sensors convert physical quantities into electrical signals, which are transmitted to the data acquisition module through dedicated signal transmission lines. Control signals come from the electronic control unit (ECU) of the vehicle body control system. The ECU generates corresponding control instructions based on the driver's operation and the vehicle's running state, and sends these instructions to the data acquisition module. Vehicle state information is obtained partly by sensors and partly by ECU through monitoring and calculation of vehicle systems. By integrating these data from different sources, the data acquisition module can comprehensively and accurately obtain various information related to vehicle body control, laying a solid foundation for subsequent logic conflict detection.

[0047] (II) Corresponding implementation case data acquisition scene Case 1 (high beam and passing light control conflict): The data acquisition module collects light control related data at a frequency of 50 Hz, including high beam 12V on / low beam 0V off state signal, passing light gear trigger 5V / release 0V operation signal, high beam 3A stable output actuator feedback signal, ECU no delay extinguishing instruction control signal.

[0048] Case 2 (vehicle door and light control conflict): The module collects real-time vehicle door sensor switch state voltage signal, ignition switch off 0V signal, and interior light control signal.

[0049] Case 3 (vehicle window and central locking control conflict): The module collects 60 km / h vehicle speed sensor data, central locking unlock state signal, and control signal that each vehicle door and window can respond to lifting.

[0050] II. Logic model loading (I) Step core operation Model retrieval: data acquisition at the same time, such as Figure 3As shown, the system loads a pre-constructed body control function logic model from the storage device, which is built based on vehicle design principles and control strategies, and clearly defines the logical relationships and constraints between functions.

[0051] Model verification: During loading, check the integrity and accuracy of the model, and if there are errors or incompleteness, prompt the user to repair or reconstruct.

[0052] Specifically, the construction of the logic model is the key link to realize the conflict detection of the body control function logic. Based on the vehicle design principles and control strategies, through the establishment of mathematical models and logical relationships, it accurately reflects the internal relationship and constraint conditions between each control function of the body, especially focusing on the function coordination logic under the superposition of multiple scenes, to avoid conflict detection missed due to incomplete single scene logic coverage.

[0053] When building the logic model, it is necessary to deeply study the vehicle design drawings, technical documents and control strategy instructions, comprehensively analyze the working principle and design intention of the body control system, and focus on sorting out the logical priority and execution rules of the same function module under the superposition of different scenes. Taking the light control system as an example, the coordination relationship between the basic lighting logic (such as high-low beam switching) and the special function logic (such as overtake light triggering) needs to be clarified: when the high beam is on, triggering the overtake light gear, the system should execute the "high beam keeps bright state → triggers momentary intensification signal → releases gear and high beam delays off" flashing logic; while the low beam is on, triggering the overtake light should execute the "high beam momentarily lights up → immediately off after releasing" logic. For the door control system, the joint control logic of the vehicle running state, key position, driver operation, etc. on the door lock needs to be clarified to avoid conflicts caused by single condition judgment.

[0054] Based on the understanding of vehicle design principles and control strategies, appropriate modeling methods and tools are used to build the logic model of body control functions. Common modeling methods include state machine model, Petri net model, etc. The state machine model describes the behavior of the system by defining different states of the system and the transition conditions between states. Taking the window control system as an example, the states of the window such as rising, falling, stopping, etc. and the conditions triggering the state transition such as pressing the rising button, releasing the button, the window reaching the limit position, etc. can be defined. Petri net model shows the sequence and relationship of events in the system in a graphical way, describes the dynamic behavior of the system through elements such as library, transition and token, and can more intuitively express complex logical relationships.

[0055] In the logical model, the logical relationships and constraints between functions are defined in detail. For example, in the body control system, there are some functions that are mutually exclusive, such as the window lifting function and the central locking function, which cannot be executed simultaneously in some cases to prevent system failure due to operational conflicts. By explicitly defining these mutual exclusion relationships in the logical model, potential logical conflicts can be detected in the detection process. At the same time, some dependent relationships of functions are also considered, such as the operation of the wiper, which usually depends on the starting state of the vehicle and the signal of the rain sensor. Only when the vehicle is started and the rain sensor detects rain, will the wiper work according to the corresponding control logic.

[0056] To verify the accuracy and effectiveness of the logical model, it is compared and analyzed with the actual vehicle control behavior. By simulating various actual working conditions, it is observed whether the output of the logical model is consistent with the control results of the actual vehicle. For example, during the simulation of vehicle driving, the body control functions under different vehicle speeds, road conditions, and driver operations are tested to check whether the logical model can accurately predict the control behavior of the vehicle. If deviations are found between the logical model and the actual situation, the model is adjusted and optimized in a timely manner to ensure that the model can truly reflect the logical relationships and constraints of the body control functions.

[0057] Model core logic examples Light control: when the low beam is turned on, the passing light is triggered, and the "high beam instant on→release gear immediately off" function needs to be implemented; when the high beam is turned on, the passing light is triggered, and the "high beam keeps on→release gear delays 1.5 seconds off" flashing logic needs to be implemented.

[0058] Door light control: when the vehicle is turned off and the door is opened, the interior light automatically turns on; after the door is closed, the light is turned off after a delay of 3 seconds.

[0059] Speed linkage control: when the vehicle speed is greater than or equal to 50 km / h, the central locking is automatically locked and only the driver's side can control the window lifting.

[0060] (II) Corresponding implementation case model basis The detection of the three cases is based on the preset logical model of the corresponding function, such as the light flashing logic of case one, the door light linkage logic of case two, and the speed central locking / window permission linkage logic of case three, which are the core rules of the loaded model.

[0061] III. Conflict detection execution (I) Core operation steps Data preprocessing: such as Figure 4The raw data collected is cleaned, converted, and normalized to eliminate noise, outliers, and inconsistencies in data format, making it suitable for model input requirements, such as filtering and denoising of sensor analog signals and unifying standards for different dimension data.

[0062] Logical matching: The preprocessed data is substituted into the logical model, and the theoretical running state of the body control function is obtained by reasoning and calculation according to the model rules.

[0063] Conflict judgment: Compare the theoretical state with the actual collected control signal. If the difference exceeds the allowed error range, it is determined that there is a logical conflict, and the conflict type (function mutual exclusion conflict, timing conflict, condition conflict, etc.) is specified.

[0064] Specifically, based on the collected data and the constructed logical model, through accurate calculation and analysis, it is quickly and accurately determined whether there is a logical conflict in the body control function, and the type and location of the conflict are determined.

[0065] The real-time data collected is compared with the normal logical relationship and constraint conditions defined in the logical model. When the data is inconsistent with the logic in the model, it is determined that there is a logical conflict. This algorithm mainly includes the following key steps: data preprocessing, logical matching, and conflict judgment.

[0066] In the data preprocessing stage, the collected raw data is cleaned, converted, and normalized to eliminate noise, outliers, and inconsistencies in the data, making it meet the input requirements of the logical model. For example, for the analog signals collected by sensors, noise interference is removed by filtering algorithms; for data collected by different sensors, normalization is performed according to their physical meaning and dimension to facilitate subsequent unified analysis.

[0067] In the logical matching stage, the preprocessed data is substituted into the logical model, and reasoning and calculation are performed according to the logical relationship defined in the model. For example, for the logical model of the light control system, the current vehicle driving state, environmental light intensity, and other data are input to calculate the type and state of the light that should be turned on in theory. Then, the calculation result is compared with the actual collected light control signal to check for any differences.

[0068] In the conflict judgment stage, it is judged whether there is a logical conflict according to the result of logical matching. If the calculation result is inconsistent with the actual data and the difference exceeds the allowed error range, it is determined that there is a logical conflict, and the type and position of the conflict are further analyzed. The conflict type may include functional mutual exclusion conflict, timing conflict, condition conflict, etc. Functional mutual exclusion conflict refers to the simultaneous activation of two or more mutually exclusive functions, such as the accidental unlocking of the vehicle door during driving; timing conflict refers to the order of function execution not meeting the logical requirements, for example, the wiper still not starting after a delay of a certain period of time when it is raining; condition conflict refers to the triggering condition of the function not being met but being executed, such as the automatic headlights being mistakenly turned on in the daytime when the light is sufficient.

[0069] To more clearly illustrate the working process of conflict detection, the following typical scene of light control is taken as an example: In the vehicle light control system design specification, it is clearly specified that the core logic of the overtaking light function is "no matter the current light state, when the overtaking light gear is triggered, the flashing reminder effect of high beam light must be realized", which is specifically divided into two scenarios: Scenario one, when the low beam light is on, trigger the overtaking light gear → high beam light is immediately turned on, release the gear → high beam light is immediately turned off; Scenario two, when the high beam light is on, trigger the overtaking light gear → high beam light remains on (the visual flashing effect is realized by strengthening the current signal), release the gear → high beam light is delayed for 1.5 seconds to turn off. When the detection system is running, the data acquisition module collects light control signals (low / high beam light state, overtaking light gear signal), light executor feedback signals (high beam light current value, lighting duration) and driver operation signals in real time. When the combination of "high beam light on signal exists + overtaking light gear trigger signal" is detected, the algorithm compares the real-time data with the scenario two rule in the logical model. If it is found that after releasing the overtaking light gear, the high beam light current value does not appear the "maintain-sudden drop" change curve, and the lighting duration does not produce a 1.5 second delay, it is determined that there is a logical conflict, and the high beam light cannot realize the flashing reminder effect according to the specification. At this time, the algorithm records the trigger condition of the conflict (high beam light on + overtaking light trigger), abnormal data (current stable without fluctuation, delay time is 0) and the function module involved (light control ECU, high beam light executor), which provides accurate basis for subsequent positioning.

[0070] (II) Conflict judgment process corresponding to implementation case Case one: After substituting the collected light data into the model, it is found that in the "high beam light on + overtaking light release" combination scenario, the high beam light current does not have a "maintain-sudden drop" change curve, and there is no 1.5 second delay off instruction, which does not meet the model rule, and it is determined that there is a logical conflict.

[0071] Case 2: In the model, "ignition switch off + door open" should trigger the light to turn on, but the actual data collection shows that this combination does not trigger the light to turn on, but "door closed" triggers the light to turn on, which is a logical inversion. It is determined as a timing / condition conflict.

[0072] Case 3: The model requires the central lock to be closed and the window authority to be limited when the vehicle speed is ≥50km / h, but in reality, the central lock is not closed and all windows can be lifted when the speed is 60km / h. The trigger condition is not met, but the corresponding logic is not executed. It is determined as a condition conflict.

[0073] Four, conflict positioning and diagnosis (1) Step core operation Fault tree analysis: As shown in Figure 5 , taking the conflict phenomenon as the top event, the potential fault reasons are decomposed layer by layer from the dimensions of software logic, hardware circuit, and signal transmission to build a fault tree.

[0074] Signal tracking: Monitor the whole process of signal transmission path in the body control system to locate the key node of signal anomaly.

[0075] Comprehensive diagnosis: Combine historical conflict data and expert system to complete diagnosis and generate a diagnosis report containing the causes of the conflict and the fault location.

[0076] Specifically, when the conflict detects that there is a logical conflict in the body control function, the conflict positioning and diagnosis module will quickly start. Its main task is to analyze the causes of the conflict in depth and accurately determine the specific location of the conflict, providing strong support for subsequent problem solving.

[0077] Conflict positioning and diagnosis employ a variety of advanced methods and techniques, among which fault tree analysis (FTA) is a commonly used and effective means. Fault tree analysis takes the conflict phenomenon as the top event, and through layer-by-layer decomposition, finds out all possible bottom events and their logical relationships that lead to the top event, thus constructing an inverted tree diagram. Taking the logical conflict of the high beam control (the high beam light triggers the passing light without flashing effect) as an example, the top event is defined as "passing light flashing function failure under high beam light on state", and the intermediate events are decomposed from three dimensions of software logic, hardware circuit, and signal transmission: software logic level includes "light control ECU passing light algorithm vulnerability" and "high beam light and passing light logic priority configuration error"; hardware level includes "high beam light relay sticking" and "actuator current detection module failure"; signal transmission level includes "passing light gear signal transmission delay" and "ECU and actuator communication interruption". Through the construction of fault tree, the logical relationship of each potential cause can be clearly displayed. Further combined with signal tracing technology, the signal flow after the passing light is triggered is monitored throughout: from the signal sent by the passing light switch, the transmission state in the LIN bus, the processing signal after ECU receives, and the control signal output from ECU to high beam light actuator, if it is found that ECU does not generate "delay extinguishing" control instruction after receiving passing light signal, the problem root cause is software algorithm vulnerability rather than hardware failure, greatly improving the diagnosis efficiency.

[0078] Signal tracing technology is also one of the important methods of conflict positioning and diagnosis. This technology tracks and monitors the signal transmission path in the body control system, finds the abnormal nodes of the signal, and determines the location of the conflict. Taking the logical conflict of the window lifting function as an example, when the window cannot be lifted normally, the control signal sent from the window switch is traced, and the transmission of the signal in the wire, relay, motor driver and other components is checked, to observe whether there is signal loss, short circuit or error. If it is found that the signal at a certain component does not match the expected, it can be determined that this component may be the location of the conflict.

[0079] In addition to the above methods, data analysis, experience knowledge and expert system are also used for comprehensive diagnosis. Through the analysis of a large amount of historical data, the patterns and rules of common logical conflicts are summarized, providing reference for conflict diagnosis. For example, certain specific sensor failures often lead to specific types of logical conflicts, through the learning of these historical data, it can be quickly judged that the conflict may be caused by which sensor. At the same time, by using expert system, the experience knowledge of experts in the field of automobiles is transformed into computer recognizable rules and knowledge base, when encountering logical conflict, the expert system can reason and judge according to these rules, and provide diagnosis suggestions.

[0080] In practical applications, the conflict positioning and diagnosis module usually generates a detailed diagnosis report containing detailed description of the conflict, possible cause analysis, located faulty components or logical links, etc. For example, for the conflict of the abnormally bright brake light, the diagnosis report may point out that the conflict phenomenon is that the brake light is on when the brake is not pressed; the possible causes include brake light switch failure (probability 60%), brake light control circuit short circuit (probability 30%), and vehicle body control unit software error (probability 10%); after signal tracking and circuit detection, it is preliminarily located that the fault may occur at the brake light switch, and it is suggested to further check the electrical performance and mechanical state of the brake light switch. Such a diagnosis report provides clear maintenance direction for maintenance personnel, greatly improving the efficiency of fault troubleshooting and repair.

[0081] (II) Positioning and diagnosis process corresponding to implementation cases Case 1: Excluding hardware relay failure (current stable without fluctuation) and signal transmission problem (bus without packet loss) through fault tree analysis, locking software level; then locating the passing light algorithm of the light control ECU through signal tracking, finding that it does not set a delay extinguishing branch for the "high beam light on" scene, but only follows the "immediate extinguishing" code of the low beam light scene.

[0082] Case 2: Through signal tracking technology, it is located that the communication line between the door sensor and the light ECU is connected in reverse, causing signal logic transmission error and causing light control abnormality.

[0083] Case 3: Excluding vehicle speed sensor failure (vehicle speed data is accurate) through fault tree analysis, finally locating that the software threshold of "vehicle speed triggering central locking" in the vehicle body control unit (BCU) is mistakenly set to 80 km / h, not meeting the model triggering condition of 50 km / h.

[0084] V. Feedback and processing (I) Core operation of the step is as shown in Figure 6 Feedback to vehicle control system: through controller area network (CAN), local area network (LIN) and other communication networks, conflict information is sent to the body control unit (BCU) or electronic control unit (ECU), and the control unit executes emergency processing (such as automatic locking of vehicle doors) or alarm reminding.

[0085] Feedback to maintenance personnel: generate a fault report containing conflict type, location and processing suggestion, which can be read through the on-board diagnostic system (OBD) interface to guide maintenance work.

[0086] Automatic repair / adjustment: for simple conflicts, the system can automatically switch to backup sensors, adjust device operating parameters; if the repair is invalid, it will feedback to manual processing.

[0087] ​Specifically, for vehicle control systems, the detection system transmits conflict information to the Body Control Unit (BCU) or other relevant Electronic Control Units (ECUs) in a specific format and protocol via the vehicle's internal communication network, such as Controller Area Network (CAN) or Local Interconnect Network (LIN). Upon receiving the conflict information, the BCU or ECU will take appropriate action according to a preset processing strategy. For example, when a logical conflict is detected where a door unexpectedly unlocks while the vehicle is in motion, the detection system sends the conflict information to the BCU. The BCU immediately initiates an emergency procedure, automatically relocking the door and alerting the driver through the vehicle's alarm system to check the door status. Simultaneously, the BCU records the time and location of the conflict, along with relevant vehicle status information, for subsequent fault analysis and handling.

[0088] For repair personnel, the diagnostic system generates a detailed fault report, containing information such as the type and location of the conflict, possible causes, and corresponding troubleshooting suggestions. The fault report can be output via the On-Board Diagnostics (OBD) interface. Repair personnel can read the report using specialized diagnostic equipment connected to the vehicle's OBD interface. For example, when a logical conflict is detected in the vehicle's lighting control system, the fault report might show: the conflict type is that both low beam and high beam are on simultaneously; the conflict location is at a relay in the lighting control circuit; the possible cause is a stuck relay; and the recommended solution is to replace the relay and check other components in the lighting control circuit for similar problems. Based on the information provided in the fault report, repair personnel can quickly and accurately troubleshoot and repair the problem, improving repair efficiency.

[0089] Some advanced detection systems also possess automatic repair or adjustment functions to handle simple logical conflicts. For example, when a logical conflict caused by an abnormal sensor signal is detected, the system can automatically switch to a backup sensor or perform reasonable estimation and compensation based on data from other relevant sensors to maintain the normal operation of the vehicle's control functions. In window control, if excessive current is detected in the window motor, it may indicate resistance during window operation. The system will automatically reduce the motor's output power and attempt to continue raising or lowering the window with less force to avoid damage due to motor overload. If the problem persists after multiple attempts, the system will then relay the conflict information to the driver and maintenance personnel for further processing.

[0090] The implementation of automatic repair or adjustment function usually relies on the intelligent algorithm and pre-set strategy of the system. The system will select the appropriate repair or adjustment method according to the type and severity of the conflict. At the same time, in order to ensure the safety and effectiveness of automatic repair or adjustment, the system will monitor and verify the body control function after repair or adjustment in real time, and stop automatic operation immediately once a problem is found, and return the control to the driver or maintenance personnel.

[0091] (II) Corresponding implementation case processing Case one: The technician supplements the algorithm branch of "1.5 seconds delay extinguishing after overtaking light release in high beam on state" for the light control ECU according to the diagnostic report, and after upgrading, the high beam current can smoothly decrease from 3A to 0A, the delay time is accurate to 1.5 seconds, and the standard flickering reminder effect is restored.

[0092] Case two: The maintenance personnel reorganize and correct the communication line between the door sensor and the light ECU, and after repair, the interior light automatically turns on when the door is opened and turns off after 3 seconds, restoring the normal use logic.

[0093] Case three: The technician corrects the vehicle speed trigger threshold in the BCU to 50km / h through the diagnostic device, and after testing, the central locking is automatically locked when the vehicle speed meets the standard, and the non-driver side window lifting function is limited, which meets the safety design requirements.

[0094] In a second aspect, the embodiments of the present application also provide a vehicle body control function logic conflict detection device, which comprises: a data acquisition and conflict detection module, which is used to acquire various types of data related to vehicle body control, compare the acquired real-time data with a vehicle body control function logic model constructed in advance based on vehicle design principles and control strategies, and detect whether there is a logic conflict in the vehicle body control function through a pre-set algorithm; a conflict positioning diagnosis and feedback processing module, which is used to position and diagnose the detected logic conflict, determine the cause and specific position of the conflict, feed back the conflict information and diagnosis result, and process the conflict according to a pre-set strategy.

[0095] Among the above vehicle body control function logic conflict detection device, the functions of each module correspond to the steps in the above vehicle body control function logic conflict detection method embodiments, and the functions and implementation processes will not be repeated here.

[0096] In a third aspect, the embodiments of the present application provide a vehicle body control function logic conflict detection device. The vehicle body control function logic conflict detection device can be a personal computer (PC), a notebook computer, a server, or other devices with data processing functions.

[0097] ReferenceFigure 7 , Figure 7 Fig. 1 is a schematic diagram of a hardware structure of a vehicle body control function logic conflict detection device according to an embodiment of the present application.

[0098] The communication bus can be of any type, for interconnecting the processor, the memory and the communication interface.

[0099] The communication interface includes an input / output (I / O) interface, a physical interface and a logical interface, etc. for interconnecting devices inside the vehicle body control function logic conflict detection device, and for interconnecting the vehicle body control function logic conflict detection device with other devices (e.g. other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber interface, an ATM interface, etc. The user device can be a display (Display), a keyboard (Keyboard), etc.

[0100] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0101] The processor can be a general-purpose processor, which can invoke a vehicle body control function logic conflict detection program stored in the memory and execute the vehicle body control function logic conflict detection method provided by the embodiments of the present application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed by the vehicle body control function logic conflict detection program when invoked can refer to each embodiment of the vehicle body control function logic conflict detection method of the present application, which will not be described here.

[0102] Those skilled in the art can understand that the hardware structure shown in the above embodiments of the present application does not constitute a limitation on the present application, and can include more or fewer components than those shown, or combine certain components, or different component arrangements. Figure 7

[0103] In a fourth aspect, the embodiments of the present application also provide a readable storage medium. ​

[0104] The vehicle body control function logic conflict detection program is stored on a readable storage medium of the application, and when the vehicle body control function logic conflict detection program is executed by a processor, the steps of the vehicle body control function logic conflict detection method described above are implemented.

[0105] The method implemented when the vehicle body control function logic conflict detection program is executed can refer to each embodiment of the vehicle body control function logic conflict detection method of the application, which will not be described here.

[0106] It should be noted that the above-mentioned sequence numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0107] The terms "include" and "have" and any variations thereof in the specification and claims of the application and the above-mentioned drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device. The terms "first", "second" and "third" and the like descriptions are used to distinguish different objects, and do not represent the order or limit the types of "first", "second" and "third".

[0108] In the description of the embodiments of the application, "exemplary", "for example" or "for instance" is used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplary", "for example" or "for instance" in the embodiments of the application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. In fact, the words "exemplary", "for example" or "for instance" are intended to present the relevant concept in a specific way.

[0109] In the description of the embodiments of the application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in the text only describes the relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, A and B together, and B alone. In addition, in the description of the embodiments of the application, "multiple" means two or more than two.

[0110] In some of the processes described in this specification, the order of operations or steps can be modified. Specifically, the serial order of any two consecutive steps carried out according to the processes described in this specification can be changed so that these two steps can be carried out in parallel or simultaneously, or the order of these two steps can be reversed.

[0111] Those skilled in the art can clearly understand the above-mentioned embodiment method from the description of the above embodiments, which can be realized by software and a necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disc) and includes a plurality of instructions for causing a terminal device to execute the methods described in the various embodiments of the present application.

[0112] The above is only a preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for detecting logical conflicts in vehicle body control functions, characterized in that, The method for detecting logical conflicts in the vehicle body control function includes: Collect various data related to vehicle body control, compare the collected real-time data with the pre-built logical model of vehicle body control function based on vehicle design principles and control strategies, and detect whether there are logical conflicts in the vehicle body control function through preset algorithms. The system locates and diagnoses detected logical conflicts, determines the cause and specific location of the conflict, feeds back the conflict information and diagnosis results, and handles the conflict according to a preset strategy.

2. The method for detecting logical conflicts in vehicle body control functions as described in claim 1, characterized in that, The collection of various data related to vehicle body control includes: It collects sensor data from key parts of the vehicle body, control signals from the vehicle control system, and vehicle operating status information, and sets differentiated collection frequencies and accuracy standards based on the characteristics and importance of different types of data.

3. The method for detecting logical conflicts in vehicle body control functions as described in claim 2, characterized in that, The sensor data for the key parts of the vehicle body includes at least one of the following: vehicle speed, door opening and closing status, ambient light intensity, temperature, and pressure data. The control signals of the vehicle body control system include at least one of the following: window lifting command, windshield wiper control signal, and door lock control signal; The vehicle operating status information includes at least one of the following: engine operating status, power storage component charge level, and vehicle driving mode information.

4. The method for detecting logical conflicts in vehicle body control functions as described in claim 1, characterized in that, The pre-built vehicle body control function logic model based on vehicle design principles and control strategies includes: By studying vehicle design data to analyze functional logic, sorting out functional priorities and execution rules under multiple scenarios, and using appropriate modeling methods to complete the construction, and through comparison, verification and optimization with actual vehicle control behavior, the logical relationships and constraints between various body control functions are clarified.

5. The method for detecting logical conflicts in vehicle body control functions as described in claim 1, characterized in that, The process involves comparing the collected real-time data with a pre-built vehicle body control function logic model based on vehicle design principles and control strategies, and using a preset algorithm to detect whether there are logical conflicts in the vehicle body control functions, including: The collected raw data undergoes preprocessing operations such as cleaning, transformation, and normalization to eliminate noise and outliers. The preprocessed data is substituted into the vehicle body control function logic model for inference and calculation to obtain the theoretical operating state of the vehicle body control function. By comparing the theoretical operating state with the actual acquired control signals, if the difference between the two exceeds the preset error range, a logical conflict is determined, and the specific type of conflict is identified.

6. The method for detecting logical conflicts in vehicle body control functions as described in claim 1, characterized in that, The process of locating and diagnosing detected logical conflicts includes: Using conflict phenomena as the apex event, various potential causes of failure are derived by decomposing them layer by layer through fault tree analysis. The signal transmission path within the vehicle control system is tracked throughout the entire process to pinpoint key nodes where signal anomalies occur. An expert system, built by combining historical conflict data and the experience of domain experts, conducts comprehensive conflict diagnosis and generates diagnostic reports.

7. The method for detecting logical conflicts in vehicle body control functions as described in claim 1, characterized in that, The step of feeding back conflict information and diagnostic results, and handling the conflict according to a preset strategy, includes at least one of the following: The conflict information is fed back to the relevant body control unit through the vehicle's internal communication network, and the control unit performs emergency handling or alarm reminder operations. Generate a fault report containing the type of conflict, the location of the conflict, and targeted handling suggestions for maintenance personnel to read and conduct troubleshooting; For simple logical conflicts, automatic repair is performed by switching to backup sensors or adjusting equipment operating parameters.

8. A vehicle body control function logic conflict detection device, characterized in that, The vehicle body control function logic conflict detection device includes: The data acquisition and conflict detection module is used to collect various types of data related to vehicle body control, compare the collected real-time data with the pre-built logical model of vehicle body control function based on vehicle design principles and control strategies, and detect whether there are logical conflicts in the vehicle body control function through a preset algorithm. The conflict location diagnosis and feedback processing module is used to locate and diagnose detected logical conflicts, determine the cause and specific location of the conflict, provide feedback on the conflict information and diagnosis results, and process the conflict according to a preset strategy.

9. A vehicle body control function logic conflict detection device, characterized in that, The vehicle body control function logic conflict detection device includes a processor, a memory, and a vehicle body control function logic conflict detection program stored in the memory and executable by the processor, wherein when the vehicle body control function logic conflict detection program is executed by the processor, it implements the steps of the vehicle body control function logic conflict detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a body control function logic conflict detection program, wherein when the body control function logic conflict detection program is executed by a processor, it implements the steps of the body control function logic conflict detection method as described in any one of claims 1 to 7.

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