1404 results about "CAN bus" patented technology

The invention discloses a vehicle idling start and stop control system and method. The control system judges whether a vehicle has idling start and stop conditions by monitoring the water temperatureof an engine, the capacity of a storage battery, a safety belt and other information, judges whether the vehicle has conditions of stopping the engine by monitoring the rotating speed of the engine, the speed of the vehicle, the brake air pressure and other conditions, and judges whether the vehicle has conditions of starting the engine by monitoring the gear of a gearbox, the speed of the vehicle, a hand brake and other information. When the relevant conditions are met, start and stop work signals are sent to the engine though a CAN bus. In order to guarantee the reliability of frequent startand stop of the engine, the system strengthens flywheel gear rings of a starter and the engine. In order to ensure that the battery does not lose power, a storage battery capacity sensor is added tothe system on the basis of increasing the capacity of the storage battery, and the idling start and stop are allowed when the state of charge (SOC) of the storage battery satisfies a safe starting threshold. The idling start and stop control system has advantages of low cost and high reliability, and is especially suitable for commercial vehicles.

The invention discloses a ship mobile energy storage system CAN communication protocol automatic test system and method, and the system comprises a protocol modeling and test configuration module, a simulation node behavior simulation module, a CAN bus interaction and power closed loop module, and a test analysis and result evaluation module. A CAN communication protocol specification of the ship mobile energy storage system and parameters of tested equipment can be obtained, a protocol analysis model and a test configuration file are constructed for format verification and logic consistency verification, meanwhile, a corresponding test case sequence is automatically generated, and the message sending time is controlled to generate a time sequence simulation message flow; and sending the time sequence simulation message flow to the tested equipment, simulating energy interaction behavior acquisition to generate a power feedback data set, testing to obtain a signal consistency deviation and a power execution error to construct a protocol conformity evaluation matrix, and generating a visual test report. According to the invention, the high coverage rate and automatic closed-loop test of the CAN communication protocol can be realized.

The invention provides a water surface target grabbing system and a control method thereof, and relates to the technical field of marine operation equipment. The system comprises an unmanned ship and a cooperative mechanical arm, the unmanned ship and the cooperative mechanical arm share a processor; the unmanned ship supplies power to the cooperative mechanical arm; the unmanned ship is positioned through an inertial navigation system on the unmanned ship and a scene camera and a depth camera on the cooperative mechanical arm; a scene camera, a depth camera and an integrated sensor on the cooperative mechanical arm transmit data to a processor on the unmanned ship through a local area network, the processor calculates and analyzes the data transmitted by the scene camera and the depth camera, and an action instruction is sent to the cooperative mechanical arm through a CAN bus. According to the water surface target grabbing system, automatic grabbing is achieved, and the grabbing precision, stability and adaptability of the system in the dynamic marine environment are improved.

The invention discloses a multi-dimensional intelligent analysis and fault traceability system for ACU final test data, and relates to the technical field of data analysis. The multi-source heterogeneous data acquisition module is used for acquiring operation parameters, function test data and assembly data through a CAN bus, test equipment and a production system, and is provided with a high-precision timestamp; the data cleaning and preprocessing module is used for standardizing data, filtering and denoising, synchronizing time and complementing missing values; the multi-dimensional feature extraction module is used for extracting features from a time domain, a frequency domain, a time sequence and a space; the intelligent fault diagnosis module is used for classifying faults by using a random forest and a D-S evidence theory and evaluating severity; the fault traceability reasoning module is used for constructing a fault propagation graph and positioning root causes through a Bayesian network; and the visual display and early warning module is used for generating a three-dimensional fault tree and a thermodynamic diagram and triggering graded early warning. According to the invention, the fault detection rate and traceability efficiency are improved, the false alarm rate is reduced, early warning is realized, the ACU test process is optimized, and the product quality and safety are guaranteed.

The invention discloses an Internet of Vehicles intrusion detection method based on hierarchical feature enhancement and a dynamic sparse attention mechanism, and the method comprises the steps: firstly obtaining an original CAN bus message data stream, and carrying out the multi-modal data preprocessing and hierarchical feature construction; secondly, for hierarchical features, performing message-level depth feature compression and space-time statistical feature enhancement by adopting a dual-channel feature compression mechanism to form an enhanced mixed feature vector, and then constructing a neural network model of a dynamic sparse attention mechanism based on content awareness to perform feature extraction; and inputting a sparse attention calculation result into a hierarchical classifier, and predicting and outputting a detection result. And training the network model, and deploying the trained network model in a vehicle-mounted embedded device to realize real-time message monitoring and intrusion detection. According to the method, the calculation complexity and parameter quantity of the model are greatly reduced, the real-time performance in a vehicle-mounted environment is remarkably improved, and the detection capability on complex hidden attacks is effectively improved.

The invention discloses an Internet of Vehicles CAN bus intrusion detection method based on noise perception active learning, and belongs to the technical field of Internet of Vehicles safety and machine learning. The invention aims to solve the technical problems of false label noise interference, high manual labeling cost, high attack missing report rate caused by class imbalance and the like. The core of the method is to execute a noise sensing mixed query strategy in an iterative loop: firstly, generating a pseudo tag through clustering and correcting by using an integrated noise detector; secondly, calculating uncertainty scores and noise probabilities of the samples, fusing the uncertainty scores and the noise probabilities to obtain a comprehensive score, and preferentially selecting the samples with high uncertainty and low noise probabilities; and then adaptively selecting a sampling strategy according to the model performance and applying category balance constraint. The query batch is used to iteratively update the model while dynamically adjusting the classification threshold to reduce the missing report rate. According to the method, the influence of pseudo label noise can be effectively suppressed, and the attack detection precision and generalization capability are remarkably improved with extremely low labeling cost.

The invention provides a CAN bus message period adjusting method and system based on dynamic load balancing, and the system measures and calculates a network load rate and an error state through a network load real-time detection module, carries out the priority grade division and parameter configuration for different messages, carries out the load partition definition according to the load rate, and carries out the adjustment of the CAN bus message period. And dynamically adjusting a message sending period according to a measurement result, adding a feedback mechanism to realize closed-loop control, and finally realizing load balancing of the system.

The invention provides an electronic mechanical braking system, a vehicle controller and an electric vehicle, and relates to the technical field of electric vehicles. The electronic mechanical braking system comprises a central controller and four wheel end braking devices, and the central controller is used for controlling the four wheel end braking devices to output clamping force to four wheels of the electric vehicle. Wherein the central controller is in communication with the whole vehicle CAN through two public CAN buses and is in communication with each of the four wheel end braking devices through two private CAN buses. In this way, redundant backup of the communication link is achieved, and the communication reliability of the electronic mechanical braking system is improved.

The invention relates to the field of vehicle-mounted bus testing, and discloses a vehicle-mounted CAN bus terminal resistor configuration method and system for node testing, and the method comprises the steps: obtaining a node identifier and a terminal resistor identifier corresponding to each test node in a vehicle-mounted CAN bus test, the terminal resistor identifier being used for identifying the terminal resistor access state of the test node; obtaining a first node position of a first test node corresponding to the first node identifier, configuring a terminal resistor for the first test node when the first node position is an end node of the vehicle-mounted CAN bus, and canceling the configured terminal resistor for the test node of a non-end node; and updating the terminal resistor identifier of each test node according to the terminal resistor access state corresponding to each test node. According to the invention, the terminal resistor can be automatically configured in the CAN bus test.

The present invention relates to a CAN bus anomaly detection method and system based on a dual attention mechanism, comprising the following steps: S1, collecting on-board data from an OBD interface of a vehicle in real time, wherein the collected on-board data comprises operation parameters of an engine, a vehicle speed, the state of a braking system, and the readings of other important sensors; and S2, performing inference analysis on the on-board data at a vehicle end by using an anomaly detection model, calculating a threshold by means of normal operation data so as to identify a potential anomaly or attack mode, once an anomaly is detected, immediately generating identification information, giving a direct alarm to a driver, and slicing, encrypting and storing abnormal data. The present invention relates to the technical field of CAN bus anomaly detection. In the present invention, an anomaly is detected by using the strong relevance of normal data characterization under different perspectives and the difference between the normal data characterization and abnormal data characterization, and by means of the characterization learning of a large amount of normal data, the objective of anomaly detection is achieved, the dependence on abnormal data is reduced, and the accuracy of CAN bus anomaly detection is improved.

The invention provides a data transmission method and device, equipment and a storage medium. The data transmission method is applied to the controller, at least two buffer areas are arranged in the controller, and the data transmission method comprises the steps that in response to starting of a first timer, CAN data sent by external equipment through a CAN controller local area network bus is stored in the buffer area in an idle state in the at least two buffer areas; in the process of storing the CAN data through the buffer area in the idle state, forwarding the CAN data stored in the buffer area in the occupied state in the at least two buffer areas through a serial peripheral interface (SPI) bus; wherein the data transmission rate of the CAN bus is smaller than that of the SPI bus.

The invention belongs to the technical field of central control screen performance testing, and particularly relates to a new energy automobile central control screen performance testing device which comprises a dynamic extreme environment reproduction cabin, a bionic man-machine interaction behavior simulator, a multi-modal parameter synchronous acquisition array, an intelligent decision-making level analysis and evaluation engine and a holographic visualization decision-making support terminal. Physical environment support is provided through the dynamic extreme environment reproduction cabin, environment parameters of the dynamic extreme environment reproduction cabin are synchronized to the multi-modal parameter synchronous acquisition array in real time through the CAN bus, and operation data generated by the bionic man-machine interaction behavior simulator and performance indexes acquired by the multi-modal parameter synchronous acquisition array are preprocessed by the edge computing node and then are transmitted to the multi-modal parameter synchronous acquisition array. The holographic visual decision support terminal is transmitted to the intelligent decision level analysis and evaluation engine through the gigabit Ethernet, and an evaluation report generated by the intelligent decision level analysis and evaluation engine drives the holographic visual decision support terminal to display a result, so that the construction of a closed-loop test system is realized, the test efficiency and the performance evaluation accuracy are remarkably improved, and the automation level and the intelligent level are high.

The invention discloses a gear calibration method for a 3D Hall type combination switch, and the method comprises the steps: starting an upper computer, notifying a six-axis force control robot and a CAN bus tester to prepare, enabling the robot to insert a test sleeve into a switch driving lever, and calibrating the test sleeve to a switch center; the six-axis force control robot pokes a poking rod to test a first gear, collects a force-angle-time array and X / Y / Z magnetic field data of a 3D Hall sensor, calculates alph and beta angles, constructs a correlation array and sends the correlation array to an upper computer; the upper computer generates a multi-dimensional curve graph, analyzes the maximum operating force F1 and the angle S1, finds out a force control point F3 and an angle S3 which are equivalent to the F1 after the S1, and determines the trigger time T3 and calibration data alpha < ph3 >, beta < 3 >, X3, Y3 and Z3; repeating the steps to obtain calibration data of each gear, and after the upper computer is verified to be qualified, writing a product by the CAN bus tester to complete calibration; and 6, the axial force control robot tests all gears, and the CAN bus tester detects the triggering condition and verifies the calibration effectiveness. Problems of early triggering, delayed triggering and the like of the switch can be avoided, and the gear function is accurately triggered.

The invention discloses a new energy unmanned ship battery power control method and system, and the method comprises the steps: an unmanned ship total system sends a start-stop instruction to a BMS, and carries out the automatic awakening and starting of a battery pack; after the BMS is started, the voltage of a battery module, the current of a main loop and the temperature of key components are detected, and if normal, a pre-charging circuit is started to pre-charge a high-voltage loop capacitor; after pre-charging is completed, the BMS disconnects the auxiliary contactor and closes the main contactor, and the battery module supplies power to the electric equipment; during operation, the BMS acquires operation data in real time and uploads the operation data to the unmanned ship total system for monitoring through an external CAN bus; when the multiple battery packs are connected in parallel, cooperative charging and discharging control is carried out through an external CAN bus; the unmanned ship main system sends a shutdown instruction, and the BMS cuts off the main contactor; when abnormity is monitored, the BMS triggers the main fuse to fuse and cuts off self power supply. According to the method, the problem of safe starting is solved, the battery state monitoring precision is improved, a multi-dimensional safety protection system is constructed, and multi-battery-pack cooperative control is optimized.

The invention relates to the technical field of data analysis, and provides a CAN bus waveform message analysis method, device and equipment and a medium, and the method comprises the steps: issuing an operation instruction carrying a preset operation parameter to an oscilloscope; in response to waveform data fed back by the oscilloscope, storing the waveform data as a message file in a preset format; analyzing and converting the message file according to the data head structural body identified by the oscilloscope to obtain a message array; performing time domain segmentation, normalization processing and de-noising processing on the data in the message array by using a Numpy library to obtain a message signal; and performing error frame screening on the message signal by adopting a strategy of supplementing one after five, and performing layer-by-layer analysis on the screened message signal based on a CAN protocol structure to obtain message analysis content. According to the invention, through the software design of the whole process, a universal scheme is adopted from data acquisition, storage and analysis to signal processing and message generation, so that the analysis universality of the CAN bus waveform message is effectively improved.

The invention discloses a predictive vehicle control system and method for multi-modal consciousness recognition and electronic equipment, and relates to the field of remote monitoring, and the system comprises a multi-modal sensing module, an intention prediction module, a cross-domain pre-control module and a false trigger suppression module. The multi-mode sensing module is used for collecting three-mode data of sight, gestures and voice and dynamically distributing weights based on environmental parameters; the intention prediction module is used for performing time-space synchronization verification on the three-mode data and calculating comprehensive confidence in a grading manner; the cross-domain pre-control module outputs pre-control instructions to a cabin domain, a vehicle body domain and a power domain based on the effective intention; the false triggering suppression module is used for dynamically adjusting a confidence coefficient threshold value based on a driving scene and has a failure backspacing learning function; wherein each module performs data interaction based on a vehicle-mounted Ethernet / CAN bus.

The present application provides a cockpit domain controller. The controller comprises an SoC and an MCU; the MCU is provided with two SPI communication channels, two CAN communication channels, a PWM channel, an I2C channel, multiple temperature ADC acquisition channels, multiple voltage monitoring and acquisition channels, and multiple GPIO control channels; the MCU is connected to the SoC by means of the two SPI communication channels and one GPIO control channel; two CAN buses are each provided with a PDCM, a PDCF, an IBC, an EPS, and a VDC; the PWM channel is provided with a fan controller; one ADC channel is connected to a voltage monitoring channel, and another ADC channel is connected to a temperature measurement channel; the I2C channel is provided with a memory, a backup loudspeaker, and a real-time clock chip. The cockpit domain controller of the present application can provide real-time and secure data interaction between the SoC and other controllers.

The embodiment of the invention discloses a test script generation method, system and device, a medium and a product, and relates to the technical field of tests.The method comprises the steps that target structured DBC data is obtained; processing the target structured DBC data by utilizing a target test script generation model to obtain at least one CAPL test script fragment; the target test script generation model is obtained by training according to historical structured DBC data and corresponding historical CAPL test script fragments; the CAPL test script fragment comprises at least one of variable declaration, function definition and event processing; and according to the at least one CAPL test script fragment, determining a target CAPL test script so as to quickly realize verification of the CAN bus communication condition.

An example operation includes one or more of receiving a request from a first ECU disposed on a virtual bus, wherein the request identifies data to be obtained from a second ECU, generating a subscription between the first ECU and the second ECU for the identified data via a framework of a virtual bus, receiving a data frame which is published by the second ECU, and forwarding the data frame published by the second ECU to the first ECU on the virtual bus based on the generated subscription.

An automotive electronic intrusion determination method, apparatus and device based on multi-source fusion data, and a storage medium, the method comprising: performing filtering processing and fusion processing on obtained CAN bus data, vehicle-mounted entertainment system data, Internet of Vehicles data and vehicle state data to generate multi-dimensional feature vector data; marking a corresponding early warning level for the multi-dimensional feature vector data to generate a multi-source fusion data set; training a preset neural network based on the multi-source fusion data set to generate an automobile electronic intrusion detection model; and based on the automobile electronic intrusion detection model, according to the obtained target CAN bus data, target vehicle-mounted entertainment system data, target Internet of Vehicles data and / or target vehicle state data, obtaining an early warning level output by the automobile electronic intrusion detection model so as to determine whether the current vehicle is invaded or not. The technical problems that the false alarm rate is high and complex attacks are difficult to recognize due to the fact that an automobile electronic intrusion detection system depends on a single data source are solved.

The invention discloses a control lever parameter field configuration method and system based on a CAN bus, and belongs to the technical field of control lever parameter field configuration, and the control lever parameter field configuration method comprises the following steps: parameter receiving and analysis, parameter updating and temporary effectiveness, operation feedback, parameter storage, power-down protection and power-on loading. According to the field configuration method and system for the joystick CAN bus parameters, a user can safely and conveniently change communication parameters by himself without returning to a factory, it is ensured that the changed parameters are not lost after power failure, the user can firstly test whether new parameters are valid or not by adopting a two-step mechanism of temporarily taking effect and confirming storage, and then the user can conveniently and rapidly configure the joystick CAN bus parameters. The risk that the system cannot communicate due to misoperation is avoided, and meanwhile operation feedback is provided to enhance man-machine interaction and reliability.

The invention discloses a vehicle-mounted CAN bus anti-interference communication system and method based on photocoupling, and the system comprises an anti-interference communication system frame, the anti-interference communication system frame comprises a CAN bus receiving and transmitting module, a photocoupling isolation module, and a signal processing and separating module, the CAN bus receiving and transmitting module is used for receiving and transmitting CAN bus signals, and the photocoupling isolation module is used for receiving and transmitting the CAN bus signals. The photoelectric coupling isolation module is used for realizing transparent conversion of data between an optical signal and an electric signal and realizing electrical isolation of a physical layer while maintaining the integrity of a CAN protocol, and the signal processing and separation module is used for constructing a cooperative processing mechanism of time sequence calibration, differential judgment, logic reconstruction and signal synthesis. According to the invention, based on a physical layer signal isolation mechanism of optoelectronic isolation, a bidirectional independent transmission path of a CAN bus TXD / RXD channel data stream is established, and TXD mapping data and CAN bus effective data in an RXD channel are accurately separated, so that the system reliability in an industrial-grade communication scene can be obviously improved.

The invention discloses a Beidou user machine high-precision time service and positioning method based on a low-orbit high-stability reference, and relates to the field of vehicle-mounted electronic communication. The method comprises the following steps: firstly, receiving a low-orbit satellite time service signal through an SBOX, generating a high-stability time service reference signal through anti-interference enhancement and delay compensation, and transmitting the high-stability time service reference signal to a Beidou user machine; the Beidou user machine calibrates drifting and fluctuation of an original time service signal of the Beidou user machine according to a low-orbit high-stability time service reference, Beidou high-precision and low-orbit high-stability time service output is achieved through double-source fusion, and finally high-precision positioning calculation is completed and packaged into CAN data; and finally, the information is transmitted to a vehicle-mounted information unit through a vehicle-mounted CAN bus, so that navigation and position reporting are realized. According to the invention, the high stability of the low earth orbit satellite and the high precision of the Beidou are complemented and cooperated, the time service precision and continuity are considered through Kalman filtering fusion and extended Kalman positioning solution, the problems of insufficient stability and poor equipment collaboration of a traditional Beidou user machine are solved, and the high stability and precision requirements of military and commercial use are met.

The invention provides a vehicle-mounted CAN bus intrusion detection system and method based on comparison self-supervised learning. The system comprises a data preprocessing module which is used for receiving a CAN bus data stream in real time, performing feature extraction on each CAN message in the CAN bus data stream to generate a multi-dimensional feature vector, and stacking the feature vectors of W continuous messages by adopting a sliding window method to construct a two-dimensional time sequence sample; the intrusion detection model is used for reasoning the two-dimensional time sequence sample and outputting a classification label; the intrusion detection model is trained through a multi-task joint training method, and the training method fuses an unsupervised reconstruction task, a supervised classification task and a self-supervised contrast learning task; and the decision module is used for judging whether a CAN bus intrusion behavior exists or not according to the classification label output by the intrusion detection model. And the purposes of high efficiency, light weight of the model and capability of accurately identifying various attacks are achieved.

The invention relates to the technical field of voice interaction, in particular to a dialogue type AI low-delay response control method and system based on semantic analysis. The method comprises the following steps: firstly, generating a driving intensity correlation factor of a current time window according to the change of CAN bus data; further monitoring the output of the NLU, analyzing the acoustic intonation raising characteristics, and obtaining an interaction suppression coefficient in combination with the driving intensity correlation factor; further acquiring a time pressure coefficient based on the mute duration after the user stops sounding; further comparing the interaction suppression coefficient and the time pressure coefficient of the current time window to obtain a response judgment value; further analyzing the change trend of the interaction inhibition coefficient, and updating an environment improvement flag bit; and finally, according to the driving intensity correlation factor, the environment improvement flag bit and the response decision value of the current time window, carrying out multi-level response decision control, and carrying out selective reset of an interaction state, thereby solving the problems of wrong truncation and response delay of voice interaction under dynamic driving.

The invention discloses a CAN bus fault diagnosis method and device, a medium and equipment in the technical field of CAN bus communication in the engineering machinery industry. The method comprises the following steps: acquiring operation data of a CAN bus of target engineering machinery; extracting multi-dimensional features including electrical layer features and protocol layer features based on the operation data of the CAN bus of the target engineering machinery; and inputting the multi-dimensional features into a pre-trained neural network model to enable the neural network model to generate a fault type probability value and a reconstruction error according to the multi-dimensional features, and determining the fault type and the specific position of the fault according to the fault type probability value and the reconstruction error. According to the method, various fault modes can be accurately identified, the accurate position and reason of the fault can be given, spectrum analysis is carried out in combination with a correlation analysis technology, the accurate position and reason of the fault can be finally given, and the operation reliability and stability of the CAN bus are improved.

The invention discloses a heavy-fork electrical system fault diagnosis and intelligent repair method, and particularly relates to the technical field of electrical system intelligent operation and maintaining.The method comprises the steps that multi-source data of electrical parameters, mechanical parameters and environmental parameters are collected through a sensor, and fault spatio-temporal feature extraction is conducted through a spatio-temporal attention feature extraction network; then obtaining a fault intelligent repair strategy based on the similarity between the real-time fault spatio-temporal feature vector and the historical fault spatio-temporal feature vector, issuing a corresponding intelligent repair instruction through a CAN bus, monitoring an execution result, evaluating execution result data after repair operation, and feeding back an evaluation abnormal result to a management terminal for human-computer interaction; according to the method, feature extraction is carried out by means of the network comprising the space attention sub-network and the cavity convolution time sequence feature extractor, the feature information of the system operation state can be comprehensively and accurately captured, and rich feature basis is provided for subsequent fault diagnosis and intelligent repair.

The invention discloses a test method, device and equipment, a medium and a product. The method comprises the following steps: acquiring original CAN bus data acquired by a real vehicle road side; the original CAN bus data are screened based on a to-be-measured algorithm, a positive scene slice set and a negative scene slice set of at least one driving scene corresponding to the to-be-measured algorithm are obtained, scene slices in the positive scene slice set are correctly recognized based on the to-be-measured algorithm, and scene slices in the negative scene slice set are correctly recognized based on the to-be-measured algorithm. The scene slices in the negative scene slice set are scene slices with errors identified based on a to-be-measured algorithm; sending input data and an output result of a to-be-measured algorithm corresponding to the negative scene slice set to a target terminal, and receiving an updated to-be-measured algorithm fed back by the target terminal; verifying the updated to-be-measured algorithm based on the positive scene slice set and the negative scene slice set of the at least one driving scene; and if the verification is passed, replacing the to-be-measured algorithm deployed on the real vehicle with the updated to-be-measured algorithm.

The invention discloses a multi-mode voice interaction system and method for an intelligent cabin. Firstly, various vehicle working condition parameters in a CAN bus are read in real time, a wavelet domain Wiener filtering and judgment statistic enhancement strategy is dynamically adjusted, and self-adaptive voice purification based on vehicle state prior is achieved. Secondly, a bidirectional long-short-term memory network is adopted as a semantic understanding core, semantic feature vectors are extracted from enhanced signals through segmented maximum pooling operation, and the problem of semantic confusion caused by manifold collapse in a traditional method is effectively solved. And the feature vector and a safety state signal are synchronously input into an improved LLM-CoT engine and a dynamic arbiter, so that context accurate understanding and safety-up priority response are realized. According to the method, vehicle working condition perception and biLSTM depth time sequence modeling are deeply adapted to a vehicle-mounted complex acoustic scene, the error rate of semantic understanding is remarkably reduced in actual measurement under multi-person dialect dialogue, and the accuracy, robustness and safety of intelligent cabin interaction are systematically improved.

The invention discloses a BMS protocol adaptation method and system based on a CSV file and a storage medium. The method comprises the steps of standardizing CSV configuration file design, storing BMS protocol data in a fixed format and integrating a verification error correction mechanism; dynamic configuration management and initialization are conducted, a FATFS file system is used for managing CSV configuration files in an SD card, multiple transmission modes are supported, and dynamic loading and hot plugging are achieved; efficient data processing and analysis are carried out, and a complete process is designed to ensure that protocol data and CAN bus data are accurately matched; and performing security encryption and access control, performing encryption processing on the configuration file, and introducing an adaptive protocol version management and rollback mechanism. The system and the storage medium correspond to the system and respectively comprise related function modules, a storage layer, a management layer and the like. According to the scheme, standardized storage and efficient processing of the BMS protocol data are achieved, unified management is facilitated, development and maintenance cost is reduced, and effective management and use of the system on the configuration files in different environments are guaranteed.