A closed-loop testing and verification method for an in-vehicle network node

Abstract

This invention provides a closed-loop testing and verification method for vehicle-mounted network nodes, belonging to the field of vehicle electronic system testing technology. The method includes: executing enhanced test cases and simultaneously monitoring the communication status of the CAN bus during environmental and electrical tests of the vehicle-mounted network node; analyzing fault data when a communication fault is detected to determine the fault mechanism and the sensitive stress conditions that trigger the fault; and formulating and verifying countermeasures: formulating hardware countermeasures based on the fault mechanism and verifying the effectiveness of the hardware countermeasures in tests that reproduce the sensitive stress conditions. This invention solves the problems of difficult fault reproduction, ambiguous fault location, and insufficient countermeasure verification in traditional testing, significantly improving the communication reliability and first-time vehicle installation success rate of vehicle-mounted network nodes.

Description

Technical Field

[0001] This invention relates to the field of vehicle electronic system testing technology, and in particular to a closed-loop testing and verification method for vehicle network nodes. Background Technology

[0002] As the core communication network of automotive electronic systems, the reliability of the vehicle's CAN bus directly affects the safety and functional integrity of the entire vehicle. During the automotive development process, ECU nodes often struggle to reproduce intermittent communication failures that occur after vehicle installation during laboratory testing. These failures are typically sensitive to environmental stress (e.g., occurring under specific temperature and voltage conditions) and have complex mechanisms involving multiple factors such as electrical layer signal integrity issues and protocol layer communication anomalies.

[0003] Existing technologies for testing CAN bus communication faults suffer from problems such as low fault reproduction rate, scattered diagnostic methods, and insufficient verification of countermeasures. Therefore, there is an urgent need for a systematic approach that can accurately reproduce faults under laboratory conditions, accurately diagnose mechanisms, formulate targeted hardware countermeasures, and ensure the effectiveness of countermeasures through closed-loop verification, ultimately solving the communication reliability problem completely before vehicle installation. Summary of the Invention

[0004] In view of the technical defects and drawbacks existing in the prior art, embodiments of the present invention provide a closed-loop testing and verification method for vehicle network nodes to overcome the above problems or at least partially solve the above problems, the specific solution of which is as follows;

[0005] A closed-loop testing and verification method for vehicular network nodes includes the following steps:

[0006] Test execution and monitoring: During the environmental and electrical tests of the vehicle network node, enhanced test cases are executed, and the communication status of the CAN bus is monitored synchronously.

[0007] Comprehensive diagnostic analysis: When a communication failure is detected, the failure data is analyzed to determine the failure mechanism and the sensitive stress conditions that cause the failure;

[0008] Countermeasure formulation and verification: Based on the failure mechanism, hardware countermeasures are formulated, and the effectiveness of the hardware countermeasures is verified in the test of reproducing the sensitive stress conditions;

[0009] If the verification passes, the closed-loop process is completed; if the verification fails, the comprehensive diagnostic analysis and countermeasure formulation and verification are iteratively executed until the verification passes.

[0010] In some embodiments, the enhanced test cases include environmental test enhanced cases and electrical test enhanced cases;

[0011] The environmental test enhancement use case is configured to: during environmental testing, when the temperature change rate is detected to exceed a first preset threshold, trigger special monitoring of CAN bus signal bit timing jitter to capture timing anomalies caused by drastic temperature changes.

[0012] The electrical test enhancement use case is configured to: during electrical testing, construct a vehicle load simulation network including equivalent harness impedance and at least three CAN nodes to simulate real vehicle electrical load conditions, and perform a full-band impedance and interference scan on the CAN bus to identify potential faults caused by impedance mismatch or electromagnetic compatibility.

[0013] In some embodiments, synchronous monitoring of the communication status of the CAN bus is achieved through an integrated dual-channel data acquisition system;

[0014] The dual-channel data acquisition system includes:

[0015] The first monitoring channel, connected to the physical cable of the CAN bus, is used to collect electrical layer signals. The electrical layer signals include signal waveform characteristics, specifically at least one of rise time, fall time, overshoot amplitude, and ringing frequency.

[0016] The second monitoring channel is connected to the CAN bus analyzer and is used to collect protocol layer messages, which include at least one of message error frame type, error frame count and frame loss rate.

[0017] Furthermore, the first monitoring channel and the second monitoring channel collect data based on a unified time reference, so that the collected electrical layer signals and protocol layer messages have synchronized timestamps, in order to establish a causal relationship between electrical signal anomalies and communication protocol errors.

[0018] In some embodiments, analyzing fault data includes the following steps:

[0019] Signal spectrum analysis: The CAN bus differential signal acquired at the moment of communication failure is subjected to fast Fourier transform to convert the signal from the time domain to the frequency domain and obtain its spectrum distribution; based on the energy concentration characteristics in the spectrum distribution, the dominant interference frequency band is identified, and it is classified as narrowband interference or wideband interference according to the bandwidth characteristics of the interference frequency band.

[0020] Signal waveform diagnosis: At the moment the communication failure occurs, the signal waveform of the CAN bus is acquired using a high-bandwidth oscilloscope; one or more waveform feature parameters are extracted from the acquired waveform, including rise time, fall time, overshoot amplitude, and ringing frequency; the extracted parameters are matched with a preset waveform feature library to identify the specific type of waveform distortion.

[0021] Stress condition correlation: The timestamp of the fault occurrence used in the signal spectrum analysis and signal waveform diagnosis is precisely aligned with the time-series data recorded in environmental and electrical tests; based on the time-aligned data, the values ​​of one or more test environment parameters at the moment of fault occurrence are obtained, including temperature, voltage, humidity and vibration; thereby determining the sensitive stress conditions that caused the communication fault.

[0022] Fault Mechanism Determination: Combining the interference types identified by the signal spectrum analysis, the waveform distortion types determined by the signal waveform diagnosis, and the sensitive stress conditions determined by the stress condition correlation, the diagnostic results of these three dimensions are used as input. By querying a preset fault mechanism mapping rule base established based on expert experience or historical data, correlation analysis and logical judgment are performed, and finally, the determination result of the root fault mechanism is output. The fault mechanism includes at least one of impedance mismatch, common-mode interference, and signal integrity degradation caused by temperature drift.

[0023] In some embodiments, hardware countermeasures are formulated based on the fault mechanism, specifically including:

[0024] Based on the determined fault mechanism type, a preset hardware countermeasure mapping table is queried, and a hardware countermeasure scheme for the fault mechanism is matched from the table.

[0025] The hardware countermeasure mapping table defines the correspondence between fault mechanism types and CAN transceiver countermeasures, wherein the countermeasures include at least one of replacement selection schemes and parameter optimization schemes.

[0026] The replacement selection scheme is reflected by specifying key selection parameters for the CAN transceiver, including at least one of slew rate, common mode rejection ratio, and operating temperature range;

[0027] The parameter optimization scheme is reflected by specifying target values ​​for optimizing the configurable parameters of the CAN transceiver. The configurable parameters include at least one of the following: slew rate configuration value, common mode rejection ratio configuration value, and operating temperature configuration value.

[0028] In some embodiments, the correspondence contained in the hardware countermeasure mapping table is specifically as follows:

[0029] If the fault mechanism is waveform distortion caused by impedance mismatch, the matching countermeasure is to select a CAN transceiver with a signal slew rate lower than the first set threshold to slow down the signal edge rate and suppress overshoot and ringing.

[0030] If the fault mechanism is common-mode interference, the matching countermeasure is to select a CAN transceiver with a common-mode rejection ratio higher than the second set threshold to improve the bus's ability to resist common-mode noise.

[0031] If the fault mechanism is temperature drift, the corresponding countermeasure is to select a CAN transceiver with a wider operating temperature range than the standard requirement. The lower limit of the operating temperature range is lower than the third set threshold, and the upper limit is higher than the fourth set threshold, to ensure the stability of parameters under extreme temperatures.

[0032] In some embodiments, verifying the effectiveness of the hardware countermeasures includes the following steps:

[0033] Stress condition reproduction: Based on the determined sensitive stress conditions, in the test environment, the test parameters are controlled by environmental test equipment such as programmable temperature chamber, power supply and load simulator to reproduce the specific environment that caused the original fault.

[0034] Post-countermeasure data acquisition: Under the reproduced sensitive stress conditions, CAN bus communication status data after the implementation of hardware countermeasures is acquired using a data acquisition device; the communication status data includes at least one of electrical layer signal quality parameters and protocol layer message integrity parameters;

[0035] Effectiveness comparison and judgment: The collected communication status data after countermeasures are compared and analyzed with the fault data collected under the same sensitive stress conditions. Based on the preset verification judgment criteria, it is determined whether the hardware countermeasures are effective. The verification judgment criteria are one or more of the following: the communication error rate is reduced to below a set threshold, the signal quality parameters are improved to a qualified range, and the message integrity parameters reach the preset standard. If the judgment criteria are met, the hardware countermeasures are determined to be effective and the verification is passed.

[0036] In some embodiments, the effectiveness of hardware countermeasures is determined based on preset verification criteria, specifically including:

[0037] Quantitative Improvement: For each of the verification criteria, calculate its corresponding quantitative improvement index; the quantitative improvement index includes:

[0038] Based on the percentage reduction in communication error rate;

[0039] Parameter deviation improvement rate based on signal quality parameters;

[0040] The improvement in compliance rate based on message integrity parameters;

[0041] Threshold comparison: Each calculated quantitative improvement indicator is compared with the preset corresponding verification judgment threshold one by one;

[0042] Validity determination: If all the quantitative improvement indicators to be assessed reach or exceed their corresponding verification thresholds, then the hardware countermeasures are ultimately determined to be effective.

[0043] In some embodiments, verifying the effectiveness of the hardware countermeasures further includes:

[0044] Robustness verification under extreme boundary conditions includes the following steps:

[0045] Limit boundary condition setting: Based on the specifications of the device under test or industry standards, determine the limit boundary value of at least one parameter among temperature, voltage, and load;

[0046] Limit boundary test: Under the limit boundary conditions, the test parameters are controlled by environmental testing equipment to reach the limit boundary value and maintain it for a set time;

[0047] Robustness verification: Under the extreme boundary conditions, CAN bus communication status data is collected, and the hardware countermeasures are judged to meet the robustness requirements based on the preset robustness judgment criteria.

[0048] The robustness criteria include at least one of the following: communication error rate is below a set threshold under extreme boundary conditions, signal quality parameters are within the qualified range, or continuous operation for a set duration without failure.

[0049] In some embodiments, verifying the effectiveness of the hardware countermeasure further includes feedback optimization, specifically including:

[0050] If the hardware countermeasures are determined to be invalid or not fully effective based on the verification criteria, a feedback optimization process is initiated, which includes:

[0051] Parameter adjustment: Based on the verification results, adjust the analysis parameters in the fault diagnosis process and / or the configuration parameters of the hardware countermeasures;

[0052] The adjustment of the analysis parameters includes modifying at least one of the following: the frequency band range of the spectrum analysis, the judgment threshold of the waveform characteristic parameters, or the sensitivity condition of the stress correlation.

[0053] The adjustment of the hardware countermeasure configuration parameters includes modifying at least one of the target value of the selection parameters of the CAN transceiver or its optimized parameter configuration value;

[0054] Iterative verification: After completing the parameter adjustment, the verification process from the stress condition reproduction step to the effectiveness comparison and judgment step is repeated until the communication failure is eliminated and the hardware countermeasure is judged to be effective.

[0055] The present invention has the following beneficial effects:

[0056] This invention fundamentally solves the industry problems of difficulty in fault reproduction, ambiguous fault location, and insufficient verification of the effectiveness of countermeasures in traditional testing by constructing a closed-loop methodology of "test monitoring → diagnostic analysis → countermeasure verification". Specifically, this method deeply integrates environmental testing, electrical testing, and real-time communication status monitoring. It can accurately expose intermittent communication faults of vehicle network nodes that only appear after vehicle installation under laboratory conditions. Through correlation analysis, it determines the correspondence between fault mechanisms and sensitive stress conditions. Finally, in the countermeasure verification stage, it ensures the effectiveness of hardware improvements, significantly improving the first-time installation success rate of components and the overall vehicle reliability. Attached Figure Description

[0057] Figure 1 A flowchart illustrating a closed-loop testing and verification method for a vehicle network node provided in an embodiment of the present invention;

[0058] Figure 2 A schematic diagram illustrating the enhancement of test cases provided in an embodiment of the present invention;

[0059] Figure 3 This is a schematic diagram of a fault diagnosis analysis provided in an embodiment of the present invention;

[0060] Figure 4 A schematic diagram illustrating a hardware countermeasure formulation provided in an embodiment of the present invention;

[0061] Figure 5 This is a schematic diagram illustrating a closed-loop countermeasure verification method provided in an embodiment of the present invention.

[0062] Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0063] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0064] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0065] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0066] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0067] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0068] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0069] To address at least one of the technical problems existing in the aforementioned related technologies, the present invention provides a closed-loop testing and verification method for vehicle network nodes. Figure 1 A flowchart illustrating a closed-loop testing and verification method for a vehicle-mounted network node provided in an embodiment of the present invention includes the following steps:

[0070] S1. In the environmental and electrical tests of the vehicle network node, enhanced test cases are executed, and the communication status of the CAN bus is monitored synchronously.

[0071] S2. When a communication failure is detected, the failure data is analyzed to determine the failure mechanism and the sensitive stress conditions that cause the failure.

[0072] S3. Based on the fault mechanism, formulate hardware countermeasures and verify the effectiveness of the hardware countermeasures in the test of reproducing the sensitive stress conditions;

[0073] If the verification passes, the closed-loop process is completed; if the verification fails, steps S2 and S3 are executed iteratively until the verification passes.

[0074] This invention fundamentally solves the industry problems of difficulty in fault reproduction, ambiguous fault location, and insufficient verification of the effectiveness of countermeasures in traditional testing by constructing a closed-loop methodology of "test monitoring → diagnostic analysis → countermeasure verification". Specifically, this method deeply integrates environmental testing, electrical testing, and real-time communication status monitoring. It can accurately expose intermittent communication faults of vehicle network nodes that only appear after vehicle installation under laboratory conditions. Through correlation analysis, it determines the correspondence between fault mechanisms and sensitive stress conditions. Finally, in the countermeasure verification stage, it ensures the effectiveness of hardware improvements, significantly improving the first-time installation success rate of components and the overall vehicle reliability.

[0075] In some embodiments, the enhanced test cases include environmental test enhanced cases and electrical test enhanced cases;

[0076] The environmental test enhancement use case is configured to: during environmental testing, when the temperature change rate is detected to exceed a first preset threshold, trigger special monitoring of CAN bus signal bit timing jitter to capture timing anomalies caused by drastic temperature changes.

[0077] The electrical test enhancement use case is configured to: during electrical testing, construct a vehicle load simulation network including equivalent harness impedance and at least three CAN nodes to simulate real vehicle electrical load conditions, and perform a full-band impedance and interference scan on the CAN bus to identify potential faults caused by impedance mismatch or electromagnetic compatibility.

[0078] In the above embodiments, by defining specific enhanced test cases in environmental and electrical tests, potential communication faults of vehicle network nodes under conditions of rapid temperature changes and complex electrical loads can be exposed in a targeted manner, improving test coverage and fault detection rate, and providing a more comprehensive and realistic test data foundation for subsequent fault diagnosis and hardware countermeasure verification.

[0079] refer to Figure 2 The diagram shown is a schematic representation of the enhanced test cases provided in an embodiment of the present invention.

[0080] The following are specific embodiments of an environmental testing enhancement use case and an electrical testing enhancement use case provided by the present invention.

[0081] (1) Specific implementation examples of environmental test enhancement use cases:

[0082] In the environmental testing of the vehicle network node, temperature cycling test conditions were set: the temperature rose from -40℃ to 85℃ at a rate of 5℃ / min (i.e., the temperature change rate exceeded the preset threshold of 3℃ / min). When the temperature change rate exceeded the threshold, the CAN signal bit jitter monitoring module was activated. A high-precision oscilloscope (e.g., sampling rate 1GS / s) was used to acquire the CAN_H and CAN_L differential signals, and the jitter value was quantified by calculating the standard deviation of the time interval between adjacent bits. If the jitter value exceeded ±5% of the normal range, it was recorded as an anomaly, triggering the subsequent diagnostic analysis process.

[0083] (2) Specific implementation examples of electrical test enhancement cases:

[0084] In electrical testing, a vehicle load network simulation platform is built: a programmable resistor network is used to simulate the equivalent wiring harness impedance (typically 120Ω ± 10%), and at least three CAN nodes are connected (including the node under test, the simulated ECU node, and the terminating resistor). A full-band scan of the CAN bus is performed: a spectrum analyzer is used to perform a full-band scan (e.g., 1MHz-1GHz), scanning in 1MHz increments, and the signal amplitude at each frequency is recorded. If abnormal peaks appear in a specific frequency band (e.g., around 30MHz), they are marked as potential interference sources and used as input for subsequent diagnostic analysis.

[0085] In some embodiments, in step S1, the synchronous monitoring of the communication status of the CAN bus is achieved through an integrated dual-channel data acquisition system;

[0086] The dual-channel data acquisition system includes:

[0087] The first monitoring channel, connected to the physical cable of the CAN bus, is used to collect electrical layer signals. The electrical layer signals include signal waveform characteristics, specifically at least one of rise time, fall time, overshoot amplitude, and ringing frequency.

[0088] The second monitoring channel is connected to the CAN bus analyzer and is used to collect protocol layer messages, which include at least one of message error frame type, error frame count and frame loss rate.

[0089] Furthermore, the first monitoring channel and the second monitoring channel collect data based on a unified time reference, so that the collected electrical layer signals and protocol layer messages have synchronized timestamps, in order to establish a causal relationship between electrical signal anomalies and communication protocol errors.

[0090] The above embodiments employ dual-channel synchronous monitoring technology, which can completely capture the real state of the CAN bus from both the electrical physical layer and the communication protocol layer. This solution solves the problem of difficulty in distinguishing between electrical anomalies and protocol errors in traditional testing. For example, it can associate and distinguish waveform ringing (electrical layer problem) with message error frames (protocol layer problem), providing an inseparable and highly reliable data foundation for accurate fault mechanism localization and avoiding misjudgments caused by insufficient monitoring data from a single dimension.

[0091] In some embodiments, the analysis of fault data in step S2 includes the following steps:

[0092] S21. Signal spectrum analysis: Perform a fast Fourier transform on the CAN bus differential signal acquired at the moment of communication failure to convert the signal from the time domain to the frequency domain and obtain its spectrum distribution; based on the energy concentration characteristics in the spectrum distribution, identify the dominant interference frequency band, and classify it into narrowband interference or wideband interference according to the bandwidth characteristics of the interference frequency band.

[0093] S22. Signal Waveform Diagnosis: At the moment the communication failure occurs, the signal waveform of the CAN bus is acquired using a high-bandwidth oscilloscope; one or more waveform feature parameters are extracted from the acquired waveform, including rise time, fall time, overshoot amplitude, and ringing frequency; the extracted parameters are matched with a preset waveform feature library to identify the specific type of waveform distortion.

[0094] S23. Stress Condition Correlation: The timestamp of the fault occurrence used in steps S21 and S22 is precisely aligned with the time-series data recorded in environmental and electrical tests; based on the time-aligned data, the values ​​of one or more test environment parameters at the moment of the fault occurrence are obtained, including temperature, voltage, humidity and vibration; thereby determining the sensitive stress conditions that caused the communication fault.

[0095] S24. Fault Mechanism Determination: Combining the interference type identified in step S21, the waveform distortion type determined in step S22, and the sensitive stress conditions determined in step S23, the diagnostic results of these three dimensions are used as input. By querying a preset fault mechanism mapping rule base established based on expert experience or historical data, correlation analysis and logical judgment are performed, and finally, the determination result of the root fault mechanism is output. The fault mechanism includes at least one of impedance mismatch, common-mode interference, and signal integrity degradation caused by temperature drift.

[0096] In the above embodiments, by integrating the four steps of spectrum analysis, waveform diagnosis, stress correlation, and multi-dimensional correlation analysis into a systematic analysis process, and employing specific technical means such as fast Fourier transform, waveform feature parameter extraction, timestamp alignment, and fault mechanism mapping rules, multi-dimensional, high-precision, and automated diagnosis of communication faults in vehicle network nodes is achieved. It can accurately identify the fault mechanism type and its corresponding sensitive stress conditions, providing a reliable technical basis for the formulation of subsequent hardware countermeasures, significantly improving the accuracy and efficiency of fault diagnosis, and solving the problems of ambiguous fault location and long diagnosis cycle in traditional testing.

[0097] refer to Figure 3 The diagram shown is a schematic representation of a fault diagnosis analysis provided in an embodiment of the present invention.

[0098] The following is a specific embodiment of the present invention for CAN bus communication fault diagnosis and analysis of an in-vehicle network node. Assume that during an environmental test, when the temperature of an in-vehicle network node rapidly increases from -40℃ to 85℃ (heating rate 5℃ / min), intermittent communication errors are detected on the CAN bus. The specific process is as follows:

[0099] Corresponding to S21, spectrum analysis:

[0100] At the moment of the fault occurrence (timestamp T0), the CAN_H and CAN_L differential signals are acquired through a high-speed data acquisition card at a sampling rate of 100MS / s and an acquisition duration of 10ms.

[0101] The acquired signal was subjected to a Fast Fourier Transform (FFT) with 1024 transformation points and a Hanning window as the window function.

[0102] After obtaining the signal spectrum distribution, the energy value of each frequency point was calculated, and it was found that a significant energy peak appeared near the 30MHz frequency point (more than 15dB higher than the normal state).

[0103] Based on the spectral energy distribution characteristics, this frequency point is identified as a narrowband interference band (bandwidth less than 2MHz).

[0104] Corresponding to S22, waveform diagnosis:

[0105] At the fault occurrence time T0, the CAN bus signal waveform was acquired using an oscilloscope (bandwidth 500MHz, sampling rate 1GS / s) for 20μs.

[0106] Extracting waveform feature parameters from the acquired waveform, specifically including:

[0107] Rise time: The time from 10% level to 90% level, measured as 15ns (normal value is 10ns);

[0108] Fall time: The time from 90% level to 10% level, measured as 18ns (normal value is 12ns).

[0109] Overshoot amplitude: The maximum overshoot amplitude after the dominant level transition, measured as 300mV (normal value should be less than 100mV).

[0110] Ringing frequency: The frequency component of the waveform ringing, measured to be 30MHz;

[0111] The extracted feature parameters are matched with a preset waveform feature library, which contains the waveform feature parameter ranges corresponding to typical faults such as impedance mismatch, common-mode interference, and abnormal terminating resistance.

[0112] The matching results show that the waveform distortion types are overshoot and ringing, and the characteristic parameters are highly consistent with the typical characteristics of impedance mismatch.

[0113] Corresponding to S23, stress correlation:

[0114] Get the timestamp of the time T0 when the fault occurred;

[0115] The timestamps are aligned with the experimental environment parameters, and the time accuracy of the environmental parameter acquisition system is 1ms.

[0116] Based on the time-aligned data, obtain the environmental parameter values ​​at time T0:

[0117] Temperature: 65℃ (during the heating process);

[0118] Voltage: 12.5V (normal range);

[0119] Humidity: 45%RH (normal range);

[0120] Vibration: None (static test);

[0121] The sensitive stress conditions that caused the failure were determined to be: during a rapid temperature change, the temperature was in the range of 60-70℃, and the rate of temperature change was greater than 3℃ / min.

[0122] Corresponding to S24, multi-dimensional correlation analysis:

[0123] Based on the analysis results of steps S21 to S23:

[0124] Interference frequency band identification result: 30MHz narrowband interference;

[0125] Waveform distortion type identification results: overshoot and ringing, characteristic parameters indicate impedance mismatch;

[0126] Results of sensitive stress condition determination: rapid temperature change (>3℃ / min) within the 60-70℃ range.

[0127] Correlation analysis is performed using preset fault mechanism mapping rules, which are established based on expert experience. An example of the rule is as follows:

[0128] Rule 1: If spectrum analysis shows narrowband interference around 30MHz, waveform diagnosis shows overshoot and ringing, and the stress condition is rapid temperature change, then the fault mechanism is impedance mismatch (probability > 80%).

[0129] Rule 2: If spectrum analysis shows broadband interference and waveform diagnosis shows common-mode noise characteristics, then the fault mechanism is common-mode interference;

[0130] Rule 3: If the spectrum analysis shows no obvious abnormalities, but the waveform diagnosis shows that the signal amplitude drifts with temperature, then the fault mechanism is temperature drift.

[0131] Applying rule 1, the fault mechanism is determined to be signal integrity degradation caused by impedance mismatch.

[0132] Based on the diagnostic results, after replacing the CAN transceiver with a matching one (a model with a lower slew rate), the test was repeated under the same stress conditions, and the communication fault disappeared, verifying the accuracy of the diagnostic results.

[0133] In some embodiments, the step S3 of formulating hardware countermeasures based on the fault mechanism specifically includes:

[0134] Based on the fault mechanism type determined in step S24, a preset hardware countermeasure mapping table is queried, and a hardware countermeasure scheme for the fault mechanism is matched from the table.

[0135] The hardware countermeasure mapping table defines the correspondence between fault mechanism types and CAN transceiver countermeasures, wherein the countermeasures include at least one of replacement selection schemes and parameter optimization schemes.

[0136] The replacement selection scheme is reflected by specifying key selection parameters for the CAN transceiver, including at least one of slew rate, common mode rejection ratio, and operating temperature range;

[0137] The parameter optimization scheme is reflected by specifying target values ​​for optimizing the configurable parameters of the CAN transceiver. The configurable parameters include at least one of the following: slew rate configuration value, common mode rejection ratio configuration value, and operating temperature configuration value.

[0138] The above embodiments establish a pre-defined mapping relationship between fault mechanisms and hardware countermeasures, directly transforming diagnostic results into specific and executable hardware selection or parameter optimization schemes. This changes the traditional trial-and-error countermeasure formulation model that relies on engineer experience, and realizes data-driven scientific decision-making. For example, explicitly mapping the "common-mode interference" mechanism to the countermeasure of "selecting a transceiver with a high common-mode rejection ratio" significantly improves the accuracy and efficiency of countermeasure formulation and shortens the problem-solving cycle.

[0139] In some embodiments, the correspondence contained in the hardware countermeasure mapping table is specifically as follows:

[0140] If the fault mechanism is waveform distortion caused by impedance mismatch, the matching countermeasure is to select a CAN transceiver with a signal slew rate lower than the first set threshold to slow down the signal edge rate and suppress overshoot and ringing.

[0141] If the fault mechanism is common-mode interference, the matching countermeasure is to select a CAN transceiver with a common-mode rejection ratio higher than the second set threshold to improve the bus's ability to resist common-mode noise.

[0142] If the fault mechanism is temperature drift, the corresponding countermeasure is to select a CAN transceiver with a wider operating temperature range than the standard requirement. The lower limit of the operating temperature range is lower than the third set threshold, and the upper limit is higher than the fourth set threshold, to ensure the stability of parameters under extreme temperatures.

[0143] refer to Figure 4 The diagram shown is a schematic diagram of a hardware countermeasure formulation provided by an embodiment of the present invention.

[0144] The following is a specific embodiment of hardware countermeasure matching based on fault mechanism provided by the present invention. It is assumed that the fault mechanism of a certain vehicle network node has been determined to be common-mode interference (spectrum analysis shows broadband interference characteristics, waveform diagnosis shows common-mode noise waveform, and stress correlation shows that it occurs under specific electromagnetic interference environment). The specific process is as follows:

[0145] During the test system initialization phase, a hardware countermeasure mapping table is pre-established and stored in the test system's configuration file. This table contains the following core mapping relationships (partial examples):

[0146] Fault mechanism type: Common-mode interference → Countermeasure: Select a CAN transceiver with a common-mode rejection ratio higher than the set threshold;

[0147] Fault mechanism type: Waveform distortion (overshoot / ringing) → Countermeasure: Select a CAN transceiver with a signal slew rate lower than the set threshold;

[0148] Fault mechanism type: Temperature drift → Countermeasure: Select a CAN transceiver with a lower limit of operating temperature below -40℃ and an upper limit of operating temperature above 125℃;

[0149] The specific value of the threshold is pre-configured according to the test standard and the requirements of the node being tested.

[0150] For example, the common mode rejection ratio threshold (i.e., the second set threshold) is set to -20dB according to the requirements of ISO 11898-2 standard (the industry standard value recorded in the original text).

[0151] Signal slew rate threshold (i.e., the first set threshold): set to 20V / μs (typical value recorded in the original text) according to the actual application scenario.

[0152] Operating temperature range thresholds (i.e., the third and fourth set thresholds): Based on the requirements of the vehicle environment, the lower limit is set to -40℃ and the upper limit is set to 125℃ (the automotive-grade temperature range recorded in the original text).

[0153] Based on the fault type "common-mode interference", the corresponding countermeasure scheme is retrieved from the preset hardware countermeasure mapping table;

[0154] The query result is: Select a CAN transceiver with a common-mode rejection ratio higher than -20dB;

[0155] Based on the matching results, the system generates hardware countermeasure suggestions:

[0156] From the pool of candidate CAN transceivers, select models with a common-mode rejection ratio (CMRR) higher than -20dB (e.g., a certain CAN transceiver model has a CMRR of -18dB, which meets the requirement).

[0157] Alternatively, the configuration parameters of existing CAN transceivers can be optimized, and their common-mode rejection ratio configuration value can be adjusted to the target range;

[0158] The system outputs the following countermeasures: "It is recommended to use a CAN transceiver model with a common-mode rejection ratio (CMRR) of ≥-20dB, or to optimize the CMRR configuration of the existing transceiver."

[0159] In some embodiments, verifying the effectiveness of the hardware countermeasures includes the following steps:

[0160] S31. Stress Condition Reproduction: Based on the sensitive stress conditions determined in step S23, in the test environment, the test parameters are precisely controlled through environmental test equipment such as programmable temperature chamber, power supply and load simulator, so as to reproduce the specific environment that caused the original fault.

[0161] S32. Post-countermeasure data acquisition: Under the sensitive stress conditions reproduced in step S31, CAN bus communication status data after implementing the hardware countermeasures is acquired using data acquisition devices such as an oscilloscope and a CAN bus analyzer; the communication status data includes at least one of electrical layer signal quality parameters and protocol layer message integrity parameters.

[0162] S33. Effectiveness Comparison and Judgment: The communication status data after countermeasures collected in step S32 is compared and analyzed with the fault data collected in step S1 under the same sensitive stress conditions. Based on the preset verification judgment criteria, it is determined whether the hardware countermeasures are effective. The verification judgment criteria are one or more of the following: the communication error rate is reduced to below a set threshold, the signal quality parameters are improved to a qualified range, and the message integrity parameters reach the preset standards. If the judgment criteria are met, the hardware countermeasures are determined to be effective and the verification is passed.

[0163] The above embodiments, through a standardized verification process of "stress condition reproduction → data acquisition → comparative verification," can accurately verify the effectiveness of countermeasures in a controlled laboratory environment after implementation. This approach objectively judges whether the countermeasures have truly resolved the initial fault by comparing key performance indicators (such as error rate and signal quality) before and after implementation, ensuring the effectiveness and reliability of the countermeasures and preventing the recurrence of situations where "tests pass but installation fails."

[0164] refer to Figure 5 The diagram shown is a schematic diagram of a closed-loop countermeasure verification provided in an embodiment of the present invention.

[0165] In some embodiments, the step S33, which involves determining the effectiveness of the hardware countermeasure based on a preset verification criterion, specifically includes:

[0166] S331. Quantitative Improvement: For each item in the verification judgment criteria, calculate its corresponding quantitative improvement index; the quantitative improvement index includes:

[0167] Based on the percentage reduction in communication error rate;

[0168] Parameter deviation improvement rate based on signal quality parameters;

[0169] The improvement in compliance rate based on message integrity parameters;

[0170] S332, Threshold Comparison: Compare each quantitative improvement index calculated in step S331 with the preset corresponding verification judgment threshold one by one.

[0171] S333. Validity determination: If all quantitative improvement indicators to be assessed reach or exceed their corresponding verification thresholds, then the hardware countermeasures are ultimately determined to be effective.

[0172] The above embodiments calculate specific indicators such as communication error rate reduction rate and signal quality improvement rate, and compare them with preset thresholds, transforming subjective judgments of "effective" or "ineffective" into data-driven scientific decisions. This eliminates the arbitrariness of human judgment, ensures the accuracy and consistency of countermeasure verification results, and provides a clear decision-making basis for the iterative optimization of the closed-loop process.

[0173] In some embodiments, verifying the effectiveness of the hardware countermeasure further includes:

[0174] Robustness verification under extreme boundary conditions includes the following steps:

[0175] Limit boundary condition setting: Based on the specifications of the device under test or industry standards, determine the limit boundary value of at least one parameter among temperature, voltage, and load;

[0176] For example, based on the datasheet parameters of the CAN transceiver under test, at least one of the following is determined: temperature boundary value from -40°C to 125°C, voltage boundary value from 9V to 16V, and load boundary value from 60Ω to 120Ω.

[0177] Limit boundary test: Under the limit boundary conditions, the test parameters are controlled by environmental testing equipment to reach the limit boundary value and maintain it for a set time;

[0178] For example, in an environmental test chamber, the temperature is controlled at the temperature limit boundary value by a temperature controller, the voltage is controlled at the voltage limit boundary value by a programmable power supply, and the load is controlled at the load limit boundary value by a load simulator, and maintained for a set time (such as 24 hours).

[0179] Robustness verification: Under the extreme boundary conditions, CAN bus communication status data is collected, and the hardware countermeasures are judged to meet the robustness requirements based on the preset robustness judgment criteria.

[0180] For example, under the corresponding extreme boundary conditions, the CAN bus signal waveform is acquired by an oscilloscope, and the message data is acquired by a CAN analyzer for a set duration; the hardware countermeasures are judged to meet the robustness requirements based on the preset robustness judgment criteria.

[0181] The robustness criteria include at least one of the following: communication error rate is below a set threshold under extreme boundary conditions, signal quality parameters are within the qualified range, or continuous operation for a set duration without failure.

[0182] For example, the robustness criteria may include at least one of the following: a communication error rate of less than 1%, signal quality parameters within the specified range, or continuous operation for 24 hours without communication failure.

[0183] In some embodiments, verifying the effectiveness of the hardware countermeasure further includes feedback optimization, specifically including:

[0184] If, in step S33, the hardware countermeasure is determined to be invalid or not fully effective based on the verification criteria, a feedback optimization process is initiated, which includes:

[0185] Parameter adjustment: Based on the verification results, adjust the analysis parameters in the fault diagnosis process and / or the configuration parameters of the hardware countermeasures;

[0186] The adjustment of the analysis parameters includes modifying at least one of the following: the frequency band range of the spectrum analysis, the judgment threshold of the waveform characteristic parameters, or the sensitivity condition of the stress correlation.

[0187] The adjustment of the hardware countermeasure configuration parameters includes modifying at least one of the target value of the selection parameters of the CAN transceiver or its optimized parameter configuration value;

[0188] Iterative verification: After completing the parameter adjustment, repeat the verification process from steps S31 to S33 until the communication fault is eliminated and the hardware countermeasure is deemed effective.

[0189] The above embodiments, by introducing a feedback optimization mechanism, upgrade the linear "test-diagnosis-countermeasure" process into a dynamic, adaptive closed-loop system. When the initial countermeasure verification fails, the system can automatically feed the result back to the diagnosis or countermeasure stage for iterative optimization until the fault is eradicated. This mechanism significantly improves the ability to resolve complex faults, ensures that all problems are completely closed in the laboratory stage, forms a continuous improvement quality control closed loop, and guarantees the maturity and reliability of the final product.

[0190] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 6 As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement a closed-loop testing and verification method for any of the vehicle network nodes described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0191] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0192] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0193] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0194] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements a closed-loop testing and verification method for any of the vehicular network nodes described in the above embodiments. The computer-readable storage medium can be volatile or non-volatile.

[0195] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes any of the above-described methods for closed-loop testing and verification of a vehicle network node.

[0196] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0197] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0198] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0199] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0200] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0201] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0202] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0203] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0204] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0205] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A closed-loop testing and verification method for vehicular network nodes, characterized in that, Includes the following steps: Test execution and monitoring: During the environmental and electrical tests of the vehicle network node, enhanced test cases are executed, and the communication status of the CAN bus is monitored synchronously. Comprehensive diagnostic analysis: When a communication failure is detected, the failure data is analyzed to determine the failure mechanism and the sensitive stress conditions that cause the failure; Countermeasure formulation and verification: Based on the failure mechanism, hardware countermeasures are formulated, and the effectiveness of the hardware countermeasures is verified in the test of reproducing the sensitive stress conditions; If the verification passes, the closed-loop process is complete. If the verification fails, the comprehensive diagnostic analysis and countermeasure formulation and verification will be performed iteratively until the verification passes.

2. The method according to claim 1, characterized in that, The enhanced test cases include enhanced environmental test cases and enhanced electrical test cases; The environmental test enhancement use case is configured to: during environmental testing, when the temperature change rate is detected to exceed a first preset threshold, trigger special monitoring of CAN bus signal bit timing jitter to capture timing anomalies caused by drastic temperature changes. The electrical test enhancement use case is configured to: during electrical testing, construct a vehicle load simulation network including equivalent harness impedance and at least three CAN nodes to simulate real vehicle electrical load conditions, and perform a full-band impedance and interference scan on the CAN bus to identify potential faults caused by impedance mismatch or electromagnetic compatibility.

3. The method according to claim 1 or 2, characterized in that, Synchronous monitoring of the CAN bus communication status is achieved through an integrated dual-channel data acquisition system; The dual-channel data acquisition system includes: The first monitoring channel, connected to the physical cable of the CAN bus, is used to collect electrical layer signals. The electrical layer signals include signal waveform characteristics, specifically at least one of rise time, fall time, overshoot amplitude, and ringing frequency. The second monitoring channel is connected to the CAN bus analyzer and is used to collect protocol layer messages, which include at least one of message error frame type, error frame count and frame loss rate. Furthermore, the first monitoring channel and the second monitoring channel collect data based on a unified time reference, so that the collected electrical layer signals and protocol layer messages have synchronized timestamps, in order to establish a causal relationship between electrical signal anomalies and communication protocol errors.

4. The method according to claim 1, characterized in that, The analysis of fault data includes the following steps: Signal spectrum analysis: The CAN bus differential signal acquired at the moment of communication failure is subjected to fast Fourier transform to convert the signal from the time domain to the frequency domain and obtain its spectrum distribution; based on the energy concentration characteristics in the spectrum distribution, the dominant interference frequency band is identified, and it is classified as narrowband interference or wideband interference according to the bandwidth characteristics of the interference frequency band. Signal waveform diagnosis: At the moment the communication failure occurs, the signal waveform of the CAN bus is acquired using a high-bandwidth oscilloscope; one or more waveform feature parameters are extracted from the acquired waveform, including rise time, fall time, overshoot amplitude, and ringing frequency; the extracted parameters are matched with a preset waveform feature library to identify the specific type of waveform distortion. Stress condition correlation: The timestamp of the fault occurrence used in the signal spectrum analysis and signal waveform diagnosis is precisely aligned with the time-series data recorded in environmental and electrical tests; based on the time-aligned data, the values ​​of one or more test environment parameters at the moment of fault occurrence are obtained, including temperature, voltage, humidity and vibration; thereby determining the sensitive stress conditions that caused the communication fault. Fault Mechanism Determination: Combining the interference types identified by the signal spectrum analysis, the waveform distortion types determined by the signal waveform diagnosis, and the sensitive stress conditions determined by the stress condition correlation, the diagnostic results of these three dimensions are used as input. By querying a preset fault mechanism mapping rule base established based on expert experience or historical data, correlation analysis and logical judgment are performed, and finally, the determination result of the root fault mechanism is output. The fault mechanism includes at least one of impedance mismatch, common-mode interference, and signal integrity degradation caused by temperature drift.

5. The method according to claim 4, characterized in that, Based on the aforementioned failure mechanism, hardware countermeasures are formulated, specifically including: Based on the determined fault mechanism type, a preset hardware countermeasure mapping table is queried, and a hardware countermeasure scheme for the fault mechanism is matched from the table. The hardware countermeasure mapping table defines the correspondence between fault mechanism types and CAN transceiver countermeasures, wherein the countermeasures include at least one of replacement selection schemes and parameter optimization schemes. The replacement selection scheme is reflected by specifying key selection parameters for the CAN transceiver, including at least one of slew rate, common mode rejection ratio, and operating temperature range; The parameter optimization scheme is reflected by specifying target values ​​for optimizing the configurable parameters of the CAN transceiver. The configurable parameters include at least one of the following: slew rate configuration value, common mode rejection ratio configuration value, and operating temperature configuration value.

6. The method according to claim 5, characterized in that, The specific correspondence contained in the hardware countermeasure mapping table is as follows: If the fault mechanism is waveform distortion caused by impedance mismatch, the matching countermeasure is to select a CAN transceiver with a signal slew rate lower than the first set threshold to slow down the signal edge rate and suppress overshoot and ringing. If the fault mechanism is common-mode interference, the matching countermeasure is to select a CAN transceiver with a common-mode rejection ratio higher than the second set threshold to improve the bus's ability to resist common-mode noise. If the fault mechanism is temperature drift, the corresponding countermeasure is to select a CAN transceiver with a wider operating temperature range than the standard requirement. The lower limit of the operating temperature range is lower than the third set threshold, and the upper limit is higher than the fourth set threshold, to ensure the stability of parameters under extreme temperatures.

7. The method according to claim 5, characterized in that, Verifying the effectiveness of the hardware countermeasures includes the following steps: Stress condition reproduction: Based on the determined sensitive stress conditions, in the test environment, the test parameters are controlled by environmental test equipment such as programmable temperature chamber, power supply and load simulator to reproduce the specific environment that caused the original fault. Post-countermeasure data acquisition: Under the reproduced sensitive stress conditions, CAN bus communication status data after the implementation of hardware countermeasures is acquired using a data acquisition device; the communication status data includes at least one of electrical layer signal quality parameters and protocol layer message integrity parameters; Effectiveness comparison and judgment: The collected communication status data after countermeasures are compared and analyzed with the fault data collected under the same sensitive stress conditions. Based on the preset verification judgment criteria, it is determined whether the hardware countermeasures are effective. The verification judgment criteria are one or more of the following: the communication error rate is reduced to below a set threshold, the signal quality parameters are improved to a qualified range, and the message integrity parameters reach the preset standard. If the judgment criteria are met, the hardware countermeasures are determined to be effective and the verification is passed.

8. The method according to claim 7, characterized in that, The effectiveness of hardware countermeasures is determined based on preset verification criteria, specifically including: Quantitative Improvement: For each of the verification criteria, calculate its corresponding quantitative improvement index; the quantitative improvement index includes: Based on the percentage reduction in communication error rate; Parameter deviation improvement rate based on signal quality parameters; The improvement in compliance rate based on message integrity parameters; Threshold comparison: Each calculated quantitative improvement indicator is compared with the preset corresponding verification judgment threshold one by one; Validity determination: If all the quantitative improvement indicators to be assessed reach or exceed their corresponding verification thresholds, then the hardware countermeasures are ultimately determined to be effective.

9. The method according to claim 7, characterized in that, Verifying the effectiveness of the hardware countermeasures also includes: Robustness verification under extreme boundary conditions includes the following steps: Limit boundary condition setting: Based on the specifications of the device under test or industry standards, determine the limit boundary value of at least one parameter among temperature, voltage, and load; Limit boundary test: Under the limit boundary conditions, the test parameters are controlled by environmental testing equipment to reach the limit boundary value and maintain it for a set time; Robustness verification: Under the extreme boundary conditions, CAN bus communication status data is collected, and the hardware countermeasures are judged to meet the robustness requirements based on the preset robustness judgment criteria. The robustness criteria include at least one of the following: communication error rate is below a set threshold under extreme boundary conditions, signal quality parameters are within the qualified range, or continuous operation for a set duration without failure.

10. The method according to claim 7, characterized in that, Verifying the effectiveness of the hardware countermeasures also includes feedback optimization, specifically including: If the hardware countermeasures are determined to be invalid or not fully effective based on the verification criteria, a feedback optimization process is initiated, which includes: Parameter adjustment: Based on the verification results, adjust the analysis parameters in the fault diagnosis process and / or the configuration parameters of the hardware countermeasures; The adjustment of the analysis parameters includes modifying at least one of the following: the frequency band range of the spectrum analysis, the judgment threshold of the waveform characteristic parameters, or the sensitivity condition of the stress correlation. The adjustment of the hardware countermeasure configuration parameters includes modifying at least one of the target value of the selection parameters of the CAN transceiver or its optimized parameter configuration value; Iterative verification: After completing the parameter adjustment, the verification process from the stress condition reproduction step to the effectiveness comparison and judgment step is repeated until the communication failure is eliminated and the hardware countermeasure is judged to be effective.

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