A whole vehicle CAN network management pressure test system and method

Abstract

This invention discloses a vehicle CAN network management stress testing system and method in the field of CAN network management technology. The system includes: based on the AUTOSAR communication matrix and network management specifications, decomposing the vehicle CAN network management stress testing requirements; generating test metadata containing protocol mapping IDs through a bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress testing scheme; based on the AUTOSAR-related stress testing scheme, simulating multi-node AUTOSAR state machine switching, capturing cross-node network management frame interaction data, calculating single-node parameter deviations by comparing the captured data with preset parameters, and identifying cross-node timing conflicts using the AUTOSAR protocol timing correlation matrix, recording the conflict frame ID, timing deviation amount, and conflict type, to obtain AUTOSAR-adaptive conflict analysis results. This invention avoids the problem of insufficient test specificity caused by traditional parameter settings based on experience or a single dimension, and can comprehensively cover the core stress scenarios in actual vehicle operation.

Description

Technical Field

[0001] This invention relates to a vehicle CAN network management stress testing system and method, belonging to the field of CAN network management technology. Background Technology

[0002] With the rapid advancement of automotive intelligence and connectivity, the complexity of vehicle electronic control systems is increasing exponentially, and the number of electronic control units is rising significantly. The collaborative interaction between these units relies on the CAN network for data transmission and command issuance. As the core communication carrier of the vehicle's electronic architecture, the CAN network's operational stability, anti-interference capabilities, and protocol compatibility directly affect the reliable implementation of key functions such as vehicle power control, vehicle safety, and entertainment systems. Stress testing is the core means of verifying the performance of the CAN network under extreme operating conditions, playing an irreplaceable role in ensuring vehicle driving safety and user experience.

[0003] Existing vehicle CAN network management stress testing methods have significant shortcomings in terms of demand relevance, comprehensive conflict identification, completeness of full-cycle evaluation, and traceability controllability, and can no longer meet the automotive industry's development needs for high reliability and low mass production risk of CAN networks. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a vehicle CAN network management stress testing system and method, which avoids the problem of insufficient test targeting caused by traditional parameter setting based on experience or a single dimension, and can comprehensively cover the core stress scenarios in the actual operation of the vehicle.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution: In a first aspect, the present invention provides a method for stress testing the management of a vehicle's CAN network, comprising: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and the full-cycle test impact evaluation results are obtained. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0006] Furthermore, the analysis of the impact of changes through the AUTOSAR full-cycle test evaluation model includes calculating the rate of change of performance impact indicators, which include bus load rate, signal packet loss rate, and wake-up response time.

[0007] Furthermore, the analysis of the impact of changes through AUTOSAR full-cycle testing and evaluation models also includes calculating a protocol conformance assessment score, the formula of which is:

[0008] In the formula: PCS is the protocol conformance assessment score; n is the number of key protocol parameters assessed; w i T represents the weight of the i-th protocol parameter; i,actual T is the sequence vector of the actual values ​​of the i-th parameter throughout the entire test period; i,standard Let be the sequence vector of theoretical standard values ​​of the i-th parameter; sim(...) represents the calculation of the cosine similarity between two vectors.

[0009] Furthermore, the analysis of the impact of changes through AUTOSAR full-cycle testing and evaluation model also includes calculating the network attack interference assessment results, the calculation formula of which is:

[0010] In the formula: ADI represents the network attack interference assessment result; t a Δt and Δt represent the attack start time and attack duration, respectively; Fmal(t) represents the attack duration within the time window [t]. aThe NM frame traffic time series vector of the perturbation node ECU_Mal within the range of ,ta+Δt]; V attack F is the attack feature vector; normal This is the time series vector of total NM frame traffic during the baseline phase when the network is functioning normally without attacks; N collision This is the count of error frames detected during the attack period due to bus contention.

[0011] Furthermore, the evaluation of the impact of changes through AUTOSAR full-cycle testing and assessment of the model also includes calculating the state machine switching anomaly index of nodes in the network and the network-level state machine switching anomaly index, calculated using the following formula:

[0012]

[0013] In the formula: SMAI k Let be the state machine transition anomaly index of the k-th tested node; m be the number of state machine transitions of this node within a complete test cycle; D j k,actual D represents the actual time taken for the j-th state transition of the k-th node; j k,expected μ is the expected time taken for the j-th state transition of the k-th node; j k,actual σ j k,actual These represent the mean and standard deviation of the NM frame transmission interval of this node within a short time window before and after this state transition; SMAI network is the network-level state machine switching anomaly index; p is the total number of nodes under test.

[0014] Furthermore, the performance compatibility multi-objective threshold includes a performance threshold and a compatibility threshold, wherein the performance threshold includes the upper limit of bus load rate, the upper limit of signal packet loss rate, and the range of wake-up response time change rate, and the compatibility threshold includes the minimum compatibility rate.

[0015] Furthermore, the AUTOSAR requirement test parameter bidirectional mapping mechanism includes extracting quantifiable test parameters from the vehicle's functional requirements and matching corresponding test parameters for each requirement item. The test parameters include the network management frame sending period, wake-up time threshold, and state machine wake-up trigger delay.

[0016] Secondly, the present invention provides a vehicle CAN network management stress testing system, comprising: The test plan generation module is used to decompose the vehicle CAN network management stress test requirements based on the AUTOSAR communication matrix and network management specifications. It generates test metadata containing protocol mapping IDs through the AUTOSAR requirement test parameter bidirectional mapping mechanism, thereby obtaining the AUTOSAR associated stress test plan. The conflict analysis module is used to simulate multi-node AUTOSAR state machine switching based on the AUTOSAR correlation stress test scheme, capture cross-node network management frame interaction data, calculate single-node parameter deviation by comparing the captured data with preset parameters, identify cross-node timing conflicts using the AUTOSAR protocol timing correlation matrix, record the conflict frame ID, timing deviation amount and conflict type, and obtain AUTOSAR adaptive conflict analysis results. The full-cycle evaluation module is used to identify the changes in test parameters based on the AUTOSAR adaptive conflict analysis results, and to analyze the performance impact and protocol compatibility risks of the changes on the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles using the AUTOSAR full-cycle test evaluation model, so as to obtain the full-cycle test impact evaluation results. The intelligent optimization and verification module is used to perform intelligent parameter rollback optimization on test versions that do not meet the threshold requirements based on the full-cycle test impact assessment results and the preset performance compatibility multi-objective thresholds. The optimized test scheme that passes the verification is stored after passing the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification. The traceability and log generation module is used to adopt the optimized test scheme, compare the test parameters with the AUTOSAR protocol specification and the vehicle functional requirements, generate a version control status containing the AUTOSAR requirement test parameter optimization change traceability chain, and integrate version update records, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0017] Thirdly, the present invention provides a vehicle CAN network management stress testing device, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the following steps: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and the full-cycle test impact evaluation results are obtained. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0018] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor of the following steps: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and the full-cycle test impact evaluation results are obtained. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0019] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: I. This invention constructs a bidirectional mapping mechanism for AUTOSAR requirement test parameters, which deeply binds the AUTOSAR communication matrix, network management specifications and test parameters. It also hashes the protocol mapping ID to ensure data security, allowing the test plan to accurately match the vehicle's functional requirements and protocol specifications. This avoids the problem of insufficient test targeting caused by traditional parameter setting based on experience or a single dimension, and can comprehensively cover the core stress scenarios in the actual operation of the vehicle. Second, this invention uses the CANoe / CANalyzer tool to simulate the switching of multi-node AUTOSAR state machines, which not only captures the parameter deviation of a single node, but also identifies cross-node NM frame timing conflicts through the AUTOSAR protocol timing correlation matrix, and quantifies and records the impact of the conflict and the amount of timing deviation. This fills the gap in the existing technology's ability to identify "cross-node implicit conflicts" and reduces the risk of serious faults such as network lag and wake-up failure from the source. Third, this invention uses the AUTOSAR full-cycle test evaluation model to systematically analyze the impact of test parameter changes on the performance and protocol compatibility of the entire process of "design verification - prototype testing - mass production adaptation". It also classifies the mass production adaptation risk level, breaking the limitation of existing technologies that only focus on the performance of the testing stage. It can predict the mass production adaptation problems caused by parameter adjustments in advance, reducing project rework costs and time-to-market risks. Fourth, this invention achieves intelligent rollback of test parameters by relying on multi-target thresholds for performance compatibility, quickly selecting the optimal protocol adaptation version without repeated manual adjustments; at the same time, it generates a full-link log containing a traceability chain of AUTOSAR requirement test parameter optimization changes, automatically recording key information such as version updates, executors, and reasons for modifications, solving the problems of low optimization efficiency and difficult fault diagnosis in existing systems, making the testing process traceable and problems quickly located. Attached Figure Description

[0020] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating a vehicle CAN network management stress test method provided in Embodiment 1 of the present invention. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0022] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0023] Example 1: like Figure 1 As shown, this embodiment proposes a method for stress testing the management of a vehicle's CAN network, including the following steps: S1: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for the vehicle's CAN network management are broken down. First, the core requirements are extracted from the "CAN Network Management Requirements Specification" provided by the vehicle manufacturer, such as "Powertrain wake-up response time ≤ 200ms", "Bus load rate ≤ 50%", and "Continuous operation for 8 hours without failure". The requirements are then broken down into multi-dimensional quantifiable test parameters according to functional modules (power system, body system, entertainment system). Then, through the AUTOSAR requirement test parameter bidirectional mapping mechanism, the corresponding test parameters are matched for each requirement item. For example, "wake-up response time ≤ 200ms" is mapped to "NM frame sending period 20ms", "wake-up time threshold 200ms" and "state machine wake-up trigger delay 10ms". Subsequently, test metadata containing the "protocol mapping ID" is extracted from the mapping results. The metadata specifically includes test node information (such as the engine ECU with node ID ECU001 and the body control module with node ID ECU002), AUTOSAR state machine configuration (activation time 300ms, sleep delay 500ms), test cycle (10s / time), and corresponding protocol parameters (NM frame data length 8 bytes). Finally, this metadata is archived in CSV format to the local server path / Documents / CANtest / metadata / 20251220 to obtain the AUTOSAR associated stress test solution.

[0024] S2: Based on the aforementioned AUTOSAR-related stress test scheme, three virtual nodes (ECU001-Power, ECU002-Body, ECU003-Entertainment) are created using the CANoe tool. The parameter configurations in the test scheme are imported to simulate the switching of the multi-node AUTOSAR state machine. The “activation-passive-sleep-wake-up” process is executed 10 times according to the preset number of cycles. Each activation lasts for 2 seconds, passive for 1 second, sleep for 3 seconds, and wake-up for 0.5 seconds. Cross-node NM frame interaction data is captured at a sampling rate of 100Hz using CANoe’s Trace function. This includes frame transmission time, node ID, data content, etc. Then, the test metadata in the captured data is compared with the preset parameters, and the deviation of single node parameters (actual value - preset value) is calculated. For example, the preset wake-up response time of ECU001 is 200ms, and the actual time is 250ms, with a deviation of 50ms. Then, cross-node timing conflicts are identified by the AUTOSAR protocol timing correlation matrix (the matrix elements are the allowed interaction timing range between nodes, such as the allowed timing difference between ECU001 and ECU002 ≤ 50ms). For example, if ECU001 sends a wake-up frame at 100ms and ECU002 responds at 300ms, the timing deviation of 200ms exceeds the threshold. Finally, the conflict frame ID (such as NM001), timing deviation amount and conflict type (response timeout) are recorded to obtain the AUTOSAR adaptive conflict analysis results.

[0025] S3: Based on the AUTOSAR adaptive conflict analysis results, identify the changes in test parameters, such as adjusting the wake-up response time of ECU001 from 250ms to 200ms and the response delay of ECU002 from 300ms to 150ms. Analyze the impact of the changes using the AUTOSAR full-cycle test evaluation model. In terms of performance impact, calculate the bus load rate change rate ((32% after change - 30% before change) / 30% ≈ 6.67%), the signal packet loss rate change rate ((0.4% after change - 1.2% before change) / 1.2% ≈ -66.67%), and the wake-up response time change rate ((200ms - 250ms) / 250ms = -20%). Using the AUTOSAR full-cycle test evaluation model, analyze the performance impact and protocol compatibility risks of the changes on the entire vehicle CAN network throughout the "design verification - prototype testing - mass production adaptation" cycle, and obtain the full-cycle test impact evaluation results. It should be noted that after completing the calculations for basic performance impacts (such as changes in bus load rate), this solution will apply the following calculations to the captured data stream through a test platform that integrates evaluation scripts: (a) Calculation of Protocol Conformity Score (PCS)

[0026] In the formula: PCS is the protocol conformance assessment score; n is the number of key protocol parameters assessed; w i T represents the weight of the i-th protocol parameter; i,actual T is the sequence vector of the actual values ​​of the i-th parameter throughout the entire test period; i,standard is the sequence vector of theoretical standard values ​​for the i-th parameter; sim(...) represents the calculation of the cosine similarity between two vectors, with a value range of [-1,1], used to evaluate the consistency between actual behavior and standard behavior in terms of change patterns, where 1 indicates complete consistency.

[0027] Assuming a calculated PCS of 82%, this indicates that under the influence of disturbances, the overall network behavior maintains 82% consistency with the protocol standard. The intelligent decision engine (the executing entity) will utilize this result: if the PCS falls below a preset threshold (e.g., 90%), it will determine that the network protocol consistency has deteriorated under the attack, triggering an optimization process. The optimization focuses on adjusting the NM parameters of relevant ECUs (such as NM frame transmission priority and waiting time) to enhance the protocol maintenance capability under interference.

[0028] (ii) Calculation of Attack-Induced Disruption Index (ADI)

[0029] In the formula: ADI represents the network attack interference assessment result; t a Δt and Δt represent the attack start time and attack duration, respectively; Fmal(t) represents the attack duration within the time window [t]. a The NM frame traffic time series vector of the perturbation node ECU_Mal within the range of ,ta+Δt]; V attack This is the attack feature vector, used to quantify attack patterns. For example, for a flood attack, it can be defined as [1, 0, 0] (high-frequency feature); for a priority tampering attack, it can be defined as [0, 1, 0]; F normal This is the time series vector of total NM frame traffic during the baseline phase when the network is functioning normally without attacks; N collision This is the count of error frames detected during the attack period due to bus contention.

[0030] Assume the calculated ADI is 2.5. ADI is a dimensionless exponent; a higher value indicates stronger interference to the network from the injected attack. The intelligent decision engine uses this result: the ADI value is correlated with the peak bus load rate and signal packet loss rate calculated in step S3. If the ADI is high but network performance degradation is not significant, it indicates that the current network configuration is highly resistant to this type of attack; conversely, it indicates network vulnerability. Based on this, the decision engine can decide whether to introduce or enhance defensive parameter configurations against this type of attack in the optimization scheme (such as configuring higher priority for critical NM frames, or setting filtering rules for abnormally high traffic nodes).

[0031] (III) Calculation of State Machine Anomaly Index (SMAI)

[0032]

[0033] In the formula: SMAI k is the state machine transition anomaly index for the k-th tested node; m is the number of state machine transitions for that node within a complete test cycle (e.g., "sleep -> wake up" is one transition); D j k,actual D represents the actual time taken for the j-th state transition of the k-th node; j k,expected μ is the expected time taken for the j-th state transition of the k-th node; j k,actual σ j k,actual These represent the mean and standard deviation of the NM frame transmission interval of this node within a short time window before and after this state transition; SMAI network This is the network-level state machine transition anomaly index. This parameter is a comprehensive quantitative evaluation value of the state machine transition anomalies in the entire CAN network under test; p is the total number of nodes under test.

[0034] In this embodiment, SMAI was calculated respectively. ECU001 =0.15, SMAI ECU002 =0.85, SMAI network=0.4. This index comprehensively measures the timeliness (deviation from expectations) of a single node's state transition and the stability (volatility) of its behavior at the transition moment. The intelligent decision engine uses this result: nodes with high SMAI values ​​are identified as weak points with unstable or delayed state transitions under disturbances. Intelligent optimization will focus on adjusting the parameters of this node, such as optimizing its internal state machine timers and adjusting the sending phase of its NM messages, to reduce the sensitivity of its transition process to network disturbances, thereby improving the coordination and robustness of the entire network's state transitions.

[0035] S4: Based on the full-cycle test impact assessment results, combined with the AUTOSAR protocol's preset performance compatibility multi-objective thresholds (performance thresholds: bus load rate ≤50%, signal packet loss rate ≤1%, wake-up response time change rate ≤±30%; compatibility thresholds: compatibility rate ≥90%). The parameters of each test version were compared one by one. Before the changes, the current version had a signal packet loss rate of 1.2% (exceeding the threshold) and a compatibility rate of 80% (exceeding the threshold), which was determined to be inconsistent with the target version. Intelligent parameter rollback optimization was performed on it. Referring to the historical best version, the wake-up response time of ECU001 was rolled back to 200ms and the response delay of ECU002 was rolled back to 150ms. At the same time, the NM frame sending period was finely adjusted from 20ms to 15ms. The consistency of parameters and protocols was verified by AUTOSAR toolchain, the cross-node timing compliance was verified by CANoe simulation, and the network stability was verified by real vehicle bench under high and low temperature and electromagnetic interference environments. It was confirmed that the optimized version had a bus load rate of 32%, a signal packet loss rate of 0.4%, and a compatibility rate of 98%, all of which met the threshold requirements. The optimized test plan for this version was stored and verified.

[0036] S5: Using the optimized test scheme, compare the bidirectional matching degree of the test parameters with the AUTOSAR protocol specification and the vehicle functional requirements. Compare parameters such as wake-up response time of 200ms and NM frame transmission period of 15ms with the AUTOSAR 4.4 protocol requirements (wake-up response time ≤ 200ms, transmission period 10-20ms). The matching degree is 100%. Compare with the vehicle's requirements for "rapid wake-up of power system" and "stable communication of body system". The wake-up response time meets the requirements for fast wake-up, the bus load rate of 32% meets the requirements for stable communication, and the matching degree is 100%. A version control status (version V2.0, update time 2025-12-20) is generated, which includes the AUTOSAR requirement test parameter optimization change traceability chain (requirement "wake-up response time ≤ 200ms" → parameter "wake-up response time 200ms" → change "rollback from 250ms to 200ms"). The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0037] Example 2: A vehicle CAN network management stress testing system, which can implement the vehicle CAN network management stress testing method described in Embodiment 1, includes: The test plan generation module is used to decompose the vehicle CAN network management stress test requirements based on the AUTOSAR communication matrix and network management specifications. It generates test metadata containing protocol mapping IDs through the AUTOSAR requirement test parameter bidirectional mapping mechanism, thereby obtaining the AUTOSAR associated stress test plan. The conflict analysis module is used to simulate multi-node AUTOSAR state machine switching based on the AUTOSAR correlation stress test scheme, capture cross-node network management frame interaction data, calculate single-node parameter deviation by comparing the captured data with preset parameters, identify cross-node timing conflicts using the AUTOSAR protocol timing correlation matrix, record the conflict frame ID, timing deviation amount and conflict type, and obtain AUTOSAR adaptive conflict analysis results. The full-cycle evaluation module is used to identify the changes in test parameters based on the AUTOSAR adaptive conflict analysis results, and to analyze the performance impact and protocol compatibility risks of the changes on the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles using the AUTOSAR full-cycle test evaluation model, so as to obtain the full-cycle test impact evaluation results. The intelligent optimization and verification module is used to perform intelligent parameter rollback optimization on test versions that do not meet the threshold requirements based on the full-cycle test impact assessment results and the preset performance compatibility multi-objective thresholds. The optimized test scheme that passes the verification is stored after passing the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification. The traceability and log generation module is used to adopt the optimized test scheme, compare the test parameters with the AUTOSAR protocol specification and the vehicle functional requirements, generate a version control status containing the AUTOSAR requirement test parameter optimization change traceability chain, and integrate version update records, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0038] Example 3: This invention also provides a vehicle CAN network management stress testing device, which can implement the vehicle CAN network management stress testing method described in Embodiment 1, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the following method: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and the full-cycle test impact evaluation results are obtained. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0039] Example 4: This invention also provides a computer-readable storage medium that implements the vehicle CAN network management stress test method described in Embodiment 1. The medium stores a computer program that, when executed by a processor, performs the steps of the following method: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and the full-cycle test impact evaluation results are obtained. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

[0040] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

[0041] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0042] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will 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 program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0043] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0044] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for stress testing vehicle CAN network management, characterized in that, include: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and to obtain the full-cycle test impact evaluation results. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

2. The vehicle CAN network management stress test method according to claim 1, characterized in that, The analysis of the impact of changes through the AUTOSAR full-cycle test evaluation model includes calculating the rate of change of performance impact indicators, which include bus load rate, signal packet loss rate, and wake-up response time.

3. The vehicle CAN network management stress test method according to claim 1, characterized in that, The method of analyzing the impact of changes through AUTOSAR full-cycle testing and evaluation models also includes calculating the protocol conformance evaluation score, the formula of which is: In the formula: PCS is the protocol conformance assessment score; n is the number of key protocol parameters assessed; w i Let be the weight of the i-th protocol parameter; T i,actual T is the sequence vector of the actual values ​​of the i-th parameter throughout the entire test period; i,standard Let be the sequence vector of theoretical standard values ​​of the i-th parameter; sim(...) represents the calculation of the cosine similarity between two vectors.

4. The vehicle CAN network management stress test method according to claim 1, characterized in that, The analysis of the impact of changes through AUTOSAR full-cycle testing and evaluation also includes calculating the network attack interference assessment results, the calculation formula of which is: In the formula: ADI represents the network attack interference assessment result; t a Δt and Δt represent the attack start time and attack duration, respectively. Fmal(t) represents the time window [t]. a The NM frame traffic time series vector of the perturbation node ECU_Mal within the range of ,ta+Δt]; V attack F is the attack feature vector; normal This is the time series vector of total NM frame traffic during the baseline phase when the network is functioning normally without attacks; N collision This is the count of error frames detected during the attack period due to bus contention.

5. The vehicle CAN network management stress test method according to claim 1, characterized in that, The assessment of the impact of changes through AUTOSAR full-cycle testing and evaluation of the model also includes calculating the state machine switching anomaly index of nodes in the network and the network-level state machine switching anomaly index. The calculation formula is as follows: In the formula: SMAI k Let be the state machine transition anomaly index of the k-th tested node; m be the number of state machine transitions of this node within a complete test cycle; D j k,actual D represents the actual time taken for the j-th state transition of the k-th node; j k,expected μ is the expected time taken for the j-th state transition of the k-th node; j k,actual σ j k,actual These represent the mean and standard deviation of the NM frame transmission interval of this node within a short time window before and after this state transition; SMAI network is the network-level state machine switching anomaly index; p is the total number of nodes under test.

6. The vehicle CAN network management stress test method according to claim 1, characterized in that, The performance compatibility multi-objective threshold includes a performance threshold and a compatibility threshold. The performance threshold includes the upper limit of bus load rate, the upper limit of signal packet loss rate, and the range of wake-up response time change rate. The compatibility threshold includes the minimum compatibility rate.

7. The vehicle CAN network management stress test method according to claim 1, characterized in that, The AUTOSAR requirement test parameter bidirectional mapping mechanism includes extracting quantifiable test parameters from the vehicle's functional requirements and matching corresponding test parameters for each requirement item. The test parameters include the network management frame sending period, wake-up time threshold, and state machine wake-up trigger delay.

8. A vehicle CAN network management stress testing system, characterized in that, include: The test plan generation module is used to decompose the vehicle CAN network management stress test requirements based on the AUTOSAR communication matrix and network management specifications. It generates test metadata containing protocol mapping IDs through the AUTOSAR requirement test parameter bidirectional mapping mechanism, thereby obtaining the AUTOSAR associated stress test plan. The conflict analysis module is used to simulate multi-node AUTOSAR state machine switching based on the AUTOSAR correlation stress test scheme, capture cross-node network management frame interaction data, calculate single-node parameter deviation by comparing the captured data with preset parameters, identify cross-node timing conflicts using the AUTOSAR protocol timing correlation matrix, record the conflict frame ID, timing deviation amount and conflict type, and obtain AUTOSAR adaptive conflict analysis results. The full-cycle evaluation module is used to identify the changes in test parameters based on the AUTOSAR adaptive conflict analysis results, and to analyze the performance impact and protocol compatibility risks of the changes on the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles using the AUTOSAR full-cycle test evaluation model, so as to obtain the full-cycle test impact evaluation results. The intelligent optimization and verification module is used to perform intelligent parameter rollback optimization on test versions that do not meet the threshold requirements based on the full-cycle test impact assessment results and the preset performance compatibility multi-objective thresholds. The optimized test scheme that passes the verification is stored after passing the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification. The traceability and log generation module is used to adopt the optimized test scheme, compare the test parameters with the AUTOSAR protocol specification and the vehicle functional requirements, generate a version control status containing the AUTOSAR requirement test parameter optimization change traceability chain, and integrate version update records, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain to obtain the full-link traceability log of the vehicle CAN network management stress test.

9. A vehicle CAN network management stress testing device, characterized in that, Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the following steps: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and to obtain the full-cycle test impact evaluation results. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it performs the following steps: Based on the AUTOSAR communication matrix and network management specifications, the stress test requirements for vehicle CAN network management are decomposed. Test metadata containing protocol mapping IDs is generated through the bidirectional mapping mechanism of AUTOSAR requirement test parameters, thereby obtaining an AUTOSAR-related stress test solution. Based on the aforementioned AUTOSAR correlation-type stress test scheme, the switching of multi-node AUTOSAR state machines is simulated, cross-node network management frame interaction data is captured, the deviation of single-node parameters is calculated by comparing the captured data with preset parameters, and cross-node timing conflicts are identified using the AUTOSAR protocol timing correlation matrix. The conflict frame ID, timing deviation amount and conflict type are recorded to obtain AUTOSAR adaptive conflict analysis results. Based on the AUTOSAR adaptive conflict analysis results, the test parameter changes are identified. The AUTOSAR full-cycle test evaluation model is used to analyze the performance impact and protocol compatibility risks of the vehicle CAN network throughout the design verification, prototype testing and mass production adaptation cycles, and to obtain the full-cycle test impact evaluation results. Based on the full-cycle test impact assessment results, combined with the preset performance compatibility multi-objective threshold, intelligent parameter rollback optimization is performed on test versions that do not meet the threshold requirements, and the optimized test scheme that passes the AUTOSAR toolchain consistency verification, simulation verification and real vehicle environment verification is stored. Using the optimized testing scheme, the test parameters are compared with the AUTOSAR protocol specification and the vehicle functional requirements to generate a version control status that includes the AUTOSAR requirement test parameter optimization change traceability chain. The version update record, protocol-test matching check results, vehicle functional requirement satisfaction degree and optimization change traceability chain are integrated to obtain the full-link traceability log of the vehicle CAN network management stress test.

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