A method and related device for online diagnosis of a drive-by-wire chassis based on causal reasoning and twin validation

By employing an online diagnostic method based on causal reasoning and twin verification, the accuracy and stability of fault diagnosis for drive-by-wire chassis systems under complex operating conditions were addressed. This enabled accurate location of the root cause of the fault and safety assessment of the correction strategy, thereby improving the system's operational stability and long-term adaptability.

CN122196807APending Publication Date: 2026-06-12WUHAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
WUHAN UNIV OF TECH
Filing Date
2026-02-06
Publication Date
2026-06-12

AI Technical Summary

⚠Technical Problem

Existing fault diagnosis methods for drive-by-wire chassis systems have low accuracy and stability under complex operating conditions and multi-source anomalies. Furthermore, they lack prior assessment of the effectiveness and safety of correction strategies, leading to decreased system stability. Additionally, onboard diagnostic models are difficult to dynamically adjust to maintain long-term adaptability.

⚗Method used

An online diagnostic method based on causal reasoning and twin verification is adopted. By acquiring multi-source heterogeneous signals to construct an observation vector sequence, calculating instantaneous reconstruction error and window anomaly score, constructing a causal relationship matrix, performing counterfactual reasoning to locate the root cause of the fault, and optimizing the causal weights of the causal relationship matrix through a digital twin verification correction strategy.

🎯Benefits of technology

It improves the accuracy and stability of fault diagnosis, enhances the operational stability of the vehicle control after correction, and continuously optimizes during vehicle operation to maintain long-term adaptability, avoiding the adverse effects of improper correction actions on the system.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a drive-by-wire chassis online diagnosis method based on causal reasoning and twin verification and related equipment, which can be applied to the technical field of intelligent networked vehicles. According to the application, after an observation vector sequence is constructed according to multi-source heterogeneous signals and corresponding instantaneous reconstruction errors are calculated, a window abnormal score is calculated and it is determined that an observation vector sequence exists in an abnormal state variable, a target causal relationship matrix is constructed based on historical normal operation data and a first causal parent set is extracted, and then counterfactual reasoning fault root cause positioning is performed to obtain a target fault root cause, so that the accuracy of fault diagnosis can be effectively improved. Then, the digital twin verification is performed on the correction strategy corresponding to the target fault root cause, and the causal weights in the target causal relationship matrix in the fault diagnosis model are updated and optimized in combination with the actual execution result, so that the running stability of the vehicle after control correction is improved, and the long-term adaptability is maintained by continuous optimization during vehicle operation.
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