Reliability Analysis of Vehicle Braking System Based on Hyperellipsoidal Dynamic Bayesian Network
Source abstract
Abstract
Brake systems are subjected to various factors such as wear and fatigue over a long period of time. They bring a great challenge to the reliability analysis of the braking system. In this paper, the hyperellipsoid model is used and the hyperellipsoid dynamic Bayesian network model is constructed. The model synthesizes the strengths of the dynamic Bayesian network with the precise constraint capability of the superellipsoid model, offering a novel methodology for the reliability analysis of the braking system. In order to verify the validity of the super ellipsoidal dynamic Bayesian network model, this paper applies it to the reliability analysis of the braking system and compares it with the traditional interval Bayesian network. The results show that the hyperellipsoidal dynamic Bayesian network model enhances the range accuracy of the probability intervals by 54.06%. This solves the conservatism problem of interval Bayesian networks. This suggests that the method improves the accuracy of brake system reliability analysis.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Decision-Making Techniques · Evaluation Methods in Various Fields · Simulation and Modeling Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Urban Railway Transportation, Shanghai University of Engineering Science, No. 333, Long-Teng Road, Shanghai 201620, China
Funding
National Natural Science Foundation of China
References (17)
Show source-provided references
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