Journal of South China University of Technology (Natural Science Edition) ›› 2019, Vol. 47 ›› Issue (3): 53-60.doi: 10.12141/j.issn.1000-565X.180096

• Mechanical Engineering • Previous Articles     Next Articles

Stability Analysis of Automotive Brake Systems Based on Evidence Theory

Lǚ Hui 1 SHANGGUAN Wenbin1 YU Dejie 2   

  1.  1. School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640, Guangdong,China; 2. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University,Changsha 410082,Hunan,China
  • Received:2018-03-07 Revised:2018-11-17 Online:2019-03-25 Published:2019-01-31
  • Contact: 吕辉( 1986-) ,男,博士,副研究员,主要从事汽车 NVH 研究 E-mail:melvhui@scut.edu.cn
  • About author:吕辉( 1986-) ,男,博士,副研究员,主要从事汽车 NVH 研究
  • Supported by:
     Supported by the National Natural Science Foundation of China ( 51605167)

Abstract: An evidence theory-based approach for the stability analysis of disc brakes was proposed to deal with the incomplete or conflicting information which may exist in automotive brake systems. In the proposed approach,parametric uncertainty was taken into account for the stability analysis of a disc brake. The evidence variables were employed to deal with the uncertain parameters whose information was incomplete or even conflicting,and the uncertain parameters with large intervals. Subsequently,the stability analysis model of uncertain disc brake system was established based on evidence theory,and the belief function and plausibility function related to the negative damping ratio of system unstable eigenvalue were used to evaluate system stability. Meanwhile,the detailed procedure of the proposed approach was presented. Finally,the influence of uncertain system parameters on brake stability was explored,based on the probability interval analysis of system stability meeting design requirement. The proposed approach has potential guidance and application in the field of automotive brake noise control.

Key words: evidence theory, system stability, belief function, plausibility function, brake noise

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