scholarly journals Reliability Modeling and Assessment of Electric Vehicle Motor Using Fault Tree and Fuzzy Petri Nets

2016 ◽  
Vol 9 (8) ◽  
pp. 121-136
Author(s):  
Bing Wang ◽  
Yanping Liang ◽  
Chaojun Yang ◽  
Zhibo Sang
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bing Wang ◽  
Guangdong Tian ◽  
Yanping Liang ◽  
Tiangang Qiang

Performing reliability analysis of electric vehicle motor has an important impact on its safety. To do so, this paper proposes its reliability modeling and evaluation issues of electric vehicle motor by using fault tree (FT) and extended stochastic Petri nets (ESPN). Based on the concepts of FT and ESPN, an FT based ESPN model for reliability analysis is obtained. In addition, the reliability calculation method is introduced and this work designs a hybrid intelligent algorithm integrating stochastic simulation and NN, namely, NN based simulation algorithm, to solve it. Finally, taking an electric vehicle motor as an example, its reliability modeling and evaluation issues are analyzed. The results illustrate the proposed models and the effectiveness of proposed algorithms. Moreover, the results reported in this work could be useful for the designers of electric vehicle motor, particularly, in the process of redesigning the electric vehicle motor and scheduling its reliability growth plan.


2018 ◽  
Vol 101 ◽  
pp. 153-165 ◽  
Author(s):  
Seung-yun Kim ◽  
Yilin Yang
Keyword(s):  

2019 ◽  
pp. 127-151
Author(s):  
Paulo Romero Martins Maciel ◽  
Jamilson Ramalho Dantas ◽  
Rubens de Souza Matos Júnior

2014 ◽  
Vol 1008-1009 ◽  
pp. 1176-1179
Author(s):  
Hai Dong ◽  
Heng Bao Xin

In this paper, an approach of fuzzy Petri nets (FPN) is proposed to simulate the fault spreading and diagnosis of hydraulic pump. First, the fuzzy production rules and the definition of FPN were briefly introduced. Then, its knowledge reasoning process and the matrix operations based on an algorithm were conducted, which makes full use of its parallel reasoning ability and makes it simpler and easier to implement. Finally, a case of hydraulic pump fault diagnosis with FPN was presented in detail, for illustrating the interest of the proposed modeling and analysis algorithm.


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