Reliability Modeling and Evaluation of Electric Vehicle Motor by Using Fault Tree and Extended Stochastic Petri Nets

Abstract

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.

The Burgers Equation for a New Continuum Model with Consideration of Driver’s Forecast Effect

“…Many factors may lead to this result such as the option of equilibrium function, the difference scheme, or the parameters. The control and optimization problems of the parameters in our model can also be studied [25][26][27][28][29][30]. We will continue to study these problems in future.…”

Research and Application of FTA and Petri Nets in Fault Diagnosis in the Pantograph-Type Current Collector on CRH EMU Trains

“…There have also been some studies on the application of FTA and Petri nets in transportation systems. For example, Wang et al proposed reliability modelling and evaluation issues of electric vehicle motors by using FT FTA-based extended stochastic Petri nets [16]; Nguyen et al combined a Petri nets (PN) method with extensions of FTA to adapt to dynamic systems and applied the method to a satellite-based railway system [17]; and Song et al applied T-S Fuzzy theory and FTA to diagnose pantograph faults in a multisource heterogeneous knowledge environment [18].…”

“…Then 3 2 can be solved according to 3 . (16) According to 3 2 , there will be two tokens in the top place 28 and the top event will inevitably happen when tokens indicate the fault transfer. Thus the fault event in the top place will happen if there is at least one token in the top place.…”

Reliability of safety‐critical systems: A state‐of‐the‐art review

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“…Wang et al 61 • In conversion to SPN from FT, it is possible to miss out a lot of important information. There should be the use of some qualitative analysis approach to overcome this issue.…”