Statistical dependency analysis of multiple competing failure causes of fuel cell engines

Tie Chen, Songlin Zheng and Jinzhi Feng

Journal of Risk and Reliability, 2017, vol. 231, issue 2, 83-90

Abstract: Given the current strict regulations on fuel emissions, hydrogen fuel cell vehicles have been considered as ideal non-polluting vehicles. As the kernel subsystem of hydrogen fuel cell vehicles, the fuel cell engine, which is a complex system, may fail because of multiple competing failure causes. In fuel cell engine reliability engineering, discriminating and measuring dependency among multiple failure causes is an urgent problem that should be addressed. This study proposes a statistical dependency analysis model under competing risks based on reliability field data of fuel cell engines. The multivariate lognormal distribution is employed to model joint failure distribution. Then, using simulated annealing algorithm to estimate the parameters of the conditional probability likelihood function. Moreover, p -value hypothesis test procedures are developed to determine the significance of the dependence degree among multiple competing failure causes. In this article, the failure mechanisms of fuel cell engine are comprehensively discussed to prove the feasibility and effectiveness of the proposed method. Results can provide technical support for studies on optimal maintenance strategies.

Keywords: Fuel cell engine; competing failure causes; statistical dependency analysis; multivariate lognormal distribution; simulated annealing algorithm; p-value hypothesis test (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:231:y:2017:i:2:p:83-90

DOI: 10.1177/1748006X16686895

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