Online Prediction of Vehicular Fuel Cell Residual Lifetime Based on Adaptive Extended Kalman Filter

Ke Song, Yimin Wang, Xiao Hu and Jing Cao
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Ke Song: School of Automotive Studies, Tongji University, Shanghai 201804, China
Yimin Wang: School of Automotive Studies, Tongji University, Shanghai 201804, China
Xiao Hu: School of Automotive Studies, Tongji University, Shanghai 201804, China
Jing Cao: School of Automotive Studies, Tongji University, Shanghai 201804, China

Energies, 2020, vol. 13, issue 23, 1-21

Abstract: The limited lifetime of proton exchange membrane fuel cell (PEMFC) inhibits the further development of the fuel cell industry. Prediction is one of the most effective means for managing the lifetime of a fuel cell because it can assist in the implementation of mitigation actions before a vehicular fuel cell fails by estimating the residual lifetime. Therefore, this study aimed to develop a PEMFC lifetime prediction method for online applications. This paper presents the online prediction method developed for the residual lifetime of a vehicular fuel cell, which utilises data processing with an adaptive extended Kalman filter and a prediction formula. The formula considers different operating conditions and the external environment, which is in accord with the actual operating conditions of fuel cell vehicles. This method realises the online prediction of the residual lifetime of a vehicular fuel cell by updating weight coefficients for the operating conditions and environmental factors. This prediction method was validated and analysed using a simulation. The influences of key parameters on the stability and prediction accuracy of the algorithm were evaluated. The prediction method proposed in this paper can provide a reference for studies on fuel cell lifetime prediction.

Keywords: proton exchange membrane fuel cell; adaptive extended Kalman filter; residual lifetime; online prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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