A reconstructed fuel cell life-prediction model for a fuel cell hybrid city bus. (15th January 2018)

• Record Type: Journal Article
• Authors: Hu, Zunyan; Xu, Liangfei; Li, Jianqiu; Ouyang, Minggao; Song, Ziyou; Huang, Haiyan
• Is Part Of: Energy conversion and management. Volume 156(2018)
• Page Start: 723
• Page End: 732
• Publication Date: 2018-01-15
• Subjects: Fuel cell -- Life prediction -- Voltage reconstruction model -- Performance degradation -- Fuel cell city bus; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2017.11.069
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A reconstructed fuel cell life-prediction model is proposed to simplify the voltage analysis in a fuel cell city bus. A new classified method is used to define two typical operating conditions to analyze the performance degradation. Compared with traditional method, a better performance degradation prediction is obtained in this study. Abstract: Life prediction is a significant and difficult topic for a proton-exchange membrane fuel cell stack, especially a commercial fuel cell stack. This paper proposes a reconstructed fuel cell life-prediction model to estimate the fuel cell lifetime adopted in a city bus. Considering the temperature fluctuation and sensor errors, the voltage model is separated into three parts to simplify the fitting process, and the validation results show that the proposed degradation model is credible and robust. Furthermore, the 14-day training data show that the deviation of the predicted voltage is less than 1%. In this study, the most important innovation is separating the time into different categories. Compared to the traditional method without classification, the proposed model obtains an improved predicted deviation of 50–100%.