Efficiency and longevity trade-off analysis and real-time dynamic health state estimation of solid oxide fuel cell system

Hongchuan Qin, Bingtao Zhang, Renjie Zhou, Yating Sun, Haichuan Tian, Zichen Wang, Shijun Wu, Xi Li and Jianhua Jiang

Applied Energy, 2024, vol. 372, issue C, No S030626192401105X

Abstract: Solid oxide fuel cell (SOFC) is a promising energy conversion technology due to its advantages of high efficiency, low emissions, and fuel adaptability. Addressing the balance between efficiency and longevity is crucial for their application on a large scale. Accurate estimation and prediction of the health state of SOFC systems is essential for the study of optimization between system efficiency and degradation. In this work, the influence law of degradation, the relationship between efficiency and longevity, and their joint optimization, alongside the state of health (SOH) estimation of the SOFC system have been deeply investigated, based on a rigorously validated model of a degraded SOFC system. First, the influential variables that predominantly influence system degradation are identified and analyzed via principal component analysis, including stack average temperature, stack temperature gradient, and fuel utilization. Then, the exploration of the trade-off relationship between system efficiency and longevity under all operating conditions is conducted, and the influence laws of influential variables on system degradation are revealed. In light of the lack of accuracy during load changes and the high time cost for existing SOH estimation methodologies, a novel improved SOH estimation strategy, considering both stack voltage and current-related states, is proposed for real-time estimation of system SOH under varying fuel compositions and dynamic power scenarios. The performance of the proposed method is demonstrated by comparing with existing methodologies. This comprehensive study lays the groundwork for the effective and sustainable health management of SOFC systems, ensuring their efficiency and longevity are maintained at an optimal balance.

Keywords: Solid oxide fuel cell; Stack degradation; Trade-off optimization; Dynamic estimation of state of health; Gaussian process regression; Long and short-term memory neural network (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123722

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