中国电机工程学报2025，Vol.45Issue(7)：2690-2698,中插20,10.DOI:10.13334/j.0258-8013.pcsee.231748
基于ARIMA-BiGRU双数据驱动的燃料电池性能退化预测方法
A Fuel Cell Performance Degradation Prediction Method Based on ARIMA-BiGRU Dual Data-driven Approach
摘要
Abstract
The proton exchange membrane fuel cell(PEMFC),as a core component of new energy technologies,requires accurate performance degradation estimation for practical applications.While conventional data-driven approaches predominantly utilize nonlinear algorithms to forecast PEMFC system performance degradation and refine predictive accuracy through algorithmic architecture optimization,they frequently overlook critical challenges such as the multi-time-scale aging behaviors of individual components and the complex voltage recovery dynamics inherent in fuel cell operation.This study proposes a dual data-driven approach for fuel cell voltage prediction by extracting performance degradation signatures from voltage data.The methodology first decomposes and reconstructs raw voltage data into multiple aging time-scale sequences using a time-frequency domain decomposition algorithm(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise,CEEMDAN).Subsequently,distinct data-driven methods are implemented to separately predict the global degradation trend and local recovery features within the decomposed sequences.Experimental validation on dynamic PEMFC datasets demonstrates that the proposed method achieves 37.2%-43.0%prediction accuracy improvement compared with standalone approaches.关键词
质子交换膜燃料电池/性能退化预测/融合预测/双向机制Key words
proton exchange membrane fuel cell(PEMFC)/performance degradation prediction/fusion prediction/bidirectional mechanism分类
信息技术与安全科学引用本文复制引用
吴航宇,王玮,朱文超,谢长君,杨扬..基于ARIMA-BiGRU双数据驱动的燃料电池性能退化预测方法[J].中国电机工程学报,2025,45(7):2690-2698,中插20,10.基金项目
国家重点研发计划项目(2020YFB1506802) （2020YFB1506802）
广东省重点领域研发计划项目(2020B0909040004) （2020B0909040004）
国家资助博士后研究人员计划项目(GZC20232011).Project Supported by National Key R&D Program of China(2020YFB1506802) （GZC20232011）
Key R&D Project of Guangdong Province(2020B0909040004) （2020B0909040004）
Nationally Funded Postdoctoral Researcher Program(GZC20232011). （GZC20232011）
