重庆理工大学学报2026，Vol.40Issue(3)：28-34,7.DOI:10.3969/j.issn.1674-8425(z).2026.02.004
基于IVYA-GRU的燃料电池汽车的电池寿命预测
Battery life prediction for fuel cell vehicles based on IVYA-GRU
摘要
Abstract
To improve the visualization and accuracy of the remaining useful life(RUL)prediction of fuel cell vehicles during operation,this paper proposes an Ivy algorithm(IVYA)combined with gated recurrent unit(GRU).The predictive model of GRU neural network is employed to predict the remaining service life of fuel cells.First,the aging experimental data set under static conditions is preprocessed by interval sampling and data smoothing.Then,IVYA is introduced to obtain the optimal hyperparameter set of GRU.Next,GRU is used to predict the fuel cell voltage.Finally,the proposed method is compared with the short-time memory network,the GRU and the Northern Goshawk optimization algorithm.With the proposed one,the root-mean-square error is 0.000 535 55 V,the average absolute error 0.000 420 6 V,the relative error 0.035 9%and the coefficient of determination of the predicted life 0.998 7.It has the highest aging prediction and RUL estimation accuracy under the same conditions.关键词
燃料汽车/氢燃料电池/常春藤优化算法/门控循环单元/数据驱动Key words
fuel cell vehicle/proton exchange membrane fuel cell/IVYA/GRU/data driven分类
信息技术与安全科学引用本文复制引用
朱楠,王靖岳,何宇亭,丁建明..基于IVYA-GRU的燃料电池汽车的电池寿命预测[J].重庆理工大学学报,2026,40(3):28-34,7.基金项目
国家自然科学基金项目(51875096) （51875096）
辽宁省自然科学基金项目(2020-MS-216) （2020-MS-216）
