姓名：牛童
职称：讲师
学历学位：研究生/工学博士
通信地址：山东省青岛市黄岛区前湾港路579号山东科技大学实训中心1310室
电子邮箱：skd995121@sdust.edu.cn
电话：17853314013
研究方向：燃料电池寿命预测与故障诊断、深度学习、智能算法
【个人简介】
牛童，女，讲师，2025年博士（直博）毕业于重庆大学机械与运载工程学院车辆工程专业。主要从事燃料电池寿命预测与故障诊断、燃料电池机理、深度学习、智能算法等研究。以第一作者在《IEEE Transactions on Industrial Electronics》、《Renewable Energy》、《Journal of Power Sources》、《Fuel》等燃料电池领域知名期刊发表论文6篇。担任 Fuel Cells，Chain等多个国内外期刊审稿人和青年编委。
【代表性论文】
[1] Tong Niu, Caizhi Zhang, Kejun Deng, et al. Long-term life prediction of proton exchange membrane fuel cells based on dynamic mode decomposition optimization model [J]. IEEE Transactions on Industrial Electronics, 2026, doi: 10.1109/TIE.2026.3661031（中科院1区Top，IF=7.2）
[2] Tong Niu, Weifeng Huang, Caizhi Zhang, et al. Study of degradation of fuel cell stack based on the collected high-dimensional data and clustering algorithms calculations [J]. Energy and AI, 2022, 10: 100184（中科院2区，IF=9.6）
[3] Tong Niu, Yu Li, Caizhi Zhang, et al. Prediction of fuel cell degradation trends using long short term memory optimization algorithm based on four-module experimental reactor validation[J], Renewable Energy, 2024, 237: 121745（中科院1区Top，IF=9.1）
[4] Tong Niu, Caizhi Zhang, Yong Ren, et al. A fast online prediction method for the health state and electrochemical performance of Proton Exchange Membrane Fue Cells without prior modeling[J], Journal of Power Sources, 2024, 630: 235847（中科院2区，IF=7.9）
[5] Caizhi Zhang#, Tong Niu#, Zhongbao Wei, et al. Lifespan prediction model for proton exchange membrane fuel cell vehicle based on time series information feature extraction and optimization [J]. Renewable Energy, 2025, 243: 122558（中科院1区Top，IF=9.1）
[6] Caizhi Zhang, Weifeng Huang, Tong Niu, et al. Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems [J]. Automotive Innovation, 2023, 6: 89–115（中科院2区，IF=5）
[7] Weifeng Huang#, Tong Niu#, Caizhi Zhang, et al. Experimental study of the performance degradation of proton exchange membrane fuel cell based on a multi-module stack under selected load profiles by clustering algorithm [J]. Energy, 2023, 270: 126937（中科院1区Top，IF=9.4）
