姓名: 汪继伟
职称: 副教授
系别: 自动化系
研究领域: 储能电池建模与优化、状态估计与寿 命预测、电池梯次利用、故障诊断、 储能系统健康评估等
电子邮箱: jiweiwang@xju.edu.cn
汪继伟,男,中共党员,博士,副教授,硕士研究生导师,教育部研究生学位论文评审专家,入选自治区青年人才计划。2022年9月毕业于日本国立弘前大学,获工学博士学位,同年入职新疆大学电气工程学院。博士期间前往重庆大学车辆动力系统实验室从事访学交流与科学研究。主要从事储能电池建模与优化、状态估计与寿命预测、电池梯次利用、故障诊断、储能系统健康评估等。近5年来,参与或主持自治区重大科技专项、重点研发专项、自然科学基金、两区科技发展计划项目等科研项目和横向课题10余项,发表SCI论文10余篇,其中以第一/通讯作者发表SCI论文4篇,EI收录3篇,申请国家发明专利2项。
IEEE会员 中国电源学会会员 日本能源学会会员
中国人工智能学会会员 日本电气化学学会会员
2025/01—2026/12,面向高能耗行业的无功补偿关键技术及应用研究,参与,在研
2024/12—2027/11,纯氢-气基竖炉能效提升技术和耐蚀内衬材料开发,参与,在研
2024/12—2027/11,输变电装备电磁热力基础特性与校核判据研,参与,在研
2024/10—2027/09,面向储能电站的锂离子电池健康管理关键技术研究,主持,在研
2024/01—2026/12,燃煤锅炉变负荷运行智能控制技术研究,参与,在研
2024/01—2026/12,储能电池健康评估关键技术研究,主持,在研
2023/10—2025/09,工业大数据驱动的催裂化装置智能建模与优化技术 研发,参与,在研
2023/01—2025/12,基于数据驱动的锂离子电池健康状态研究,主持,在研
2021/01—2021/12,电池热电模型技术合作项目,参与,结题
2021/01—2023/12,退役电池电网侧储能应用关键技术研究,参与,结题
2020/10—2022/09,高能量密度全固态锂电池关键技术研究,参与,结题
[1]Juncheng Fu, Chunling Wu,Jiwei Wang, Md Majidul Haque, Limin Geng, Jinhao Meng. "Lithium-ion battery SOH prediction based on VMD-PE and improved DBO optimized temporal convolutional network model. "Journal of Energy Storage.87
(2024):111392.
[2]Jiwei Wang, Hao Li, Chunling Wu, Yujun Shi, Linxuan Zhang, and Yi An. "State of Health Estimations for Lithium-Ion Batteries Based on MSCNN."Energies(19961073) 17, no. 17 (2024).
[3]Li, Hao,Jiwei Wang*, Yujun Shi, Tiancheng Fang, Peng Shang, and Abuliti Abudula. "Research on SOH Estimation Method of Lithium-ion Battery based on Fusion of VMD and SVR."In 2024 IEEE 4th New Energy and Energy Storage System Control Summit Forum (NEESSC), pp. 189-194. IEEE, 2024.
[4]Jiwei Wang, Hao Li, Linxuan Zhang, Yi An, Lirong Xie, Yujun Shi, and Penghua Li. "Research on Lithium-Ion Battery State of Health Prediction Based on Autoregressive Integrated Moving Average Mode."In 2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC), pp. 1238-1242. IEEE, 2024.
[5]Jiwei Wang, Zhongwei Deng, Tao Yu, Akihiro Yoshida, Lijun Xu, Guoqing Guan, and Abuliti Abudula."State of Health Estimation Based on Modified Gaussian Process Regression for Lithium-Ion Batteries. "Journal of Energy Storage.51(2022):
104512.
[6]Jiwei Wang, Zhongwei Deng, Kaile Peng, Xinchen Deng, Lijun Xu, Guoqing Guan, and Abuliti Abudula. "Early Prognostics of Lithium-Ion Battery Pack Health."Sustainability14.4 (2022):2313.
[7]Jiwei Wang, Zhongwei Deng,Jinwen Li, Kaile Peng, Lijun Xu, Guoqing Guan, and Abuliti Abudula."State of Health Trajectory Prediction Based on Multi-Output Gaussian Process Regression for Lithium-Ion Battery."Batteries, 8.10(2022):134.
[8]Jiwei Wang, Yunhong Che, Zhongwei Deng, Kaile Peng, Guoqing Guan, and Abuliti Abudula. "Lifetime prognostics of lithium-ion battery pack based on its early cycling data and complete degradation information of battery cells."In 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA), vol. 2, pp. 961-965. IEEE, 2021.