科研成果
学术成果
[1] Tian, Y., Zhao, K., Liu, W., Sun, X., Wei, W., & Mei, S. (2026). Coordinated fuzzy control of hybrid energy storage systems for enhanced secondary frequency regulation in power grids. Journal of Energy Storage, 141, 119270. (IF: 9.8, JCR Q1, 中科院2区)
[2] Tian, Y., Jiang, L., Sun, X., Wei, W., Zheng, T., & Mei, S. (2025). Sizing of hybrid energy storage systems with integrated frequency stability constraints. Journal of Energy Storage, 131, 116882. (IF: 9.8, JCR Q1)
[3] Xiong, X., Zhang, Y., & Feng, W. (2025). Robust battery fault detection for electric mining trucks using deep learning with enhanced interpretability. Journal of Power Sources, 655, 237965. (IF: 7.9, JCR Q1, 中科院1区Top期刊)
[4] Sun, W., Wu, C., Xie, C., Wang, X., Guo, Y., Tang, Y., ... & Yao, W. (2025). Fine-tuning enables state of health estimation for lithium-ion batteries via a time series foundation model. Energy, 318, 134177. (IF: 9.4, JCR Q1, 中科院1区Top期刊)
[5] Guo Y, Yang Z, Liu K, et al. A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system[J]. Energy, 2021, 219: 119529. (IF: 9.4, JCR Q1, 中科院1区Top期刊, 被引111次)
[6] Zhou D, Liang J, Li F, et al. SOH prediction of lithium-ion batteries using a hybrid model approach integrating single particle model and neural networks[J]. Journal of Energy Storage, 2024, 104: 114579. (IF: 9.8, JCR Q1)
[7] Zhou D, Chen F, Liang J, et al. Battery defect detection using ultrasonic guided waves and a convolutional neural network model[J]. Journal of Energy Storage, 2025, 119: 116352. (IF: 9.8, JCR Q1)
[8] Zhang, Y., Song, W., Lin, S., & Feng, Z. (2014). A novel model of the initial state of charge estimation for LiFePO4 batteries. Journal of Power Sources, 248, 1028-1033. (IF: 7.9, JCR Q1, 中科院1区Top期刊, 被引163次)
[9] Zhao, T., Zhang, Y., Wang, M., Feng, W., Cao, S., & Wang, G. (2025). A critical review on the battery system reliability of drone systems. Drones, 9(8), 539. (IF: 4.4, JCR Q1)
其他代表性成果