02 储能工程
1. Xiong X, Zhang Y, Feng W. Robust battery fault detection for electric mining trucks using deep learning with enhanced interpretabilit[J]. Journal of Power Sources, 2025, 655: 237965.
2. Sun W, Wu C, Xie C, et al. Fine-tuning enables state of health estimation for lithium-ion batteries via a time series foundation model[J]. Energy, 2025, 318: 134177.
3. 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.
4. 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.
5. 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.
6. T. R. Zhao, Y. H. Zhang, M. H. Wang, et al. A Critical Review on the Battery System Reliability of Drone Systems[J]. Drones, 2025, 9(8): 539.
7. Shao L, Pan Z, Xu X, et al. Fault prediagnosis of power electronic devices in urban new energy system[J]. Energy Reports, 2021, 7: 134-140.
8. Zhou J, Zhang Y, Guo Y, et al. Parameters identification of battery model using a novel differential evolution algorithm variant[J]. Frontiers in Energy Research, 2022, 10: 794732.
9. T. R. Zhao, Y. H. Zhang, M. H. Wang, et al. A Hybrid LSTM-Transformer Model for Accurate Remaining Useful Life Prediction of Lithium-Ion Batteries[J]. Frontiers in Electronics, 2025, 6: 1654344.
10. Zhou B, Jiang Y, Zhang Y, et al. Review of Modelling and Optimal Control Strategy for Virtual Energy Storage[J]. IET Generation, Transmission & Distribution, 2025, 19(1): e70031.
11. S. X. Cao, T. R. Zhao, G. Wang, M. H. Wang, W. Feng and Y. H. Zhang, “Reliability assessment model of energy storage battery based on multidimensional generalized generating function”, in the 4th IEEE International Conference on Industrial Electronics for Sustainable Energy Systems, Sep. 2025.
12. Y. H. Zhang, T. R. Zhao, X. T. Xiong, H. H. Xiang, M. H. Wang and W. Feng, “Unsupervised Thermal Runaway Detection in Lithium-Ion Batteries Using Autoencoder and GAN Discriminator”, in the 4th IEEE International Conference on Industrial Electronics for Sustainable Energy Systems, Sep. 2025.
13. H. H. Xiang, T. R. Zhao, X. T. Xiong, M. H. Wang, W. Feng and Y. H. Zhang, “Battery Capacity Degradation Prediction Based on Optimal Feature Selection under Small Sample Conditions”, in the 4th IEEE International Conference on Industrial Electronics for Sustainable Energy Systems, Sep. 2025.
14. Y. H. Zhang, X. T. Xiong, W. Feng, C. H. Huang, T. R. Zhao and H. H. Xiang, “Decoupling independent aging features based on deep convolutional temporal networks and multi-physics coupling characteristics of batteries”, in the 4th IEEE International Conference on Industrial Electronics for Sustainable Energy Systems, Sep. 2025.