Digital Intelligent Battery Lab

Publications

Journals
Conference
Patents

Journal papers

Browse by Year.

Early Access

2026

[J36] Shaohua Xie, Guangzhong Dong*, Haonan Chen, Yunjiang Lou,   Realistic multi-fault diagnostics of millions-scale Li-ion batteries with rapid unsupervised learning. Cell Reports Physical Science, 2026, 7(3):103154.

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This paper has been selected as one of our featured articles for the March 2026 issue.

2025

[J35] Haonan Chen, Guangzhong Dong*, Shaohua Xie, Yifei Wang, Yunjiang Lou,  A Scalable Recurrent Structure With Fast Transfer Learning for Lithium-Ion Battery State of Charge Estimation at Different Ambient Temperatures. IEEE Transactions on Intelligent Transportation Systems, 2025, 26(10):14792-14806.

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[J34] Fukang Shen, Guangzhong Dong*, Zhipeng Zhu, Li Sun, Yunjiang Lou,  An Online Model-Based Diagnosis Method for Micro-Short Circuits in Series-Connected Lithium-Ion Battery Packs. IEEE Transactions on Industrial Electronics, 2025, 72(12):13141-13150.

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[J33] Haonan Chen, Guangzhong Dong*, Yifei Wang, Jincheng Yu, Liangcai Wu, Yunjiang Lou,  Data-Driven Battery Health Prognosis Using Scalable Deep Recurrent Structure and Partial Fast-Charging Profiles. IEEE Transactions on Vehicular Technology, 2025, 74(11):17034-17046.

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[J32] Nanbing Hua, Haonan Chen, Guangzhong Dong*,  Deep transfer learning-enabled battery health prognosis using impedance spectrum data. Journal of Energy Storage, 2025, 132(Part C):117855.

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[J31] Daren Chen, Li Sun, Fukang Shen, Guangxin Gao, Yunjiang Lou, Guangzhong Dong*,  A fuzzy extended PI observer for state of charge estimation of LiFePO4 batteries across broad temperature ranges. Journal of Energy Storage, 2025, 128:116964.

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[J30] Guangxin Gao, Guangzhong Dong*, Yunjiang Lou, Li Sun, Jingwen Wei,  Physics-Informed Data-Driven Power Capacity Prediction of Lithium-Ion Battery Against Various Temperatures. IEEE Transactions on Intelligent Transportation Systems, 2025, 26(6):8670 – 8681.

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[J29] Shaohua Xie, Guangzhong Dong*, Haonan Chen, Li Sun, Yunjiang Lou,  Data-Driven Battery Health Prognostics Using Time-Frequency Feature Maps and Spatial-Temporal Neural Network. IEEE Transactions on Vehicular Technology, 2025, 74(5):8226 – 8237.

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[J28] Zhipeng Zhu, Guangzhong Dong*, Yunjiang Lou, Li Sun, Jincheng Yu, Liangcai Wu,  MPC-Guided Deep Reinforcement Learning for Optimal Charging of Lithium-Ion Battery With Uncertainty. IEEE Transactions on Transportation Electrification, 2025, 11(1):4408 – 4419.

[J27] Guangzhong Dong, Nanbing Hua, Haonan Chen, Yunjiang Lou,  Deep Transfer Learning Enabled State of Health Estimation of Lithium-Ion Battery Using Voltage Sample Entropy Under Fast Charging Profiles. IEEE Transactions on Transportation Electrification, 2025, 11(1):3703 – 3714.

2024

[J26] Guangzhong Dong, Guangxin Gao, Yunjiang Lou, Jincheng Yu, Chunlin Chen, Jingwen Wei, Hybrid Physics and Data-Driven Electrochemical States Estimation for Lithium-ion Batteries. IEEE Transactions on Energy Conversion, 2024, 39(4):2689 – 2700.

[J25] Guangzhong Dong, Zhipeng Zhu, Yunjiang Lou, Jincheng Yu, Liangcai Wu, Jingwen Wei, Optimal Charging of Lithium-Ion Battery Using Distributionally Robust Model Predictive Control With Wasserstein Metric. IEEE Transactions on Industrial Informatics, 2024, 20(5):7630 – 7640.

[J24] Guangzhong Dong, Fukang Shen, Li Sun, Mingming Zhang, Jingwen Wei, A Bayesian Inferred Health Prognosis and State of Charge Estimation for Power Batteries. IEEE Transactions on Instrumentation and Measurement, 2024, 74:1000312.

[J23] Guangzhong Dong, Yuyao Feng, Yunjiang Lou, Mingming Zhang, Jingwen Wei, Data-Driven Fast Charging Optimization for Lithium-Ion Battery Using Bayesian Optimization With Fast Convergence. IEEE Transactions on Transportation Electrification, 2024, 10(2):4173 – 4183.

2023

[J22] Guangzhong Dong, Yuyao Feng, Yifei Wang, Jingwen Wei,  Probabilistic dischargeable time forecasting of power batteries via statistical characterization of future loading profiles. Journal of Energy Stroage, 2023, 59(6):106488.

[J21] Jingwen Wei, Chunlin Chen, Guangzhong Dong*, Global Sensitivity Analysis for Impedance Spectrum Identification of Lithium-Ion Batteries Using Time-Domain Response. IEEE Transactions on Industrial Electronics, 2023, 70(4):3825 – 3835.

2022

[J20] Guangzhong Dong, Yan Xu, Zhongbao Wei, A Hierarchical Approach for Finite-Time H-∞ State-of-Charge Observer and Probabilistic Lifetime Prediction of Lithium-Ion Batteries. IEEE Transactions on Energy Conversion, 2022, 37(1):718 – 728.

[J19] Weiji Han, Anton Kersten, Changfu Zou, Torsten Wik, Xiaoliang Huang, Guangzhong Dong*, Analysis and Estimation of the Maximum Switch Current During Battery System Reconfiguration. IEEE Transactions on Industrial Electronics, 2022, 69(6):5931 – 5941.

2021

[J18] Guangzhong Dong, Jingwen Wei, A physics-based aging model for lithium-ion battery with coupled chemical/mechanical degradation mechanisms. Electrochimica Acta, 2021, 395:139133.

[J17] Guangzhong Dong, Mingqiang Lin, Model-based thermal anomaly detection for lithium-ion batteries using multiple-model residual generation. Journal of Energy Stroage, 2021, 40:102740.

[J16] Guangzhong Dong, Weiji Han; Yujie Wang, Dynamic Bayesian Network-Based Lithium-Ion Battery Health Prognosis for Electric Vehicles. IEEE Transactions on Industrial Electronics, 2021, 68(11):10949 – 10958.

Before 2021

[J15] Guangzhong Dong, Jingwen Wei, Determination of the load capability for a lithium-ion battery pack using two time-scale filtering. Journal of Power Sources, 2020, 480(11):229056.

[J14] Jingwen Wei, Guangzhong Dong*, Zonghai Chen*, Lyapunov-Based Thermal Fault Diagnosis of Cylindrical Lithium-Ion Batteries. IEEE Transactions on Industrial Electronics, 2020, 67(6):4670 – 4679.

[J13] Guangzhong Dong, Fangfang Yang, Kwok-Leung Tsui, Changfu Zou, Active Balancing of Lithium-Ion Batteries Using Graph Theory and A-Star Search Algorithm. IEEE Transactions on Industrial Informatics, 2020, 17(4):2587 – 2599.

[J12] Guangzhong Dong, Zonghai Chen, Jingwen Wei, Sequential Monte Carlo Filter for State-of-Charge Estimation of Lithium-Ion Batteries Based on Auto Regressive Exogenous Model. IEEE Transactions on Industrial Electronics, 2019, 66(11):8533 – 8544.

[J11] Guangzhong Dong, Fangfang Yang, Zhongbao Wei, Jingwen Wei, Kwok-Leung Tsui, Data-Driven Battery Health Prognosis Using Adaptive Brownian Motion Model. IEEE Transactions on Industrial Informatics, 2019, 16(7):4736 – 4746.

[J10] Chenbin Zhang, Yayun Zhu, Guangzhong Dong*, Jingwen Wei*, Data-driven lithium-ion battery states estimation using neural networks and particle filtering. International Journal of Energy Research, 2019, 43(8):8230–8241.

[J9] Fangfang Yanga, Xiangbao Song, Guangzhong Dong*, Kwok-Leung Tsui, A coulombic ef ciency-based model for prognostics and health estimation of lithium-ion batteries. Energy, 2019, 171:1173-1182.

[J8] Guangzhong Dong, Zonghai Chen, Battery Health Prognosis Using Brownian Motion Modeling and Particle Filtering. IEEE Transactions on Industrial Informatics, 2019, 15(2):869 – 877.

[J7] Guangzhong Dong, Zonghai Chen, Jingwen Wei; Qiang Ling, Battery Health Prognosis Using Brownian Motion Modeling and Particle Filtering. IEEE Transactions on Industrial Electronics, 2018, 65(11):8646 – 8655.

[J6] Guangzhong Dong, Jingwen Wei, Zonghai Chen, Constrained Bayesian dual-filtering for state of charge estimation of lithium-ion batteries. International Journal of Electrical Power & Energy Systems, 2018, 99:516-524.

[J5] Guangzhong Dong, Jingwen Wei, Zonghai Chen, Han Sun, Xiaowei Yu, Remaining dischargeable time prediction for lithium-ion batterie using unscented Kalman filter. Journal of Power Sources, 2017, 364:316-327.

[J4] Guangzhong Dong, Jingwen Wei, Zonghai Chen, Kalman filter for onboard state of charge estimation and peak power capability analysis of lithium-ion batteries. Journal of Power Sources, 2016, 328:615-626.

[J3] Guangzhong Dong, Jingwen Wei, Chenbin Zhang, Zonghai Chen, Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method. Applied Energy, 2016, 162:163-171.

[J2] Guangzhong Dong, Zonghai Chen, Jingwen Wei, Chenbin Zhang, Peng Wang, An online model-based method for state of energy estimation of lithium-ion batteries using dual filters. Journal of Power Sources, 2016, 301:277-286.

[J1] Guangzhong Dong, Xu Zhang, Chenbin Zhang, Zonghai Chen, A method for state of energy estimation of lithium-ion batteries based on neural network model. Energy, 2015, 90(P1):879-888.

Articles that I co-authored.

实验室与电力系统、电机控制、氢能、风能、电池控制等领域合作成果

  • Wei, J., Dong, G., Chen, Z., and Kang, Y., “System state estimation and optimal energy control framework for multicell lithium-ion battery system,” in: Applied Energy 187 (Feb. 2017), pp. 37–49, DOI: 10.1016/j.apenergy.2016.11.057.
  • Wei, J., Dong, G., and Chen, Z., “On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment,” in: Journal of Power Sources 365 (Oct. 2017), pp. 308–319, DOI: 10.1016/j.jpowsour.2017.08.101.
  • Wei, J., Dong, G., and Chen, Z., “Lyapunov-based state of charge diagnosis and health prognosis for lithium-ion batteries,” in: Journal of Power Sources 397 (Sept. 2018), pp. 352–360, DOI: 10.1016/j.jpowsour.2018.07.024.
  • Chen, Z., Sun, H., Dong, G., Wei, J., and Wu, J., “Particle filter-based state-of-charge estimation and remaining-dischargeable-time prediction method for lithium-ion batteries,” in: Journal of Power Sources 414 (Feb. 2019), pp. 158–166, DOI: 10.1016/j.jpowsour.2019.01.012.
  • Zhang, C., Yu, X., Dong, G., Wei, J., and Chen, Z., “A method for remaining discharge time prediction of lithium-ion batteries under dynamic uncertainty,” in: International Journal of Energy Research 43.5 (Apr. 2019), pp. 1760–1774, DOI: 10.1002/er.4391.
  • Wei, Z., Zhao, J., Xiong, R., Dong, G., Pou, J., and Tseng, K. J., “Online Estimation of Power Capacity With Noise Effect Attenuation for Lithium-Ion Battery,” in: IEEE Transactions on Industrial Electronics 66.7 (July 2019), pp. 5724–5735, DOI: 10.1109/TIE.2018.2878122.
  • Chen, Z., Xu, K., Wei, J., and Dong, G., “Voltage fault detection for lithium-ion battery pack using local outlier factor,” in: MEASUREMENT 146 (Nov. 2019), pp. 544–556, DOI: 10.1016/j.measurement.2019.06.052.
  • Han, W., Wik, T., Kersten, A., Dong, G., and Zou, C., “Next-Generation Battery Management Systems: Dynamic Reconfiguration,” in: IEEE INDUSTRIAL ELECTRONICS MAGAZINE 14.4 (Dec. 2020), pp. 20–31, DOI: 10.1109/MIE.2020.3002486.
  • Wei, Z., Dong, G., Zhang, X., Pou, J., Quan, Z., and He, H., “Noise-Immune Model Identification and State-of-Charge Estimation for Lithium-Ion Battery Using Bilinear Parameterization,” in: IEEE Transactions on Industrial Electronics 68.1 (Jan. 2021), pp. 312–323, DOI: 10.1109/TIE.2019.2962429.
  • Wu, J., Fang, L., Meng, J., Lin, M., and Dong, G., “Optimized Multi-Source Fusion Based State of Health Estimation for Lithium-Ion Battery in Fast Charge Applications,” in: IEEE Transactions on Energy Conversion 37.2 (June 2022), pp. 1489–1498, DOI: 10.1109/TEC.2021.3137423.
  • Wu, J., Fang, L., Dong, G., and Lin, M., “State of health estimation of lithium-ion battery with improved radial basis function neural network,” in: Energy 262.B (Jan. 2023), DOI: 10.1016/j.energy.2022.125380.
  • Zhou, Y., Dong, G., Tan, Q., Han, X., Chen, C., and Wei, J., “State of health estimation for lithium-ion batteries using geometric impedance spectrum features and recurrent Gaussian process regression,” in: Energy 262.B (Jan. 2023), DOI: 10.1016/j.energy.2022.125514.
  • Wu, J., Fang, L., Dong, G., and Lin, M., “State of health estimation for lithium-ion batteries in real-world electric vehicles,” in: Science China-Technological Sciences 66.1 (Jan. 2023), pp. 47–56, DOI: 10.1007/s11431-022-2220-y.
  • Wang, Y., Pan, W., Leong, K. W., Xu, X., Dong, G., Ye, X., Zhang, M., and Leung, D. Y. C., “Screen-printed water-in-salt Al ion battery for wearable electronics,” in: Journal of Energy Storage 63 (July 2023), DOI: 10.1016/j.est.2023.106983.
  • Lin, M., Yan, C., Wang, W., Dong, G., Meng, J., and Wu, J., “A data-driven approach for estimating state-of-health of lithium-ion batteries considering internal resistance,” in: Energy 277 (Aug. 2023), DOI: 10.1016/j.energy.2023.127675.
  • Wu, B., Xu, X., Dong, G., Zhang, M., Luo, S., Leung, D. Y. C., and Wang, Y., “Computational modeling studies on microfluidic fuel cell: A prospective review,” in: Renewable & Sustainable Energy Reviews 191 (Mar. 2024), DOI: 10.1016/j.rser.2023.114082.
  • Wu, B., Wu, Q., Xu, X., Dong, G., Zhang, M., Leung, D. Y. C., and Wang, Y., “Microfluidic fuel cell with arc-shaped electrodes to adapt to its mixing zone, a simulation study,” in: Applied Energy 376.A (Dec. 2024), DOI: 10.1016/j.apenergy.2024.124177.
  • Zhang, Z., Dai, H., Xu, X., Dong, G., Zhang, M., Luo, S., Leung, D. Y. C., and Wang, Y., “Investigation of electrode scaling-up strategies for paper-based microfluidic fuel cells,” in: Renewable Energy 235 (Nov. 2024), DOI: 10.1016/j.renene.2024.121316.
  • Wu, Q., Wu, B., Xu, X., Dong, G., Zhang, M., Leung, D. Y. C., and Wang, Y., “Segmented catalyst layer with varied catalyst loading to improve the cost performance of proton exchange membrane electrolysis cell, a numerical investigation,” in: International Journal of Hydrogen Energy 89 (Nov. 2024), pp. 401–412, DOI: 10.1016/j.ijhydene.2024.09.364.
  • Wang, Y., Xu, X., Dong, G., Zhang, M., Jiao, K., and Leung, D. Y. C., “Flexible fuel cells: A prospective review,” in: Energy Reviews 3.4 (Dec. 2024), DOI: 10.1016/j.enrev.2024.100099.
  • Wang, Y., Dong, G., Yu, J., Qin, C., Feng, Y., Deng, Y., and Zhang, M., “In-situ green hydrogen production from offshore wind farms, a prospective review,” in: Renewable Energy 239 (Feb. 2025), DOI: 10.1016/j.renene.2024.122099.
  • Dai, H., Zhang, Z., Zhang, M., Xu, X., Dong, G., Leung, D. Y. C., Leung, M. K. H., and Wang, Y., “Combined cooling and power: Investigating the coupling effect between a microfluidic fuel cell and a heating chip,” in: Chemical Engineering Journal 504 (Jan. 2025), DOI: 10.1016/j.cej.2024.159031.
  • Wu, Q., Zhang, M., Xu, X., Dong, G., Wang, J., Leung, D. Y. C., Leung, M. K. H., and Wang, Y., “Effect of channel rib on oxygen removal in 3D porous transport layer of proton exchange membrane electrolysis cell, a numerical investigation,” in: International Journal of Hydrogen Energy 106 (Mar. 2025), pp. 171–185, DOI: 10.1016/j.ijhydene.2025.01.450.
  • Mi, W., Yu, J., Zhao, F., Dong, G., and Zhao, H., “Complex-Vector Flux-Linkage Envelope Demodulation for High-Speed Resolver-to-Digital Conversion System,” in: IEEE Transactions on Industrial Electronics 72.9 (Sept. 2025), pp. 9758–9768, DOI: 10.1109/TIE.2025.3536538.
  • Xie, L., Wei, J., Li, X., Chen, C., Chen, H., and Dong, G., “Deep Learning-Enabled Fault Diagnosis of Lithium-Ion Batteries Using Real-World Vehicle Data With Gramian Angular Difference Fields,” in: IEEE Transactions on Industrial Informatics 21.7 (July 2025), pp. 5622–5632, DOI: 10.1109/TII.2025.3556068.
  • He, J., Han, X., Yang, X., Chen, C., Wei, J., and Dong, G., “User Preference-Adaptive Battery Fast Charging Strategy Considering Temperature Rising Based on Transfer Reinforcement Learning,” in: IEEE Transactions on Industrial Electronics 72.10 (Oct. 2025), pp. 10327–10337, DOI: 10.1109/TIE.2025.3558034.
  • Guo, J., Dong, G., and Wei, J., “Battery state of health estimation based on automatic feature selection and streamlined temporal focus,” in: Journal of Energy Storage 141.A (Jan 2026), DOI: 10.1016/j.est.2025.119160.
  • Sun, L., Wang, H., and Dong, G., “Analysis and mitigation of circulating currents for grid-forming DERs during parallel black-start in islanded systems,” in: International Journal of Electrical Power & Energy Systems 175 (Feb. 2026), DOI: 10.1016/j.ijepes.2026.111678.
  • Lu, Q., Peng, W., Chen, H., Hu, R., Dong, G., Huang, W. M., Han, Q., Guo, H., Yuan, B., and Lou, Y., “Incorporating dynamic mode decomposition and domain adversarial training for cross-domain state of health estimation of lithium-ion batteries,” in: Journal of Power Sources 675 (May 2026), DOI: 10.1016/j.jpowsour.2026.239836.

Conference

Conference papers.

实验室与电力系统、电机控制、氢能、风能、电池控制、机器学习等领域合作成果

  • Xie, S., Chen, D., and Dong, G., “Robust Lithium-ion Battery SOH Estimation via Denoising Autoencoder-CNN-Transformer with Noisy Multi-Feature Input”, in: Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025, Shenzhen, China, 2025, pp. 942–947, URL: 10.1109/IEEECONF65522.2025.11137038.
  • Feng, Y., Chen, Y., and Dong, G., “Application of A Derivative-Free Data-Driven Optimization Algorithm on Li-Ion Battery Parameter Identification”, English, in: Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025, Shenzhen, China, 2025, pp. 936–941, URL: 10.1109/IEEECONF65522.2025.11136895.
  • Chen, Y., Feng, Y., and Dong, G., “Temperature Estimation of Lithium-Ion Battery Based on Dual Model Fusion”, English, in: Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025, Shenzhen, China, 2025, pp. 1010–1014, URL: http://dx.doi.org/10.1109/IEEECONF65522.2025.11136995.
  • Chen, D., Xie, S., and Dong, G., “Adaptive OCV Hysteresis Modeling for LiFePO4 SOC Estimation via Unscented Kalman Filter”, English, in: Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025, Shenzhen, China, 2025, pp. 1003–1009, URL: 10.1109/IEEECONF65522.2025.11137268.
  • Luo, X., and Dong, G., “Robust Physics-Informed Neural Network for State of Health Estimation of Lithium-Ion Battery”, English, in: Proceedings of 2025 IEEE 26th China Conference on System Simulation Technology and its Applications, CCSSTA 2025, Shenzhen, China, 2025, pp. 998–1002, URL: 10.1109/IEEECONF65522.2025.11137014.
  • Yang, T., Wei, J., Chen, C., and Dong, G., “Charging Scheduling Optimization of Electric Buses Considering Battery Degradation”, English, in: Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics, Hybrid, Vienna, Austria, 2025, pp. 3192–3197, URL: 10.1109/SMC58881.2025.11343409.
  • Deng, X., Lin, Z., and Dong, G., “Data-Driven Wind Farm Layout Optimization Using Bayesian Adaptive Direct Search”, English, in: Proceedings of 2024 IEEE 25th China Conference on System Simulation Technology and its Application, CCSSTA 2024, Tianjin, China, 2024, pp. 762–769, URL: 10.1109/CCSSTA62096.2024.10691758.
  • Lin, Z., Deng, X., and Dong, G., “Wind Farm Power Optimization Using Bayesian Adaptive Direct Search for Active Pitch Control”, English, in: Proceedings of 2024 IEEE 25th China Conference on System Simulation Technology and its Application, CCSSTA 2024, Tianjin, China, 2024, pp. 755–761, URL: 10.1109/CCSSTA62096.2024.10691844.
  • Cheng, Z., Xue, J., Wang, B., Dong, G., Wei, J., and Chen, C., “Path Planning Using Improved Hybrid A* Algorithm for Mobile Robots”, English, in: Proceedings of 2024 IEEE 25th China Conference on System Simulation Technology and its Application, CCSSTA 2024, Tianjin, China, 2024, pp. 352–357, URL: 10.1109/CCSSTA62096.2024.10691828.
  • Sun, L., and Dong, G., “Optimal Power Sharing Control with Stability Enhancement for Islanded Microgrids”, English, in: Proceedings of the 11th International Conference on Innovative Smart Grid Technologies – Asia, ISGT-Asia 2022, Singapore, Singapore, 2022, pp. 560–564, URL: 10.1109/ISGTAsia54193.2022.10003638.

Patents

序号专利名称专利授权国/专利申请国专利号/申请号授权公告日
0
1基于可扩展循环神经网络的锂电池健康诊断方法及系统中国专利ZL202410321108.42024-12-31
2具备快速迁移能力的锂电池荷电状态估计系统及方法中国专利ZL202410321069.82025-01-24
3基于分布鲁棒模型预测控制的锂电池安全快速充电方法中国专利ZL202410324638.42025-01-17
4一种面向稀疏数据的模型与数据融合驱动的储能锂电池微短路及低容量故障诊断与分类方法中国专利ZL202510077144.52025-10-28
5一种用于锂离子电池不同快充工况下的健康状态估计方法中国专利ZL202510022138.X2025-11-04
6储能设备组的故障检测方法、装置、计算机设备和可读存储介质中国专利ZL202411948997.32025-11-07
7退役动力电池拆解仿真软件V1.0软件著作权2026SR04524832026-03-18