| A fast estimation algorithm for lithium-ion battery state of health X Tang, C Zou, K Yao, G Chen, B Liu, Z He, F Gao Journal of Power Sources 396, 453-458, 2018 | 293 | 2018 |
| Critical review of life cycle assessment of lithium-ion batteries for electric vehicles: A lifespan perspective X Lai, Q Chen, X Tang, Y Zhou, F Gao, Y Guo, R Bhagat, Y Zheng Etransportation 12, 100169, 2022 | 182 | 2022 |
| A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging X Tang, Y Wang, C Zou, K Yao, Y Xia, F Gao Energy conversion and management 180, 162-170, 2019 | 166 | 2019 |
| Model migration neural network for predicting battery aging trajectories X Tang, K Liu, X Wang, F Gao, J Macro, WD Widanage IEEE Transactions on Transportation Electrification 6 (2), 363-374, 2020 | 157 | 2020 |
| A method for state-of-charge estimation of LiFePO4 batteries based on a dual-circuit state observer X Tang, Y Wang, Z Chen Journal of Power Sources 296, 23-29, 2015 | 148 | 2015 |
| Joint estimation of battery state-of-charge and state-of-health based on a simplified pseudo-two-dimensional model B Liu, X Tang, F Gao Electrochimica Acta 344, 136098, 2020 | 121 | 2020 |
| Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method X Tang, C Zou, K Yao, J Lu, Y Xia, F Gao Applied Energy 254, 113591, 2019 | 108 | 2019 |
| Recovering large-scale battery aging dataset with machine learning X Tang, K Liu, K Li, WD Widanage, E Kendrick, F Gao Patterns 2 (8), 2021 | 86 | 2021 |
| Run-to-run control for active balancing of lithium iron phosphate battery packs X Tang, C Zou, T Wik, K Yao, Y Xia, Y Wang, D Yang, F Gao IEEE Transactions on Power Electronics 35 (2), 1499-1512, 2019 | 77 | 2019 |
| Load-responsive model switching estimation for state of charge of lithium-ion batteries X Tang, F Gao, C Zou, KE Yao, W Hu, T Wik Applied energy 238, 423-434, 2019 | 75 | 2019 |
| Model migration based battery power capability evaluation considering uncertainties of temperature and aging X Tang, Y Wang, K Yao, Z He, F Gao Journal of Power Sources 440, 227141, 2019 | 71 | 2019 |
| Observer based battery SOC estimation: Using multi-gain-switching approach X Tang, B Liu, Z Lv, F Gao Applied energy 204, 1275-1283, 2017 | 70 | 2017 |
| Automotive battery equalizers based on joint switched-capacitor and buck-boost converters K Liu, Z Yang, X Tang, W Cao IEEE Transactions on Vehicular Technology 69 (11), 12716-12724, 2020 | 69 | 2020 |
| Investigating carbon footprint and carbon reduction potential using a cradle-to-cradle LCA approach on lithium-ion batteries for electric vehicles in China Q Chen, X Lai, H Gu, X Tang, F Gao, X Han, Y Zheng Journal of Cleaner Production 369, 133342, 2022 | 67 | 2022 |
| Real-time aging trajectory prediction using a base model-oriented gradient-correction particle filter for Lithium-ion batteries X Tang, K Liu, X Wang, B Liu, F Gao, WD Widanage Journal of Power Sources 440, 227118, 2019 | 64 | 2019 |
| Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter X Tang, K Liu, J Lu, B Liu, X Wang, F Gao Applied Energy 280, 115895, 2020 | 54 | 2020 |
| Future ageing trajectory prediction for lithium-ion battery considering the knee point effect K Liu, X Tang, R Teodorescu, F Gao, J Meng IEEE Transactions on Energy Conversion 37 (2), 1282-1291, 2021 | 49 | 2021 |
| Long-term battery voltage, power, and surface temperature prediction using a model-based extreme learning machine X Tang, K Yao, B Liu, W Hu, F Gao Energies 11 (1), 86, 2018 | 48 | 2018 |
| Remaining useful life prediction of lithium-ion battery based on discrete wavelet transform Y Wang, R Pan, D Yang, X Tang, Z Chen Energy Procedia 105, 2053-2058, 2017 | 47 | 2017 |
| Joint estimation of state-of-charge and state-of-health for all cells in the battery pack using “leader-follower” strategy X Tang, Y Zhou, F Gao, X Lai Etransportation 15, 100213, 2023 | 42 | 2023 |
