| Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression Z Deng, X Hu, X Lin, Y Che, L Xu, W Guo Energy 205, 118000, 2020 | 284 | 2020 |
| General discharge voltage information enabled health evaluation for lithium-ion batteries Z Deng, X Hu, X Lin, L Xu, Y Che, L Hu IEEE/ASME Transactions on Mechatronics 26 (3), 1295-1306, 2020 | 168 | 2020 |
| Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery Z Deng, L Yang, Y Cai, H Deng, L Sun Energy 112, 469-480, 2016 | 150 | 2016 |
| Predictive battery health management with transfer learning and online model correction Y Che, Z Deng, X Lin, L Hu, X Hu IEEE Transactions on Vehicular Technology 70 (2), 1269-1277, 2021 | 145 | 2021 |
| Health prognosis for electric vehicle battery packs: A data-driven approach X Hu, Y Che, X Lin, Z Deng IEEE/ASME transactions on mechatronics 25 (6), 2622-2632, 2020 | 135 | 2020 |
| Data-driven battery state of health estimation based on random partial charging data Z Deng, X Hu, P Li, X Lin, X Bian IEEE Transactions on Power Electronics 37 (5), 5021-5031, 2021 | 133 | 2021 |
| Naturalistic data-driven predictive energy management for plug-in hybrid electric vehicles X Tang, T Jia, X Hu, Y Huang, Z Deng, H Pu IEEE Transactions on Transportation Electrification 7 (2), 497-508, 2020 | 133 | 2020 |
| Battery health estimation with degradation pattern recognition and transfer learning Z Deng, X Lin, J Cai, X Hu Journal of Power Sources 525, 231027, 2022 | 128 | 2022 |
| Data-driven fault diagnosis and thermal runaway warning for battery packs using real-world vehicle data L Jiang, Z Deng, X Tang, L Hu, X Lin, X Hu Energy 234, 121266, 2021 | 98 | 2021 |
| An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries P Li, Z Zhang, R Grosu, Z Deng, J Hou, Y Rong, R Wu Renewable and Sustainable Energy Reviews 156, 111843, 2022 | 96 | 2022 |
| Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles L Yang, Y Cai, Y Yang, Z Deng Applied Energy 257, 114006, 2020 | 77 | 2020 |
| Polynomial approximation pseudo-two-dimensional battery model for online application in embedded battery management system Z Deng, L Yang, H Deng, Y Cai, D Li Energy 142, 838-850, 2018 | 73 | 2018 |
| State of health prognostics for series battery packs: A universal deep learning method Y Che, Z Deng, P Li, X Tang, K Khosravinia, X Lin, X Hu Energy 238, 121857, 2022 | 72 | 2022 |
| A reduced-order electrochemical model for all-solid-state batteries Z Deng, X Hu, X Lin, L Xu, J Li, W Guo IEEE Transactions on Transportation Electrification 7 (2), 464-473, 2020 | 63 | 2020 |
| State of health estimation based on modified Gaussian process regression for lithium-ion batteries J Wang, Z Deng, T Yu, A Yoshida, L Xu, G Guan, A Abudula Journal of Energy Storage 51, 104512, 2022 | 62 | 2022 |
| A deep learning method for lithium-ion battery remaining useful life prediction based on sparse segment data via cloud computing system Q Zhang, L Yang, W Guo, J Qiang, C Peng, Q Li, Z Deng Energy 241, 122716, 2022 | 62 | 2022 |
| A review of second-life lithium-ion batteries for stationary energy storage applications X Hu, X Deng, F Wang, Z Deng, X Lin, R Teodorescu, MG Pecht Proceedings of the IEEE 110 (6), 735-753, 2022 | 61 | 2022 |
| Implementation of reduced-order physics-based model and multi-parameters identification strategy for lithium-ion battery Z Deng, H Deng, L Yang, Y Cai, X Zhao Energy 138, 509-519, 2017 | 60 | 2017 |
| Sensitivity analysis and joint estimation of parameters and states for all-solid-state batteries Z Deng, X Hu, X Lin, Y Kim, J Li IEEE Transactions on Transportation Electrification 7 (3), 1314-1323, 2021 | 57 | 2021 |
| Online identification of lithium-ion battery state-of-health based on fast wavelet transform and cross D-Markov machine Y Cai, L Yang, Z Deng, X Zhao, H Deng Energy 147, 621-635, 2018 | 44 | 2018 |
Xiaosong Hu 胡晓松Professor, Department of Mechanical and Vehicle Engineering, Chongqing University在 ieee.org 的电子邮件经过验证
