| Review on supercapacitors: Technologies and performance evaluation J Zhao, AF Burke Journal of energy chemistry 59, 276-291, 2021 | 314 | 2021 |
| Electrochemical capacitors: Materials, technologies and performance J Zhao, AF Burke Energy Storage Materials 36, 31-55, 2021 | 105 | 2021 |
| Electrochemical capacitors: performance metrics and evaluation by testing and analysis J Zhao, AF Burke Advanced Energy Materials 11 (1), 2002192, 2021 | 96 | 2021 |
| Performance testing of supercapacitors: Important issues and uncertainties J Zhao, Y Gao, AF Burke Journal of Power Sources 363, 327-340, 2017 | 58 | 2017 |
| Machine learning for predicting battery capacity for electric vehicles J Zhao, H Ling, J Liu, J Wang, AF Burke, Y Lian ETransportation 15, 100214, 2023 | 51 | 2023 |
| Past, present and future of electrochemical capacitors: technologies, performance and applications AF Burke, J Zhao Journal of Energy Storage 35, 102310, 2021 | 34 | 2021 |
| Electric Vehicle Batteries: Status and Perspectives of Data-Driven Diagnosis and Prognosis J Zhao, AF Burke Batteries 8 (10), 142, 2022 | 32 | 2022 |
| Data-driven prediction of battery failure for electric vehicles J Zhao, H Ling, J Wang, AF Burke, Y Lian Iscience 25 (4), 2022 | 30 | 2022 |
| The creation of a representative driving cycle based on intelligent transportation system (ITS) and a mathematically statistical algorithm: A case study of Changchun (China) J Zhao, Y Gao, J Guo, L Chu Sustainable Cities and Society 42, 301-313, 2018 | 24 | 2018 |
| Cloud-based artificial intelligence framework for battery management system D Shi, J Zhao, C Eze, Z Wang, J Wang, Y Lian, AF Burke Energies 16 (11), 4403, 2023 | 21 | 2023 |
| Cloud-based deep learning for co-estimation of battery state of charge and state of health D Shi, J Zhao, Z Wang, H Zhao, C Eze, J Wang, Y Lian, AF Burke Energies 16 (9), 3855, 2023 | 21 | 2023 |
| Cycle life testing of lithium batteries: The effect of load-leveling J Zhao, Y Gao, J Guo, L Chu, AF Burke International Journal of Electrochemical Science 13 (2), 1773-1786, 2018 | 17 | 2018 |
| Specialized deep neural networks for battery health prognostics: Opportunities and challenges J Zhao, X Han, M Ouyang, AF Burke Journal of Energy Chemistry, 2023 | 16 | 2023 |
| Battery prognostics and health management from a machine learning perspective J Zhao, X Feng, Q Pang, J Wang, Y Lian, M Ouyang, AF Burke Journal of Power Sources 581, 233474, 2023 | 15 | 2023 |
| Battery prognostics and health management for electric vehicles under industry 4.0 J Zhao, AF Burke Journal of Energy Chemistry 84 (9), 30, 2023 | 15 | 2023 |
| Spatial-temporal self-attention transformer networks for battery state of charge estimation D Shi, J Zhao, Z Wang, H Zhao, J Wang, Y Lian, AF Burke Electronics 12 (12), 2598, 2023 | 10 | 2023 |
| Battery Diagnosis: A Lifelong Learning Framework for Electric Vehicles J Zhao, et al. https://ieeexplore.ieee.org/document/10003378, 2022 | 9 | 2022 |
| Autonomous driving system: A comprehensive survey J Zhao, W Zhao, B Deng, Z Wang, F Zhang, W Zheng, W Cao, J Nan, ... Expert Systems with Applications, 122836, 2023 | 8 | 2023 |
| Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks J Zhao, X Feng, J Wang, Y Lian, M Ouyang, AF Burke Applied Energy 352, 121949, 2023 | 7 | 2023 |
| Development, performance, and vehicle applications of high energy density electrochemical capacitors AF Burke, J Zhao Applied Sciences 12 (3), 1726, 2022 | 7 | 2022 |
Andrew F. BurkeResearch Engineer, University of California, DavisVerified email at ucdavis.edu
