| 1 |
State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles
Zahid T, Xu K, Li WM, Li CM, Li HZ
Energy, 162, 871, 2018 |
| 2 |
Battery state of health estimation: a structured review of models, methods and commercial devices
Ungurean L, Carstoiu G, Micea MV, Groza V
International Journal of Energy Research, 41(2), 151, 2017 |
| 3 |
Probability based remaining capacity estimation using data-driven and neural network model
Wang YJ, Yang D, Zhang X, Chen ZH
Journal of Power Sources, 315, 199, 2016 |
| 4 |
Multi-time-scale observer design for state-of-charge and state-of-health of a lithium-ion battery
Zou CF, Manzie C, Nesic D, Kallapur AG
Journal of Power Sources, 335, 121, 2016 |
| 5 |
Multicell state estimation using variation based sequential Monte Carlo filter for automotive battery packs
Li JH, Barillas JK, Guenther C, Danzer MA
Journal of Power Sources, 277, 95, 2015 |
| 6 |
Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles
Farmann A, Waag W, Marongiu A, Sauer DU
Journal of Power Sources, 281, 114, 2015 |
| 7 |
Composite electrodes of disordered carbon and graphite for improved battery state estimation with minimal performance penalty
Wang JS, Sherman E, Verbrugge M, Liu P
Journal of Power Sources, 196(22), 9648, 2011 |
