Journal
ENERGIES
Volume 9, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/en9090710
Keywords
daptive extended Kalman filter (AEKF); electric vehicle (EV); state of charge (SOC); weighed coefficients
Categories
Funding
- National Science Foundation of China [51567012]
- key project of education department of Yunnan province [2015Z023]
- talent training program of Yunnan province [KKSY201302084]
- innovation fund of advanced techniques for new energy vehicles of Kunming University of Science and Technology [14078368]
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This paper focuses on state of charge (SOC) estimation for the battery packs of electric vehicles (EVs). By modeling a battery based on the equivalent circuit model (ECM), the adaptive extended Kalman filter (AEKF) method can be applied to estimate the battery cell SOC. By adaptively setting different weighed coefficients, a battery pack SOC estimation algorithm is established based on the single cell estimation. The proposed method can not only precisely estimate the battery pack SOC, but also effectively prevent the battery pack from overcharge and over-discharge, thus providing safe operation. Experiment results verify the feasibility of the proposed algorithm.
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