JOURNAL OF POWER SOURCES | 卷:273 |
Combined State of Charge and State of Health estimation over lithium-ion battery cell cycle lifespan for electric vehicles | |
Article | |
Zou, Yuan1  Hu, Xiaosong2  Ma, Hongmin1  Li, Shengbo Eben3  | |
[1] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China | |
[2] Univ Calif Berkeley, Energy Controls & Applicat Lab, Berkeley, CA 94720 USA | |
[3] Tsinghua Univ, Dept Automot Engn, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China | |
关键词: Electric vehicles; Lithium-ion battery; Kalman filter; Recursive least squares; State of charge; State of health; | |
DOI : 10.1016/j.jpowsour.2014.09.146 | |
来源: Elsevier | |
【 摘 要 】
A combined SOC (State Of Charge) and SOH (State Of Health) estimation method over the lifespan of a lithium-ion battery is proposed. First, the SOC dependency of the nominal parameters of a first-order RC (resistor-capacitor) model is determined, and the performance degradation of the nominal model over the battery lifetime is quantified. Second, two Extended Kalman Filters with different time scales are used for combined SOC/SOH monitoring: the SOC is estimated in real-time, and the SOH (the capacity and internal ohmic resistance) is updated offline. The time scale of the SOH estimator is determined based on model accuracy deterioration. The SOC and SOH estimation results are demonstrated by using large amounts of testing data over the battery lifetime. (C) 2014 The Authors. Published by Elsevier B.V.
【 授权许可】
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【 预 览 】
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