期刊
IET POWER ELECTRONICS
卷 8, 期 10, 页码 1825-1833出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-pel.2014.0523
关键词
secondary cells; adaptive Kalman filters; H filters; nonlinear filters; square-root unscented Kalman filter; adaptive extended Kalman filter; tuning parameter adjustment; SOC-varying model; polynomial approximation; charge-discharge process; battery dynamical behaviour; universal linear model; AHF; lithium-ion battery types; battery state-of-charge-varying modelling; state-of-charge estimation; adaptive H filter design
This study suggests a new method for modelling lithium-ion battery types and state-of-charge (SOC) estimation using adaptive H filter (AHF). First, a universal linear model with some free parameters is considered for dynamical behaviour of the battery. The battery voltage and SOC are used as states of the model. Then for every period in the charge/discharge process the free parameters of the model are identified. Each period of process is associated with a specific SOC value, hence the parameters can be regarded as functions of SOC in the entire process. The functions are determined based on polynomial approximation and least squares method. The proposed SOC-varying model is incorporated in AHF for SOC estimation. Moreover, a new method for adjusting the tuning parameters of the filter is suggested. The proposed method is verified by experimental tests on a lithium-ion battery and is compared with adaptive extended Kalman filter and square-root unscented Kalman filter
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