NDLI: Design of adaptive H ∞ filter for implementing on state-of-charge estimation based on battery state-of-charge-varying modelling

Content Provider	IET Digital Library
Author	Charkhgard, Mohammad Zarif, Mohammad Haddad
Abstract	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
Starting Page	1825
Ending Page	1833
Page Count	9
ISSN	17554535
Volume Number	8
e-ISSN	17554543
Issue Number	Issue 10, Oct (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-pel/8/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-pel.2014.0523
Journal	IET Power Electronics
Publisher Date	2015-06-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Extended Kalman Filter Adaptive H∞ Filter Design Adaptive Kalman Filter AHF Battery Dynamical Behaviour Battery State-of-charge-varying Modelling Charge-discharge Process Filtering Method in Signal Processing H∞ Filter Lithium-ion Battery Types Nonlinear Filter Polynomial Approximation Secondary Cell SOC-varying Model Square-root Unscented Kalman Filter State-of-charge Estimation Tuning Parameter Adjustment Universal Linear Model
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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