A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery

Wen-Jing SHEN; Han-Xiong LI

doi:10.1109/ACCESS.2017.2678598

A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery

Wen-Jing SHEN
, Han-Xiong LI^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

27 Citations (Scopus)

61 Downloads (CityUHK Scholars)

Abstract

This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.

Original language	English
Pages (from-to)	4377-4387
Journal	IEEE Access
Volume	5
Online published	9 Mar 2017
DOIs	https://doi.org/10.1109/ACCESS.2017.2678598
Publication status	Published - 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Research Keywords

group-wise identification
Levenberg-Marquardt algorithm
Li-ion battery
parameter identification
sensitivity analysis

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© 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission.

RGC Funding Information

RGC-funded

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10.1109/ACCESS.2017.2678598

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Cite this

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title = "A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery",

abstract = "This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.",

keywords = "group-wise identification, Levenberg-Marquardt algorithm, Li-ion battery, parameter identification, sensitivity analysis",

author = "Wen-Jing SHEN and Han-Xiong LI",

year = "2017",

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language = "English",

volume = "5",

pages = "4377--4387",

journal = "IEEE Access",

issn = "2169-3536",

publisher = "IEEE",

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TY - JOUR

T1 - A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery

AU - SHEN, Wen-Jing

AU - LI, Han-Xiong

PY - 2017

Y1 - 2017

N2 - This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.

AB - This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.

KW - group-wise identification

KW - Levenberg-Marquardt algorithm

KW - Li-ion battery

KW - parameter identification

KW - sensitivity analysis

UR - https://www.scopus.com/pages/publications/85018940572

UR - https://www.scopus.com/pages/publications/85018940572#tab=impact

U2 - 10.1109/ACCESS.2017.2678598

DO - 10.1109/ACCESS.2017.2678598

M3 - RGC 21 - Publication in refereed journal

SN - 2169-3536

VL - 5

SP - 4377

EP - 4387

JO - IEEE Access

JF - IEEE Access

ER -

A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery

Abstract

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Research Keywords

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GRF: Multi-scale Spatiotemporal Modeling and Intelligent Control for BMS

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A Sensitivity-Based Group-Wise Parameter Identification Algorithm for the Electric Model of Li-Ion Battery

Abstract

UN SDGs

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

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GRF: Multi-scale Spatiotemporal Modeling and Intelligent Control for BMS

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