An Empirical Capacity Degradation Modeling and Prognostics of Remaining Useful Life of Li-ion Battery using Unscented Kalman Filter

Venu Sangwan, Rajesh Kumar, Akshay Kumar Rathore

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Citations (Scopus)

Abstract

In battery power, electric vehicle lifetime and the cost of the battery are the primary concern and challenge in the fast evolving and promising uptake of an electric vehicle. Battery aging leads to gradually deteriorates in battery performance hence identification of battery states and health is essential. Battery health identification helps the customer to maintain and replace batteries in advance to prevent the loss caused by the unexpected failure of these batteries and help in reducing maintenance cost. This paper presents and compares two empirical models to describe battery degradation behaviors over its lifespan. Validation of the accuracy of the empirical model is performed by using experimental life-cycle test data. Subsequently, the most accurate model has been used in an Unscented Kalman Filter to predict battery remaining useful life (RUL). This work provides the initial step towards the development of battery health management system.

Original languageEnglish
Title of host publication8th IEEE India International Conference on Power Electronics, IICPE 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538649961
DOIs
Publication statusPublished - 2 Jul 2018
Externally publishedYes
Event8th IEEE India International Conference on Power Electronics, IICPE 2018 - Jaipur, India
Duration: 13 Dec 201815 Dec 2018

Publication series

NameIndia International Conference on Power Electronics, IICPE
Volume2018-December
ISSN (Print)2160-3162
ISSN (Electronic)2160-3170

Conference

Conference8th IEEE India International Conference on Power Electronics, IICPE 2018
Country/TerritoryIndia
CityJaipur
Period13/12/1815/12/18

Keywords

  • Battery Electric Vehicle
  • Capacity degradation
  • Health Management
  • Remaining Useful Life
  • State of Health
  • Unscented Kalman Filter

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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