Develop a Versatile ECM Framework Capable of Accurately Representing Multiple Cell Types

  • Sarbani Mandal
  • , Bikash Sah
  • , Sai Krishna Mulpuri
  • , Anup Barai
  • , Praveen Kumar

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

1 Scopus citations

Abstract

Battery electric equivalent circuit model (ECM) parameters are widely popular for performing modelling and estimation of energy storage systems across various applications, such as grid storage and electric vehicle applications. The modelling parameters and estimated values (State of Charge (SoC) and State of Health (SoH)) form the basis of different analyses performed on the batteries. One of the critical challenges is to develop an ECM that is versatile enough to capture the varied nature of battery cell types because of changes in chemistry, geometry, applications, and operating conditions. In this paper, a versatile equivalent circuit model (ECM) development framework is approached, which is capable of precisely representing various cell types. Statistical analysis is performed to identify the most dominating factor among the ECM parameters, which affects most changes in cell manufacturing and chemistry, directing towards developing a universal equivalent circuit modelling approach.

Original languageEnglish
Title of host publication2025 IEEE Energy Conversion Congress and Exposition Asia
Subtitle of host publicationShaping a Greener Future with Power Electronics, ECCE-Asia 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331518868
DOIs
StatePublished - 2025
Event17th IEEE Energy Conversion Congress and Exposition Asia, ECCE-Asia 2025 - Bengaluru, India
Duration: May 11 2025May 14 2025

Publication series

Name2025 IEEE Energy Conversion Congress and Exposition Asia: Shaping a Greener Future with Power Electronics, ECCE-Asia 2025

Conference

Conference17th IEEE Energy Conversion Congress and Exposition Asia, ECCE-Asia 2025
Country/TerritoryIndia
CityBengaluru
Period05/11/2505/14/25

Keywords

  • and clustering
  • batteries
  • electric equivalent circuit model
  • principal component analysis
  • statistical analysis

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