Estimation of Battery charging for Electric vehicle using soft computing techniques

Authors

  • S.Arulkumar Department of Electrical and Electronics Engineering, Academy of Maritime Education and Training (AMET), Deemed to be University, Chennai, India.
  • K.E.Lakshmiprabha Department of Electrical and Electronics Engineering, Karpaga Vinayaga College of Engineering and Technology, KVELL (Deemed to be University), Chengalpattu, India.
  • P.Rajivgandhi Department of Electrical and Electronics Engineering, Adhiparasakthi Engineering College, Melmaruvathur, India.
  • M.Saravanan Department of Electrical and Electronics Engineering, Holymary Institute of Technology and Sceince, Hyderabad, India.

DOI:

https://doi.org/10.70917/ijcisim-2026-4657

Keywords:

State of charge, Electric vehicle, Lithium-ion battery, Machine learning techniques

Abstract

The objective of this work is to estimate the SOC in Lithium-Ion batteries used in electric vehicles (EVs). The generalized linear model (GLM) is applied, the GLM method with Poisson regression and a linear interpolation in estimating the SOC. The coefficient of the models is obtained from three machine learning techniques. The new SOC estimation strategies are tested applied to a Lithium battery model computationally implemented in four driving profiles and comparison of the results obtained between the proposed method and other existing methods in the literature are performed.

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Published

2026-08-12

How to Cite

S.Arulkumar, K.E.Lakshmiprabha, P.Rajivgandhi, & M.Saravanan. (2026). Estimation of Battery charging for Electric vehicle using soft computing techniques. International Journal of Computer Information Systems and Industrial Management Applications, 18(16s), 1275–1294. https://doi.org/10.70917/ijcisim-2026-4657

Issue

Vol. 18 No. 16s (2026)

Section

Original Articles