Energy Storage System Modelling For Hybrid Electric Vehicle

¹ Ahl Al Bayt University, Karbala, Iraq
² Department of EEE, GRIET,Bachupally, Hyderabad, Telangana, India
³ Professor,New Prince Shri Bhavani College of Engineering and Technology, chennai
⁴ Department of Mathematics,Christ University, Bangalore
⁵ Department of computers Techniques engineering, College of technical engineering, The Islamic University, Najaf, Iraq, Department of computers Techniques engineering, College of technical engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of computers Techniques engineering, College of technical engineering, The Islamic University of Babylon, Babylon, Iraq

^* Corresponding author: Mohammed.g@abu.edu.iq
^** srividyadevi2001@gmail.com
^*** hodece@newprinceshribhavani.com
^**** subramani.r@christuniversity.in
^***** saifobeed.aljanabi@iunajaf.edu.iq

Abstract

The equivalent circuit model (ECM)-based traditional state-of-charge (SoC) estimate approaches combine all state variables into a single enhanced state vector. However, the stability and accuracy of the estimates are compromised by the correlations between RC voltages and SOC. In this article, the four battery chemistries have been discussed for their state variable characterization i.e. state of charge (SOC). The battery types considered are lead acid, nickel metal hydride, lithium ion. The manufacturer’s battery discharge curves are used to determine the model parameters, and a method is also described for doing this. An improved battery model is suggested in this study that can be applied to HEV design and analysis. By incorporating the electrical characteristics of the battery, the model generates precise results.