Energy Consumption Analysis for the Prediction of Battery Residual Energy in Electric Vehicles

Authors

  • Keerthi Unni Department of Electronics and Telecommunication Engineering, Agnel Charities’ Fr. C. Rodrigues Institute of Technology, India
  • Sushil Thale Department of Electrical Engineering, Agnel Charities’ Fr. C. Rodrigues Institute of Technology, India
Volume: 13 | Issue: 3 | Pages: 11011-11019 | June 2023 | https://doi.org/10.48084/etasr.5868

Abstract

The emergence of Electric Vehicles (EVs) is a turning point in decarbonizing the road transport sector. In spite of the various apprehensions of the customers, such as range anxiety, long charging times, higher costs, and the lack of charging infrastructures, EVs have managed to considerably penetrate into the market. Appreciable subsidies in EV purchase and possibilities of renewable energy-based local charging equipment have encouraged more and more people to own EVs. Electrifying road transport also calls for scaling up of all stages of the supply chain as it involves a lot of raw materials and critical metals used for battery technology. One of the most important factors determining the range of an EV is the energy density of the battery, which has reached over 300 Wh/kg, from 100-150 Wh/kg a decade ago. This clearly means that the same vehicle can travel double the distance with the same mass. Understanding and modeling the energy consumption in an EV is quintessential in alleviating the fear of range anxiety. This paper presents a detailed mathematical equation-based energy consumption analysis of a particular EV model for Indian roads. Very few researchers have worked on drive cycles suitable for India. The novelty of the current work is that the energy consumption calculation can be worked out for any EV model or vehicle type through simple mathematical equations.

Keywords:

electric vehicle, Electric Vehicle Charging Stations (EVCSs), residual energy, aerodynamic drag, kinematics, tractive forces, rolling force, power electronics

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[1]
Unni, K. and Thale, S. 2023. Energy Consumption Analysis for the Prediction of Battery Residual Energy in Electric Vehicles. Engineering, Technology & Applied Science Research. 13, 3 (Jun. 2023), 11011–11019. DOI:https://doi.org/10.48084/etasr.5868.

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