Electric Vehicle Battery Pack Charging Time Prediction
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How to Cite

VijayaKumar, R., D. Kowsikan, A. Ponvel, R. Shyam, and G. Naveen Kumar. 2024. “Electric Vehicle Battery Pack Charging Time Prediction”. Journal of Electrical Engineering and Automation 6 (2): 144-59. https://doi.org/10.36548/jeea.2024.2.005.

Keywords

— Arduino Controller
— Current Sensor
— L298 Motor Drive
— Electrical vehicles
Published: 04-06-2024

Abstract

The electric vehicle's most crucial component is its battery, which provides the vehicle with power. A key element of electric vehicles (EVs) is the battery management system (BMS), which ensures the safe and efficient functioning of the battery pack. Previous research on electric vehicles has identified some drawbacks, such as lengthy charging times and the need for different charging methods depending on battery capacity and temperature. In the proposed work, the battery's state of charge and remaining capacity will be estimated by measuring the voltage and current with the use of a current sensor and temperature monitor. The novelty of the work lies in its ability to increase the range of electric vehicles. This is achieved through higher energy densities in high-voltage batteries, which allow for longer driving distances between charges. Additionally, faster charging systems can handle higher charging power levels, resulting in quicker charging times. These improvements in performance are made possible by the use of high-voltage batteries, which provide the necessary power for greater peak speeds and improved acceleration. As electric mobility becomes more widespread, the ability to accurately predict charging times based on layout becomes crucial in building user confidence, optimizing energy grid management, and promoting the widespread adoption of electric vehicles.

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