Battery Management System(BMS80) to Improve Battery Life in Electric Vehicles

Authors

  • Shanthala Devi Patil School of Compuer Science and Engineering, REVA University, Bengaluru-560064, India

  • S Roshan Dharan School of Compuer Science and Engineering, REVA University, Bengaluru-560064, India

  • Dheeraj M R School of Compuer Science and Engineering, REVA University, Bengaluru-560064, India

  • Bharath Srinivas S R School of Compuer Science and Engineering, REVA University, Bengaluru-560064, India


DOI:

https://doi.org/10.5281/zenodo.7920923

Keywords:

Electric Vehicle, Lithium-Ion Battery, Battery Management System, State of Charge(SoC), Battery Life

Abstract

The transportation sector is moving towards environmentally sustainable energy sources that are dependable, regulatory, and sustainable as the world battles with the negative impacts of conventional vehicles in conjunction with the shortage of fossil resources. Electric cars (EVs) are the Solution to the problem, However, the battery of an electric vehicle is crucial to its operation and the motor with all its operations use a sizable portion of an EV's battery which results in limited battery life. Therefore, preserving battery life in electric vehicles is a challenge that needs to be overcome by regulating the consumption of battery energy efficiently. The proposed work is focused on creating a Battery Management System(BMS) that limits the charging process using an eco-charging software function. The battery's state of charge (SoC) is monitored through a microcontroller, working in tandem with a software function to cease charging at 80%. The battery management system promises to increase battery life while also enhancing the convenience of charging and lowering the cost of EV ownership in the long run.

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Published

2023-05-10

How to Cite

Shanthala Devi Patil, S Roshan Dharan, Dheeraj M R, & Bharath Srinivas S R. (2023). Battery Management System(BMS80) to Improve Battery Life in Electric Vehicles. International Journal of Computational Learning & Intelligence, 2(2), 39–47. https://doi.org/10.5281/zenodo.7920923

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Section

RESEARCH ARTICLES