How Machine Learning is Innovating Today's World

13Machine Learning Applications in Battery Management System

Ponnaganti Chandana^* and Ameet Chavan

VIT-AP University, SENSE Department, Andhra Pradesh, India

Abstract

Modern society is going through a substantial transition towards new forms of sustainable transportation and energy generation that allow for the reduction of the level of greenhouse emissions and atmospheric warming. The energy storage industry has evolved as there is a lot of ongoing research for the effective storage of energy. Batteries play an important role in this regard because they enable high-power, high-efficiency energy storage at a low cost. The battery industry is growing significantly, and lithium-ion batteries are widely applicable in diversified applications such as in electric vehicles (EVs) and smart grids that require a battery management system (BMS). BMS is a key element in applications such as electric vehicles and renewable energy. This assertion is due to BMS being responsible for managing the energy consumption completely or partially, as well as managing the energy storage in the battery.

BMS implementation necessitates a combination of software and hardware, which contains tasks to monitor, control, and estimate the state of battery and detect the fault. Although there are various types of BMS that allow for efficient energy utilization, new techniques are emerging that aim to contribute to the development of innovative solutions. The problems associated with improper battery monitoring ...