International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
www.irjet.net
AUTOMATIC BATTERY HEALTH MONITORINGUSING MACHINE LEARNING FOR E-VEHICLES Sarupriya S1, Abitha N2, Aishwarya Lakshmi R3, Merscia Serylin Jefy A4, Shrinidhi N A5 Assistant Professor1, U G Students2,3,4,5 Electronics And Communication Engineering1,2,3,4,5 Velammal Engineering Collegr1,2,3,4,5 -------------------------------------------------------------------------***--------------------------------------------------------------------lifecycle. Therefore, a Battery Management System is a Abstract- Batteries, which are made of a combination of electrochemical cells, provide the necessary electrical current for powering electrical equipment. Batteries continuously transform chemical energy into electrical energy, and for them to operate at their peak efficiency, appropriate maintenance must be given. In addition to the use of batteries, it is also believed that health management systems with expertisein various battery conditioning features, such as temperature, current, and voltage regulation, charging and discharging management mechanisms, and other mechanisms, will help to reduce risks to people's health, safety, and property. These systems regulate battery performance using merit-based standards. In this paper, we provide a data-driven perpetual literacy system for neural networks to cover the foreseen parameters. We use a machine learning technique to extract crucial features from the discharge curves in order to estimate these values. Extensive simulations have been performed in order to evaluate the performance of the suggested technique at different currents and temperatures.
critical part of an electric vehicle, and a good battery management system can improve the life of an electric vehicle by several years. To address this inherent shortcoming of Lithium ion batteries, a battery management system is required to secure the entire system and keep track of the most efficient way to consume energy. These battery management systems must ensure that battery functions, such as SOH and SOC. A battery is used as a secondary power source in automobiles. An electric vehicle battery is a secondary (rechargeable) battery. It uses chemical energy stored in rechargeable battery packs for power and therefore does not require any combustion engine for propulsion. An electric vehicle battery or traction battery powers the propulsion of battery electric vehicles. Forinstance, the SOH and SOC in electrical cars are analogous to an odometer and a gasoline-powered car's fuel gauge, respectively. SOH and SOC are critical metrics because, if calculated properly, they can stop overcharging, reduce overheating, and increasebattery life.
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2. RELATED WORK
INTRODUCTION
Limited number of studies have demonstrated the potential of automatic battery health tracking using various ideologies.
The battery management system monitors individual cells in the battery pack. It then calculates how much current can safely go in (charge) and come out (discharge) without damaging the battery. The current limits prevent the source (usually a battery charger) and the load (such as an inverter) from overdrawing or overcharging the battery. This protects the battery pack from cell voltages getting too high or low, which helps increase the battery’s longevity.
An adaptive Gaussian mixture model (AGMM) was created by Yu, Jianbo, et al. for addressing of various changes of battery health over the courseof the battery's existence. A Bayesian-inference method is used to detect novel health states that are online modelled by removing and adding components in AGMM.
The BMS also monitors the remaining charge in the battery. It continually tracks the amount of energy entering and exiting the battery pack and monitors cell voltages. It uses this data to know when the battery is drained and shut the battery down. This is why lithiumion batteries don’t show signs of dying like a lead-acid, but just shut off.The Battery Management System on an electric vehicle monitors each cell in the battery pack closely. It ensures that the battery pack is safe to use and protects the car if the cells are not working correctly.In addition, it estimates the range that the vehicle can travel and helps improve the battery pack's overall
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According to Banaei et al., a novel technique for calculating a Lithium-Ion battery's State Of Health using impulse response has been developed. The proposed approach forecasts the terminal voltage of a battery using the terminal current measurement and exhibits the impulse response of a healthy battery. A system to diagnose a battery cell fault using a Deep Neural Network was developedby Lee, et al. The discharge voltage data that was obtained by operating the lithium battery cell at a high temperature was used by the DNN state in this method.
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