Version 1
: Received: 23 August 2024 / Approved: 23 August 2024 / Online: 23 August 2024 (18:52:21 CEST)
How to cite:
Maurya, M.; Gawade, S.; Zope, N.; Shitole, M.; Thorat, P. An Analytical Approach for Accurate SoC Estimation by Comparing Different Machine Learning Algorithms for EVs. Preprints2024, 2024081725. https://doi.org/10.20944/preprints202408.1725.v1
Maurya, M.; Gawade, S.; Zope, N.; Shitole, M.; Thorat, P. An Analytical Approach for Accurate SoC Estimation by Comparing Different Machine Learning Algorithms for EVs. Preprints 2024, 2024081725. https://doi.org/10.20944/preprints202408.1725.v1
Maurya, M.; Gawade, S.; Zope, N.; Shitole, M.; Thorat, P. An Analytical Approach for Accurate SoC Estimation by Comparing Different Machine Learning Algorithms for EVs. Preprints2024, 2024081725. https://doi.org/10.20944/preprints202408.1725.v1
APA Style
Maurya, M., Gawade, S., Zope, N., Shitole, M., & Thorat, P. (2024). An Analytical Approach for Accurate SoC Estimation by Comparing Different Machine Learning Algorithms for EVs. Preprints. https://doi.org/10.20944/preprints202408.1725.v1
Chicago/Turabian Style
Maurya, M., Manisha Shitole and Prajwal Thorat. 2024 "An Analytical Approach for Accurate SoC Estimation by Comparing Different Machine Learning Algorithms for EVs" Preprints. https://doi.org/10.20944/preprints202408.1725.v1
Abstract
The SOC (State of Charge) in Lithium-ion battery packs refers to determining a battery's current energy level or capacity at a given time. SOC is important for many battery-operated systems since it shows how much energy is available. In the earlier stage SOC is calculated by different techniques such as Coulomb counting, open-circuit voltage, Kalman filters, Data-Driven Approaches, and Real-Times Updates so these all methods are used to calculate the SOC Estimation in battery packs. In recent years, these old methods have had some errors and accuracy malfunctions in SOC estimation in battery packs. The SOC estimation errors occur on Two-Wheeler, Three-Wheeler, and four-wheeler of Electric Vehicles (EV). To Overcome this problem in current years the AI&ML Algorithms Methods are applied everywhere related to Accuracy, Solutions & All. To increase the accuracy of SOC Estimations we are going to use Machine Learning Algorithms to improve the SOC in Machine Learning there are various methods such as supervised, unsupervised, and reinforcement. Of these three methods, one of the best methods is to select the Algorithms is apply to the Battery packs to get accurate SOC Estimations. In Machine Learning, we select the Supervised Learning Algorithms. Currently, the project will focus on the use of a Supervised Machine Learning Algorithm which includes an Extra Trees Regressor, Bagging Regressor, K-Neighbors Regressor, Decision Tree Regressor, and Random Forest Regressor for SOC Estimation. In this, we will develop algorithms applied to Lithium-ion Battery Packs to accurately the SOC estimates. In conclusion, the algorithms we will develop by using Machine Learning are compared with the algorithms and analytical Models.
Keywords
State of Charge (SOC); Machine Learning Algorithm; Lithium-ion (Li-ion) Battery; Accurate Soc Estimation
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
