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Paper Title: Machine Learning Applied to Estimate the Battery SoH by using Various Algorithms in Python
Authors Name: Ashutosh Deshpande , Jitendra Patil , Sohan Patil , Ganesh Lohar
Unique Id: IJSDR2212190
Published In: Volume 7 Issue 12, December-2022
Abstract: Accurate state of health (SOH) prediction is significant to guarantee operation safety and avoid latent failures of lithium-ion batteries. With the development of communication and artificial intelligence technologies, a body of researches have been performed toward precise and reliable SOH prediction method based on machine learning (ML) techniques. In this the conception of SOH is defined, and the state-of the-art prediction methods are classified based on their primary implementation procedure. As an essential step in ML-based SOH algorithms, the health feature extraction methods reported in the literature are comprehensively surveyed. Next, an exhausted comparison is conducted to elaborate the development of ML-based SOH prediction techniques. Not only their advantages and disadvantages of the application in SOH prediction are reviewed but also their accuracy and execution process are fully discussed. Finally, pivotal challenges and corresponding research directions are provided for more reliable and high-fidelity SOH prediction. The growing interest and recent breakthroughs in artificial intelligence and machine learning (ML) have actively contributed to an increase in research and development of new methods to estimate the state of health of battery by using various algorithms. This paper provides a survey of battery state estimation methods based on ML algorithms accuracy such as, Logistic Regression (LR), Linear Discriminant Analysis (LDA), KNeighbors Classifier (KNN), Decision Tree Classifier (CART), GaussianNB (NB) with help of Python. Programming in Python with the help of SKlearn & Pandas.
Keywords: Python, Machine Learning, Artificial Intelligence, Algorithm, Battery, SOH.
Cite Article: "Machine Learning Applied to Estimate the Battery SoH by using Various Algorithms in Python ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 12, page no.1169 - 1175, December-2022, Available :http://www.ijsdr.org/papers/IJSDR2212190.pdf
Downloads: 000201535
Publication Details: Published Paper ID: IJSDR2212190
Registration ID:203240
Published In: Volume 7 Issue 12, December-2022
DOI (Digital Object Identifier):
Page No: 1169 - 1175
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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