Predicting the state parameters of lithium ion batteries: the race between filter-based and data driven approaches-Reference-Cited by-同舟云学术

Predicting the state parameters of lithium ion batteries: the race between filter-based and data driven approaches

Published:2023 Issue:3 Volume:7 Page:598-628
ISSN:2398-4902
Container-title:Sustainable Energy & Fuels
language:en
Short-container-title:Sustainable Energy Fuels

Author:

Pandey Siddhi Vinayak¹,Parikh Nishi²^ORCID,Prochowicz Daniel³^ORCID,Akin Seckin⁴^ORCID,Satapathi Soumitra⁵^ORCID,Tavakoli Mohammad Mahdi⁶^ORCID,Kalam Abul⁷,Yadav Pankaj¹

Affiliation:

1. Department of Solar Energy, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382 007, Gujarat, India

2. Department of Science, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382 007, Gujarat, India

3. Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, Warsaw 01-224, Poland

4. Department of Metallurgical and Materials Engineering, Karamanoglu Mehmetbey University, 70200, Karaman, Turkey

5. Department of Physics, Indian Institute of Technology Roorkee, Roorkee, Haridwar, Uttarakhand, 247667, India

6. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

7. Department of Chemistry, Faculty of Science, King Khalid University, P. O. Box 9004, Abha 61413, Saudi Arabia

Abstract

Various techniques are used to estimate the SOC, SOH & RUL of LIBs. Labels AI, ML and DL are artificial intelligence, machine learning and deep learning, respectively.

Funder

Science and Engineering Research Board

Gujarat Council on Science and Technology

King Khalid University

Publisher

Royal Society of Chemistry (RSC)

Subject

Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SE/D2SE01209J

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1. Energy storage: Applications and challenges