LAPSE:2023.6478
Published Article
LAPSE:2023.6478
Review of the Li-Ion Battery, Thermal Management, and AI-Based Battery Management System for EV Application
Maryam Ghalkhani, Saeid Habibi
February 23, 2023
Abstract
With the large-scale commercialization and growing market share of electric vehicles (EVs), many studies have been dedicated to battery systems design and development. Their focus has been on higher energy efficiency, improved thermal performance and optimized multi-material battery enclosure designs. The integration of simulation-based design optimization of the battery pack and Battery Management System (BMS) is evolving and has expanded to include novelties such as artificial intelligence/machine learning (AI/ML) to improve efficiencies in design, manufacturing, and operations for their application in electric vehicles and energy storage systems. Specific to BMS, these advanced concepts enable a more accurate prediction of battery performance such as its State of Health (SOH), State of Charge (SOC), and State of Power (SOP). This study presents a comprehensive review of the latest developments and technologies in battery design, thermal management, and the application of AI in Battery Management Systems (BMS) for Electric Vehicles (EV).
Keywords
AI-based monitoring systems, battery management systems, electric vehicle, lithium-ion batteries
Suggested Citation
Ghalkhani M, Habibi S. Review of the Li-Ion Battery, Thermal Management, and AI-Based Battery Management System for EV Application. (2023). LAPSE:2023.6478
Author Affiliations
Ghalkhani M: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Habibi S: Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Journal Name
Energies
Volume
16
Issue
1
First Page
185
Year
2022
Publication Date
2022-12-24
ISSN
1996-1073
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Original Submission
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PII: en16010185, Publication Type: Review
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LAPSE:2023.6478
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https://doi.org/10.3390/en16010185
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