Advancements in battery thermal management for electric vehicles: Types, technologies, and control strategies including deep learning methods

Abstract

As electric vehicles (EVs) become more commonplace, the development and deployment of advanced battery thermal management (BTM) technologies are vital for increasing the sturdiness of EV batteries, ultimately contributing to the sustainable and massive adoption of electric mobility. This study comprehensively evaluates new advancements in BTM systems for EVs, supplemented with a comparative evaluation of various BTM technologies, including active and passive cooling strategies, structure design, and advanced control algorithms, including deep learning methods. The study also scrutinizes the software’s capabilities employed for designing BTM systems. The cross-relevant papers related to BTM systems from 2019 to early 2024, which rely on Scopus and Web of Science databases, are considered. The comparative evaluation explores the strengths and obstacles of different BTM processes, shedding light on their efficacy under varying operational conditions. Additionally, this study discusses the impact of BTM on overall EV efficiency from the perspective of thermal considerations. Insights into current research trends, innovations, and emerging trends in the field are also presented. Ultimately, this state-of-the-art study aims to thoroughly understand the latest BTM for EVs. The findings offer insightful information for scientists, engineers, and professionals pursuing sustainable transportation development and the continuous enhancement of EV technology.

Keywords

• Battery thermal management systems
• Control strategies
• Deep learning
• Electric vehicles
• Heat transfer