Machine learning assisted multi-objective design optimization for battery thermal management system-Reference-Cited by-同舟云学术

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Machine learning assisted multi-objective design optimization for battery thermal management system

Published:2024-09 Issue: Volume:253 Page:123826
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Zhou Xianlong,Guo Weilong,Shi Xiangyu,She Chunling,Zheng Zhuoyuan^ORCID,Zhou Jie,Zhu Yusong

Publisher

Elsevier BV

Reference49 articles.

1. Comparative study of flow-channel layout schemes in liquid cooling plates of a prismatic battery module;Dai;Appl. Therm. Eng.,2024

2. IEA, Global EV, Outlook 2023, 2023. https://www.iea.org/reports/global-ev-outlook-2023.

3. Numerical analysis of single-phase liquid immersion cooling for lithium-ion battery thermal management using different dielectric fluids;Jithin;Int. J. Heat Mass Transf.,2022

4. Structural optimization of lithium-ion battery for improving thermal performance based on a liquid cooling system;Shang;Int. J. Heat Mass Transf.,2019

5. Electrochemical thermal modeling and experimental measurements of 18650 cylindrical lithium-ion battery during discharge cycle for an EV;Panchal;Appl. Therm. Eng.,2018

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