Validation of a data-driven fast numerical model to simulate the immersion cooling of a lithium-ion battery pack
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DOI: 10.1016/j.energy.2022.123633
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- Wu, Tingting & Wang, Changhong & Hu, Yanxin & Liang, Zhixuan & Fan, Changxiang, 2023. "Research on electrochemical characteristics and heat generating properties of power battery based on multi-time scales," Energy, Elsevier, vol. 265(C).
- Zha, Yunfei & Meng, Xianfeng & Qin, Shuaishuai & Hou, Nairen & He, Shunquan & Huang, Caiyuan & Zuo, Hongyan & Zhao, Xiaohuan, 2023. "Performance evaluation with orthogonal experiment method of drop contact heat dissipation effects on electric vehicle lithium-ion battery," Energy, Elsevier, vol. 271(C).
- Zhang, Xiaoxi & Pan, Yongjun & Xiong, Yue & Zhang, Yongzhi & Tang, Mao & Dai, Wei & Liu, Binghe & Hou, Liang, 2024. "Deep learning-based vibration stress and fatigue-life prediction of a battery-pack system," Applied Energy, Elsevier, vol. 357(C).
- Wang, Bing-Chuan & He, Yan-Bo & Liu, Jiao & Luo, Biao, 2024. "Fast parameter identification of lithium-ion batteries via classification model-assisted Bayesian optimization," Energy, Elsevier, vol. 288(C).
- Rajib Mahamud & Chanwoo Park, 2022. "Theory and Practices of Li-Ion Battery Thermal Management for Electric and Hybrid Electric Vehicles," Energies, MDPI, vol. 15(11), pages 1-45, May.
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Keywords
Lithium-ion batteries; Immersion cooling; Experimental dataset; Numerical simulation; Uncertainty quantification; Sensitivity analysis; Surrogate model; Bayesian calibration;All these keywords.
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