TY - JOUR
T1 - A new structure optimization method for forced air-cooling system based on the simplified multi-physics model
AU - Lyu, Chao
AU - Song, Yankong
AU - Wang, Lixin
AU - Ge, Yaming
AU - Xiong, Rui
AU - Lan, Tian
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/11/5
Y1 - 2021/11/5
N2 - Energy storage systems equipped with lithium-ion batteries are susceptible to fire and explosion hazards, especially when such batteries are used to power electric vehicles. One of the most important reasons for these undesirable consequences is the lack of an effective battery thermal management system. In this regard, an optimization method for the forced air-cooling system is introduced based on a simplified multi-physics simulation model. The simplified multi-physics model consists an electro-thermal coupling model and a flow resistance network model. The accuracy of the simplified multi-physics model is verified by comparison with experimental results. Subsequently, the deflector angle and cell space in the forced air-cooling system are optimized, respectively, based on the simplified multi-physics model, via an exhaustive search method and a genetic algorithm. Finally, the verification platform for the forced air-cooling system is built. After the optimization of deflector angle and cell space, the maximum temperature and temperature difference are limited to 38℃ and 2℃, with a reduction of about 30% and 80%, with respect to the unoptimized version. The consistency between the simulated and measured maximum temperature further confirms the effectiveness of the structure optimization method. In that, the method proposed in this paper is of great significance to shorten the time of structural optimization for forced air-cooling systems.
AB - Energy storage systems equipped with lithium-ion batteries are susceptible to fire and explosion hazards, especially when such batteries are used to power electric vehicles. One of the most important reasons for these undesirable consequences is the lack of an effective battery thermal management system. In this regard, an optimization method for the forced air-cooling system is introduced based on a simplified multi-physics simulation model. The simplified multi-physics model consists an electro-thermal coupling model and a flow resistance network model. The accuracy of the simplified multi-physics model is verified by comparison with experimental results. Subsequently, the deflector angle and cell space in the forced air-cooling system are optimized, respectively, based on the simplified multi-physics model, via an exhaustive search method and a genetic algorithm. Finally, the verification platform for the forced air-cooling system is built. After the optimization of deflector angle and cell space, the maximum temperature and temperature difference are limited to 38℃ and 2℃, with a reduction of about 30% and 80%, with respect to the unoptimized version. The consistency between the simulated and measured maximum temperature further confirms the effectiveness of the structure optimization method. In that, the method proposed in this paper is of great significance to shorten the time of structural optimization for forced air-cooling systems.
KW - Experimental verification
KW - Forced air-cooling system
KW - Simplified multi-physics model
KW - Structure parameters optimization
UR - https://www.scopus.com/pages/publications/85113734425
U2 - 10.1016/j.applthermaleng.2021.117455
DO - 10.1016/j.applthermaleng.2021.117455
M3 - Article
AN - SCOPUS:85113734425
SN - 1359-4311
VL - 198
JO - Applied Thermal Engineering
JF - Applied Thermal Engineering
M1 - 117455
ER -
