@ARTICLE{Qiu_Chenghui_Multi-objective_2023,
 author={Qiu, Chenghui and Wu, Chongtian and Yuan, Xiaolu and Wu, Linxu and Yang, Jiaming and Shi, Hong},
 volume={71},
 number={4},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e145677},
 howpublished={online},
 year={2023},
 abstract={Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.},
 type={Article},
 title={Multi-objective optimization of PCM-fin structure for staggered Li-ion battery packs},
 URL={http://journals.pan.pl/Content/126999/PDF/BPASTS_2023_71_4_3434.pdf},
 doi={10.24425/bpasts.2023.145677},
 keywords={staggered arrangement, phase change material, fin, entropy weight-TOPSIS, multi-objective optimization, thermal management},
}