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Multidisciplinary optimal design of prismatic lithium‐ion battery with an improved thermal management system for electric vehicles
Author(s) -
Li Adriel Chi Tak,
Li Wei,
Chin Christina M. M.,
Garg Akhil,
Gao Liang
Publication year - 2021
Publication title -
energy storage
Language(s) - English
Resource type - Journals
ISSN - 2578-4862
DOI - 10.1002/est2.217
Subject(s) - battery pack , battery (electricity) , particle swarm optimization , finite element method , lithium ion battery , automotive engineering , internal resistance , range (aeronautics) , electric vehicle , reliability (semiconductor) , computer science , materials science , mechanical engineering , engineering , structural engineering , thermodynamics , algorithm , composite material , physics , power (physics)
Abstract The reliability and performance of lithium‐ion battery implemented in electric vehicles is greatly influenced by temperature. However, there is yet to have a systematic battery thermal strategy due to the poor understanding of battery thermal behavior. Although several heat management systems have been proven to be functional in regulating the operating temperature effectively, its capability would be overtaken by the escalating internal resistance due to ageing after a certain period. Hence, an integration of finite element method (FEM) with particle swarm optimization (PSO) approach is proposed, more specifically for phase change material‐based cooling system, by performing multiobjective optimization of battery pack volume and temperature effects. As such, the multidisciplinary design optimization is considered level by level for the battery pack in order to prevent premature ageing. After justifying the lithium‐ion composition, the prismatic battery pack is modeled parametrically and its thermal responses assessed using FEM. The dimension and arrangement of battery cells are assigned as design variables and constrained in a fixed range, which will then be iterated through online optimization whereby the temperature difference, SD and volume are objectives and minimized by using PSO algorithm. The optimization results are summarized: maximum temperature difference is 0.8208383 K, SD is 0.17239 K, and area is 53 082 cm 3 . The results also imply that the numbers and columns for cells have a significant impact on the effectiveness of heat transfer which may be correlated to its cell dimension.