Data of "Optimization of automotive battery pack casing based on equilibrium response surface model and multi objective particle swarm algorithm"

Research on Light-weighting and safety of electric vehicle battery pack is an important topic. The maximum stress, maximum deformation, and frequency of the electric vehicle battery pack casing under three typical operating situations are employed as optimization boundary conditions in this work. Neither the quadratic polynomial without cross terms nor the classic quadratic polynomial response surface approach can strike the right balance between accuracy and efficiency. As a result, we provide and justify a more balanced adaptive response surface model prediction method. The ideal size of the battery pack shell is then computed as (T₁, T₂, T₃, T₄) = (0.7, 2.5, 1.6, 2.5), using the Multi-Objective Particle Swarm Optimization.The maximum stress was decreased from exceeding the permissible stress value to a suitable range of usage, the first order frequency was increased by 41% to minimize resonance, and the maximum deformation was decreased from 2.7 mm to 1.12 mm. These studies provide directions for electric vehicle battery pack optimization research.