Optimization of honeycomb battery package based on space mapping algorithm

TL;DR

This paper presents a novel honeycomb battery package design optimized using a space mapping algorithm, significantly reducing computational costs while improving stress distribution and structural strength.

Contribution

It introduces a space mapping optimization approach with a pseudo-plane-strain model for honeycomb battery packages, enhancing efficiency and reliability.

Findings

Stress distribution and magnitude are significantly improved.

Optimization process reduces computational cost.

Final design achieves better structural performance.

Abstract

A new honeycomb battery package structure is designed and optimized in this study. It is a honeycomb structure which uses grid to reinforce the strength. To obtain the highly accurate finite element (FE) model, the material parameters of 18650 cylindrical Li-ion battery are identified by using optimization techniques based on flat compression test data. Due to the expensive cost of finite element evaluation, the space mapping (SM) algorithm is suggested to optimize the structure of the package. Compared with other space mapping algorithms, the coarse model of space mapping in this work is based on a pseudo-plane-strain model. Moreover, to guarantee the reliability, the mean and variance values of battery stress are used to be the objective function. The final optimum solution is obtained in 3 days, and it shows the magnitude of stress and the distribution of stress are improved significantly compared with initial structure. Moreover, the computational cost of optimization for the problem is decreased greatly.