Optimized design of battery pack system structure and cell layout based on crush and random vibration analysis
Abstract
To enhance the mechanical performance and energy density (ED) of the Battery Pack System (BPS), this study proposes a multi-objective optimization (MOO) method that automates cell array layout design. Using cell arrangement parameters as design variables, the approach optimizes ED, crush deformation (Def), root mean square equivalent stress (RMSES), and energy absorption rate (REA). A surrogate model based on Support Vector Regression (SVR) is established and combined with an improved Reference Vector Guided Evolutionary Algorithm (RVEA) to generate the Pareto front. The optimal solution is selected via the Entropy Weight-VIKOR method. Results show a 4.063% increase in ED, along with reductions of 8.131% in RMSES, 21.646% in Def, and 10.204% in REA. This method offers an innovative strategy for lightweight and safety-oriented BPS design with strong practical applicability.
Fields of Study & Subjects
Battery Modeling and Management
Advanced Multi-Objective Optimization Algorithms
Topology Optimization in Engineering
Publication details
- Journal / source
- Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
- Publication date
- 5 March 2026
- Language
- EN