Digital Twin-based AAHP/CFRP Battery Enclosure Hybrid Optimization Lightweight Design Method

Abstract To address the problems of low multidisciplinary coupled simulation efficiency and long design-verification iteration cycles in lightweight design of traditional electric vehicle battery enclosures, a collaborative optimization method based on digital twin technology is proposed. Construct a digital-twin-driven lightweight design framework that integrates a multidisciplinary simulation platform with multi-fidelity analysis/gradient optimization algorithms to achieve closed-loop iteration. Design the aluminum alloy enclosure as a AAHP/CFRP hybrid material structure. Optimize the CFRP inner panel for free size/size/sequence and adopt the Kriging surrogate model combined with the PSO-GA hybrid algorithm to perform multi-objective size optimization for the AAHP outer panel. The results show that the optimized hybrid-material enclosure achieves a 12.3% weight reduction compared to the aluminum alloy structure. The first-order bending mode and second-order torsional mode frequencies are improved by 27.5% and 25.6%, respectively. The maximum compressive stresses in the X/Y-axis decreased by 26.1% and 27.6%, while the maximum deformations under 200 kN crush load were reduced by 22.4% and 19.2%, respectively. Under crash conditions, the peak stresses dropped by 16.2% and 16.3%. The modal test data and simulation results were compared, verifying the accuracy of the digital twin framework, providing an efficient and reliable digital solution for the safe lightweight design of electric vehicle battery enclosures.