Juncheng Lu

Lightweight design and crashworthiness of protective structures are critical for battery safety in electric vehicles (EVs). This study addresses the limited research on cross-sectional shape design of high-strength steel double-cell roll-formed tubes (DCRFTs), widely used in EV bumper beams, battery boxes, and electric bus frames. A parametric design method is proposed based on three parameters: middle flange offset (o), upper deflection angle (α), and lower deflection angle (β). Under the constraints of constant cross-sectional height and enclosed area, this method systematically generates diverse shapes, including square, trapezoid, hexagon, re-entrant hexagon, and various hybrid shapes. Validated finite element models were employed to analyze the deformation modes and crashworthiness of DP980 steel DCRFTs under idealized lateral three-point bending with simple supports. The results indicated that the re-entrant hexagon section reduced maximum deformation (Disp) by 2.95%, peak crushing force (PCF) by 9.53%, and improved crushing force efficiency (CFE) by 13.88% compared to the baseline square section. The parametric study and sensitivity analysis confirmed that the offset (o) was the most critical parameter, contributing over 80% of the variance in Disp, PCF, and CFE. Multi-objective optimization using an RBF surrogate model and the NSGA-II algorithm yielded Pareto optimal solutions. Compared to the baseline, three representative solutions achieved Disp reductions of 11.83–25.10% and CFE improvements of 15.63–22.26%, each with distinct trade-offs among objectives. This work establishes a methodological framework for parametric cross-section design of roll-formed profiles; its extension to realistic boundary conditions will further facilitate practical EV protective structure design.

To address the conflicts among objectives and the decision-making challenges in the multi-condition adaptive design of battery boxes for new energy vehicles, this study proposes a multi-objective collaborative optimization method based on an improved relaxation factor, aiming to achieve a comprehensive enhancement in both structural lightweighting and mechanical performance. A finite element model of the CTB high-strength steel roll-formed battery box was established and validated through modal testing. According to the Chinese National Standard GB 38031-2025, the mechanical responses of the battery box under random vibration, extreme operating conditions, and impact loads were analyzed to identify performance weaknesses. Sensitivity analysis was conducted to screen the design variables, and an improved relaxation factor strategy based on weight distribution difference information was introduced to construct a multi-objective collaborative optimization model. Furthermore, the entropy-weighted TOPSIS method was employed to enable intelligent decision-making on the Pareto solution set. The results demonstrate that the proposed method outperforms conventional approaches in both convergence speed and solution distribution uniformity. After optimization, the mass of the battery box was reduced by 12.38%, while multiple mechanical performance indicators were simultaneously improved, providing valuable theoretical and engineering guidance for the structural design of power battery systems.