Electric heavy-duty trucks often employ a three-section frame, where the central battery-integrated segment connects to the traditional front/rear rails via steel-aluminum bolted joints. These connections represent a critical structural weakness, bearing concentrated loads under demanding conditions. This paper addresses the trade-off between reliability and lightweighting in these mixed-material connections by proposing a multi-objective optimization methodology. High-fidelity finite element models, incorporating material nonlinearity, are first developed to analyze stress responses of bolt tightening process and bolts under realistic loading conditions of trucks. A Kriging surrogate model, trained via Latin Hypercube Sampling, is then constructed to reduce computational cost. Particle swarm optimization is subsequently employed to identify the optimal combination of design and process parameters. The results demonstrate that the optimized connection achieves a 27.5% reduction in maximum stress under extreme operating conditions while effectively controlling mass. This study provides an integrated and high-fidelity approach for the engineering design and lightweighting of these critical joints.
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