Abstract
The fatigue resistance of the torsion beam is the keyway to prolong the service life of the chassis of the driverless vehicle. The rigid-flexible coupling finite element model of the chassis is constructed using anti-fatigue algorithm. In this model, the stress time history of the torsion beam is obtained by modal stress recovery. The nominal stress method is used to analyze the fatigue life of the structure. It is known that the structure weight affects the fatigue life, so the algorithm aims at lightening the structure to realize the improved fatigue resistance of the torsional beam structure. The parametric model of torsion beam is constructed with mass and fatigue life as optimization objectives, first-order torsion mode frequency and torsion stiffness as constraints. Multi-objective particle swarm optimization (MPSO) based on the Kriging model is used to achieve improved fatigue life of the torsion beam. After optimization, the structural weight of the torsion beam is reduced by 19.20%, and the light-weight and anti-fatigue effect are better than the baseline design.
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