Reliability Optimization Method for CFRP Control Arm with Multi-Scale Parameters

ObjectiveMulti-scale parameter uncertainties are involved in the design of carbon fiber reinforced polymer (CFRP) control arms. Macro-scale layup optimization is mostly adopted in existing researches, which can hardly balance material micro-property fluctuation and macro structural reliability. To fully exploit the mechanical properties of CFRP, a reliability design scheme with synergistic macro and micro parameters was proposed for CFRP control arms.MethodsFirstly, the mechanical properties of unidirectional CFRP were predicted by Digimat software, and the prediction accuracy was verified through tensile tests to provide data support for cross-scale parameter transfer. Secondly, structural replacement of the CFRP control arm was completed based on the equal stiffness principle, and a finite element analysis model was constructed to provide a calculation carrier for reliability evaluation. Then, a double-weighted vector-projection response surface method was proposed, and reliability analysis of the control arm under multi-scale uncertain parameters was realized combined with a polynomial surrogate model to balance calculation accuracy and efficiency. Finally, a multi-scale reliability optimization framework was established and solved by integrating the surrogate model, improved response surface method and particle swarm optimization algorithm.ResultsThe results show that the reliability calculation error of the double-weighted vector-projection response surface method is less than 0.9% compared with the Monte Carlo method. The optimized CFRP control arm achieves a weight reduction of 41.29% compared with the original steel structure under the constraints of 90% reliability and performance requirements, which can provide references for lightweight reliability design of composite automotive structural parts.