Optimal Design of an Electric Vehicle Frame Based on Response Surface Analysis

Abstract

Aiming at the lightweight optimization problem of electric commercial vehicle frames, a multi-objective optimization method combining response surface method with MOGA (Multi-Objective Genetic Algorithm) optimization algorithm is proposed. Based on ANSYS Workbench, the finite element model was established, and the comprehensive influence of the size of longitudinal beam and cross beam on the lightweight of frame was explored. Through Central Composite Design, the second-order response surface models which affect the weight, the maximum deformation, the maximum equivalent stress, the seventh frequency and the eighth frequency was established. Took the size of frame longitudinal and cross beam as design variables, multi-objective optimization function for mass, stress, deformation and natural frequency was established. The MOGA optimization algorithm was used to optimize the model and obtained an optimized solution. The verification results show that the weight of the original frame is reduced from 314.42kg to 284.76kg, a decrease of 9.43%. The maximum stress of the frame is reduced from 189.86Mpa to 179.8Mpa, and the structure is more reasonable. The vibration frequency of the frame can stagger the vibration frequency of the road excitation and human organs when the vehicle is running normally, and the probability of resonance electromotion with the motor is small. The lightweight optimization design method has good feasibility.