Title: Multidisciplinary Design Optimization of BEV Body Structure
text: Blade Electric Vehicle (BEV) with a light body plays an important role in saving the energy and reducing the exhaust emission. However, reducing the body weight need to meet the heterogeneous attributes such as structural, safety and NVH (Noise, Vibration and Harshness) performance. With the rapid development of finite element (FE) analysis technology, simulation analysis is widely used for researching the complex engineering design problem. Multidisciplinary Design Optimization (MDO) of a BEV body is a challenging but meaningful task in the automotive lightweight. In present research, the MDO is introduced to optimize a BEV Body-in-White (BIW). The goal of optimization is to minimize the mass of the BIW while meeting the following requirements: structural performance (the bending and torsion stiffness is increased), NVH performance (the first overall torsion frequency is increased), and safety performance (the roof crush resistance is improved).The sample points were obtained by using Design of Experiment (DOE) with optimal Latin hypercube. The approximation models of mass, bending stiffness, torsion stiffness, modal and safety were established with the polynomial response surface method (RSM). The thicknesses of nine parts of the BIW were selected to be optimized by Muti-island Genetic Algorithm (MGA) method. After the MDO of the BIW, the paper drew the following conclusions: 1.The predictive values of the approximation and the results of FE simulation had a good agreement with an error less than 5.00% and the former met the engineering requirements; 2.The weight of the BIW was reduced by 2.00% and the optimized BIW met all prescribed requirements about structural, NVH and safety performance.