Lightweight Design of Automotive Front Side Rail Based on Robust Optimisation

• Published in: Thin-walled structures Vol. 45; no. 7; pp. 670 - 676
• Main Authors: Zhang, Yu, Zhu, Ping, Chen, Guanlong
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2007; New York, NY Elsevier Science
• Subjects: DOE; Exact sciences and technology; Front side rail; Fundamental areas of phenomenology (including applications); Inelasticity (thermoplasticity, viscoplasticity...); Lightweight design; Physics; Robust optimisation; RSM; Solid mechanics; Structural and continuum mechanics; Structural crashworthiness; DOE; Front side rail; Lightweight design; Structural crashworthiness; RSM; Robust optimisation; Motor car; Breaking in; Probabilistic approach; Geometrical parameter; Car body; Quadratic programming; Weight; Inelasticity; Uncertain system; Rail; Medium effect; Sequential method; Experimental design; Environmental effect; Response surface; Reliability; Deterministic approach; Crush
• ISSN: 0263-8231; 1879-3223
• DOI: 10.1016/j.tws.2007.05.007

Nowadays, both conventional automobiles and new energy cars require urgently the lightweight design to realise energy economy and environmental protection in a long run. The weight reduction of body structure plays a rather important role in decreasing the weight of full vehicle. In the real engineering problems, the variation in sheet gauge, geometrical size and material parameters, caused by environmental factors and other uncertainties, may affect the structural performances of body parts. Therefore, the lightweight design without considering this kind of tolerance may result in the loss of feasibility and reliability in engineering application. In this work, based on robust optimisation method, the study on the front side rail lightweight design is performed. The response surface method (RSM), coupled with design of experiment (DOE) technique, is employed to create the approximate functions of structural performances. The robust optimisation and deterministic optimisation formulations are constructed, respectively, for comparison. The solutions are obtained by using the sequential quadratic programming (SQP) algorithm. The lightweight design, considering the impact of the tolerance of sheet gauge, mechanical parameters of material and structural performances, is still guaranteed to be reliable when structural random varieties are present. The weight reduction achieved by using robust optimisation reached 29.96%.