吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (3): 884-890.doi: 10.13229/j.cnki.jdxbgxb201703027

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Optimization design of hot-stamping beam structure considering rollover crash safety of school bus

HU Kan1, YU Ye2, YING Liang2, HU Ping2, HOU Wen-bin2   

  1. 1.School of Mechanical Engineering, Dalian University of Technology, Dalian 116024,China;
    2.State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024,China
  • Received:2016-01-18 Online:2017-05-20 Published:2017-05-20

Abstract: A novel hot-stamping beam with ultra-high strength is introduced to improve both rollover safety and lightweight performance, which is based on the mechanical characteristics of the side beams and the excellent properties of hot-stamping material. Finite Element Method (FEM) analysis is used to calculate single cantilever beam with impact load on the middle position. Results show that the maximum deformation of the hot-stamping beam is about 74.9% lower the load bearing capacity is about 223.6% higher than that with equal-mass. This demonstrates that this novel beam has extremely crashworthy performance and potency of lightweight. The rollover crash simulation and test of the original school bus are conducted, which show that the simulation result is in good agreement with the test result, suggesting that the FEM analysis is accurate. The deformation, acceleration and structure weight surrogate are established based on Radial Basis Function (RBF) method. Then, multi-objective evolutionary algorithms are employed to obtain the optimal solution set. The results show that the deformation is decreased by 38.2%, the acceleration of survive room is decreased by 23.4% and the structure weight is reduced by 63.9%. It is proved that the hot-stamping steel beam performs far better in both rollover safety and lightweight performance compared to the original one.

Key words: material synthesis and processing technology, vehicle engineering, hot-stamping, school bus, rollover safety, multi-objective optimization

CLC Number: 

  • TG386
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