For the coach industry, rapid modeling and efficient optimization methods are desirable for structure modeling and optimization based on simplified structures, especially for use early in the concept phase and with capabilities of accurately expressing the mechanical properties of structure and with flexible section forms. However, the present dimension-based methods cannot easily meet these requirements. To achieve these goals, the property-based modeling (PBM) beam modeling method is studied based on the PBM theory and in conjunction with the characteristics of coach structure of taking beam as the main component. For a beam component of concrete length, its mechanical characteristics are primarily affected by the section properties. Four section parameters are adopted to describe the mechanical properties of a beam, including the section area, the principal moments of inertia about the two principal axles, and the torsion constant of the section. Based on the equivalent stiffness strategy, expressions for the above section parameters are derived, and the PBM beam element is implemented in HyperMesh software. A case is realized using this method, in which the structure of a passenger coach is simplified. The model precision is validated by comparing the basic performance of the total structure with that of the original structure, including the bending and torsion stiffness and the first-order bending and torsional modal frequencies. Sensitivity analysis is conducted to choose design variables. The optimal Latin hypercube experiment design is adopted to sample the test points, and polynomial response surfaces are used to fit these points. To improve the bending and torsion stiffness and the first-order torsional frequency and taking the allowable maximum stresses of the braking and left turning conditions as constraints, the multi-objective optimization of the structure is conducted using the NSGA-II genetic algorithm on the ISIGHT platform. The result of the Pareto solution set is acquired, and the selection strategy of the final solution is discussed. The case study demonstrates that the mechanical performances of the structure can be well-modeled and simulated by PBM beam. Because of the merits of fewer parameters and convenience of use, this method is suitable to be applied in the concept stage. Another merit is that the optimization results are the requirements for the mechanical performance of the beam section instead of those of the shape and dimensions, bringing flexibility to the succeeding design.
[1]
Thomas Vietor,et al.
Automatic concept model generation for optimisation and robust design of passenger cars
,
2007,
Adv. Eng. Softw..
[2]
Chengwu Duan,et al.
Beam element modelling of vehicle body-in-white applying artificial neural network
,
2009
.
[3]
A. Ismail-Yahaya,et al.
Multiobjective robust design using physical programming
,
2002
.
[4]
Magnus Eriksson,et al.
Simulation Driven Car Body Development Using Property Based Models
,
2001
.
[5]
Graham Thompson,et al.
A design process for complex mechanical structures using property based models, with application to car bodies
,
2002
.
[6]
Ren-Jye Yang,et al.
Multidisciplinary Design Optimization of A Full Vehicle With High Performance Computing
,
2001
.
[7]
Yoshio Kojima.
Mechanical CAE in Automotive Design
,
2000
.
[8]
Nicklas Bylund,et al.
Simulation driven product development applied to car body design
,
2004
.
[9]
Jack E. Thompson,et al.
Use of SFE CONCEPT in developing fea models without CAD
,
2000
.
[10]
Ren-Jye Yang,et al.
Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment
,
2004
.
[11]
Stijn Donders,et al.
Simplified modelling of joints and beam-like structures for BIW optimization in a concept phase of the vehicle design process
,
2009
.
[12]
Aki Mikkola,et al.
A Non-Incremental Finite Element Procedure for the Analysis of Large Deformation of Plates and Shells in Mechanical System Applications
,
2003
.
[13]
Wang Xiao-peng.
Pareto genetic algorithm for multi-objective optimization design
,
2003
.