Research Papers

Bi-level Approach to Vehicle Component Layout With Shape Morphing

[+] Author and Article Information
Hong Dong

Vanderplaats Research and Development, Inc., 41700 Gardenbrook, Suite 115, Novi, MI 48375hdong@vrand.com

Paolo Guarneri

Department of Mechanical Engineering,  Clemson University, Clemson, SC 29634pguarne@clemson.edu

Georges Fadel

Department of Mechanical Engineering,  Clemson University, Clemson, SC 29634fgeorge@clemson.edu

J. Mech. Des 133(4), 041008 (May 18, 2011) (8 pages) doi:10.1115/1.4003916 History: Received September 07, 2009; Revised March 28, 2011; Published May 18, 2011; Online May 18, 2011

Engineering research into packing problems has been widely undertaken in recent years. The use of component shape morphing in layout design has, however, received little attention. Shape morphing is required for fitting a component of sufficient size in a limited space while optimizing the overall performance objectives of the vehicle and improving design efficiency. To morph components that can have arbitrary shapes in layout design, a mass-spring physical model-based morphing method is proposed and implemented. Vehicle layout design with shape morphing is a multi-objective, multilevel problem with a large number of design variables. To solve this large scale problem, decomposition is adopted. At the system level, the overall performance objectives are optimized with respect to locations and orientations of components. At the component level, deformable objects are morphed to fit in the available space. A vehicle underhood layout design problem is demonstrated to illustrate the proposed approach.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

2D mesh of circle and 3D mesh of a ball

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Figure 2

Flow chart of the bi-level iteration process

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Figure 3

Identifying the status that the target volume cannot be reached

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Figure 4

Ford Taurus underhood compartment

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Figure 5

Packing components in the underhood compartment

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Figure 6

Definition of accessibility along a specific direction

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Figure 7

Pareto front of system level global search. The Pareto set is projected on a 2D domain by considering solutions with the same accessibility = 10.

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Figure 8

System level global search result of solution C

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Figure 9

System level expanding optimization and subsequent component level volume expansion result

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Figure 10

System level local search result of solution C



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