Multi-objective optimization of tire carcass contours using a systematic aspiration-level adjustment procedure

While forming a basic tire configuration and supporting most static and dynamic loads of automobiles, tire carcass influences major tire performances according to its contour. Among significant tire performances, we in this study intend to improve the automobile maneuverability and the tire durabili...

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Bibliographic Details
Published in:Computational mechanics 2002-11, Vol.29 (6), p.498-509
Main Authors: CHO, J. R, JEONG, H. S, YOO, W. S
Format: Article
Language:English
Subjects:
Automobiles
Computational techniques
Contours
Dynamic loads
Exact sciences and technology
Finite difference method
Finite-element and galerkin methods
Flux density
Fundamental areas of phenomenology (including applications)
Maneuverability
Mathematical methods in physics
Multiple objective analysis
Nonlinear analysis
Optimization
Optimization techniques
Physics
Sensitivity analysis
Shape
Solid mechanics
Static elasticity
Static elasticity (thermoelasticity...)
Structural and continuum mechanics
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Summary:While forming a basic tire configuration and supporting most static and dynamic loads of automobiles, tire carcass influences major tire performances according to its contour. Among significant tire performances, we in this study intend to improve the automobile maneuverability and the tire durability by optimizing the sidewall carcass contour. In order to effectively maximize these multi-objectives, we refine the conventional satisficing trade-off methods (STOM) which were proposed originally for the multi-objective structural optimization, by introducing a systematic aspiration-level adjustment procedure. According to the systematic procedure, we perform the sidewall contour optimization that ideally distributes the sidewall carcass tension and minimizes strain-energy density at the belt edge. Since the tire analysis is highly nonlinear problem we employ an incremental analysis scheme, together with the finite-difference sensitivity scheme. Through the numerical experiment, we confirmed that the refined multi-objective optimization technique systematically leads to a final optimum sidewall contour, together with the stable and rapid convergence.
ISSN:0178-7675
1432-0924
DOI:10.1007/s00466-002-0359-2