A procedure for multi-objective optimization of tire design parameters

Article history: Received September 9 2014 Received in Revised Format October 23 2014 Accepted November 25 2014 Available online November 26 2014 The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method. © 2015 Growing Science Ltd. All rights reserved

[1]  M.A. El-Sharkawi,et al.  Pareto Multi Objective Optimization , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[2]  N. Korunovi,et al.  Finite Element Model for Steady-State Rolling Tire Analysis , 2009 .

[3]  O. A. Olatunbosun,et al.  FE Simulation of the Effect of Tire Design Parameters on Lateral Forces and Moments , 2004 .

[4]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[5]  Wolfgang Graf,et al.  A multi-objective optimization approach with consideration of fuzzy variables applied to structural tire design , 2013 .

[6]  Oluremi A. Olatunbosun,et al.  A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour , 2014 .

[7]  M. Koishi,et al.  Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2 , 2006 .

[8]  Marko Kovacevic,et al.  Software prototype for solving multi-objective machining optimization problems: Application in non-conventional machining processes , 2014, Expert Syst. Appl..

[9]  T. C. Warholic,et al.  Towards Predicting Relative Belt Edge Endurance With the Finite Element Method , 1990 .

[10]  Mir Hamid Reza Ghoreishy.  Finite element analysis of steady rolling tyre with slip angle: effect of belt angle , 2006 .

[11]  Pareto Solutions.  Multi-Objective Design Problem of Tire Wear and Visualization of Its , 2006 .

[12]  Wan-Suk Yoo,et al.  Multi-objective optimization of tire carcass contours using a systematic aspiration-level adjustment procedure , 2002 .

[13]  T. Kamegawa,et al.  Application of a Neural Network for the Optimization of Tire Design , 1999 .

[14]  Jonathan F. Bard,et al.  Engineering Optimization: Theory and Practice, Third Edition , 1997 .

[15]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.