TY - JOUR
T1 - In-Plane Flexible Ring Tire Model Parameter Identification
T2 - Optimization Algorithms
AU - Li, Bin
AU - Yang, Xiaobo
AU - Yang, James
N1 - Publisher Copyright:
Copyright © 2018 SAE International.
PY - 2018
Y1 - 2018
N2 - Parameter identification is an important part of tire model development. The prediction performance of a tire model highly depends on the identified parameter values of the tire model. Different optimization algorithms may yield different tire parameters with different computational accuracy. It is essential to find out which optimization algorithm is most likely to generate a set of parameters with the best prediction performance. In this study, four different MATLAB® optimization algorithms, including fminsearchcon, patternsearch, genetic algorithm (GA), and particleswarm, are used to identify the parameters of a newly proposed in-plane flexible ring tire model. The reference data used for parameter identification are obtained through a ADAMS FTire® virtual cleat test. After parameters are identified based on above four algorithms, their performances are compared in terms of effectiveness, efficiency, reliability, and robustness. Once the best optimization algorithm for the proposed tire model is determined, this optimization algorithm is used to test different types of cost functions to determine which cost function is the best choice for tire model parameter identification. The study in this paper provides some important insights for the tire model parameter identification.
AB - Parameter identification is an important part of tire model development. The prediction performance of a tire model highly depends on the identified parameter values of the tire model. Different optimization algorithms may yield different tire parameters with different computational accuracy. It is essential to find out which optimization algorithm is most likely to generate a set of parameters with the best prediction performance. In this study, four different MATLAB® optimization algorithms, including fminsearchcon, patternsearch, genetic algorithm (GA), and particleswarm, are used to identify the parameters of a newly proposed in-plane flexible ring tire model. The reference data used for parameter identification are obtained through a ADAMS FTire® virtual cleat test. After parameters are identified based on above four algorithms, their performances are compared in terms of effectiveness, efficiency, reliability, and robustness. Once the best optimization algorithm for the proposed tire model is determined, this optimization algorithm is used to test different types of cost functions to determine which cost function is the best choice for tire model parameter identification. The study in this paper provides some important insights for the tire model parameter identification.
KW - Flexible ring tire model
KW - cleat tests
KW - optimization algorithms
KW - parameter identification
KW - vehicle dynamics
UR - http://www.scopus.com/inward/record.url?scp=85088850427&partnerID=8YFLogxK
U2 - 10.4271/10-02-01-0005
DO - 10.4271/10-02-01-0005
M3 - Article
AN - SCOPUS:85088850427
SN - 2380-2162
VL - 2
SP - 71
EP - 87
JO - SAE International Journal of Vehicle Dynamics, Stability, and NVH
JF - SAE International Journal of Vehicle Dynamics, Stability, and NVH
IS - 1
ER -