吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (1): 15-20.doi: 10.13229/j.cnki.jdxbgxb201701003

• Orginal Article • Previous Articles     Next Articles

Parameter identification for UniTire model based on hybrid optimization method

ZHANG Jia-xu1, 2, LI Jing1   

  1. 1.State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2.R& D Center, China FAW Group Corporation, Changchun 130011, China;
  • Received:2015-09-09 Online:2017-01-20 Published:2017-01-20

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Abstract: A hybrid optimization method is proposed based Particle Swarm Optimization (PSO) algorithm and modified Gauss-Newton (S-N) algorithm, which is used for characteristic parameter identification of UniTire model under pure longitudinal slip and pure cornering conditions. Taking the full advantages of the two algorithms, the approximate solutions are identified first using the PSO algorithm, which is superior in global search; then, the optimal solutions of the parameters are obtained in the neighboring region of the approximate solutions by using the modified G-N algorithm, which is superior in local search. The results of residual analysis of the identified parameters show that the parameterized UniTire model with the identified results has high accuracy, and can meet the requirements to establish hardware in the loop simulation test environment for electric control unit of the vehicle chassis.

Key words: vehicle engineering, particle swarm optimization(PSO) algorithm, Gauss-Newton algorithm, UniTire model, parameters identification

CLC Number: 

  • U461.1
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