吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (增刊1): 1-4.

• paper •     Next Articles

Nonparametric models of shock absorber based on support vector machine regression

GUO Kong-hui, WANG Xian-yun   

  1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
  • Received:2003-09-25 Online:2011-09-01 Published:2011-09-01

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Abstract:

Then we constructed non-parametric damper models using dynamometer data of two dampers,a general hydraulic damper and a displacement-dependent damper respectively.These models were based on support vector machine regression algorithm.Thereafter,these models were validated using the data outside the sample data.The validated results of the general damper showed that the model suppose the force was a function of velocity and displacement was better than the model that suppose the force is a function of velocity.The validated results of the displacement-dependent damper made out that this method could identify the nonlinear characteristics successfully.

Key words: vehicle engineering, shock absorber simulation, support vector machine, machine learning

CLC Number: 

  • U463.33


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