Vehicle Suspension Optimization For Stochastic Inputs
Inamdar, Kailas Vijay
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In the present thesis, a simulation based numerical method has been proposed for optimization of vehicle suspension system for stochastic inputs from random road surface profiles. Road surfaces are classified in based upon the power spectral density functions. The road surface is considered as a stationary stochastic process in time domain assuming constant vehicle speed. Using Fourier transforms, it is possible to generate the road surface elevations as a function of time. Time domain responses of the output of the suspension system are obtained using transfer function techniques. Optimum values of the damper constant are computed by simulation of the Quarter Car Model for generated stochastic inputs for good road holding and passenger ride comfort. A performance index minimization procedure is developed to find optimum damper constant value considering mutually conflicting requirements of ride comfort and road holding. The handling of the vehicle, cornering force, tractive force depends upon the road holding. The road holding capacity of the vehicle changes with change in vehicle speed as well as road roughness. A quantitative measure for deciding the road holding of the vehicle is defined.