Optimal lumped parameters estimation of vehicle passive suspension system using genetic algorithm

H. El-taweel, Mohamed M. Abd elhafiz, H. Metered

Abstract


In this paper, optimal lumped vehicle passive suspension parameters are estimated using genetic algorithm (GA) to decrease vibration levels of the vehicle body and passenger seat so that better ride comfort and vehicle stability are achieved. The optimal values of suspension parameters for minimizing a combined multi-objective function are tuned using GA due to its simplicity, convergence, and robustness. The equations of motion of five-degrees-of-freedom passive half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of the suspension system including bounce and pitch motion. The performance of the optimized passive suspension system using optimal lumped parameters is compared with the nominal passive to show the efficiency of the proposed optimized suspension system. The simulation results prove that the optimized passive suspension system using GA can offer significant improvements of ride comfort and vehicle stability.


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References


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