Numerical study on suspension parameters optimization for bus traveling on poor road condition

This paper uses a multi-objective approach in order to optimize the suspension parameters of a bus traveling on poorly maintained runways. The objective functions chosen are the minimization of loads acting on the track and the RMS accelerations on the seat of three strategically positioned passengers on the bus. The numerical model of the bus has 13 degrees of freedom, including lateral dynamics, and the optimization is performed at a traveling speed of 40 km/h in a Double Lane Change (DLC) maneuver. The track is generated according to ISO 8606: 1995, described as class E. The model provides correlations between the sidetracks, and the dynamic interaction between the pavement and the tire is considered using the well-known model of Pacejka. Finally, the equations are solved in the time domain by the nonlinear Newmark method. The numerical model is coupled to a multi-objective optimization algorithm based on the Quantum Particle Swarm Optimization (MOQPSO) and to the well-known Non-dominated Sorting Genetic Algorithm (NSGA-II) algorithm. Comparisons between the algorithms and a mono-objective approach are performed in order to verify the quality of the obtained results, as well as their performance. As general conclusion, it is verified that the new parameters generated by the optimization produce lower vibrations when compared to those obtained by using the nominal values. Thus, the resulting Pareto Front can be used to choose the most suitable components for the minimization of passenger’s acceleration and applied tire loads, remaining to a specialist the choice of the most convenient solution from the Pareto Front.