Structural design optimization of the arc spring and dual-mass flywheel integrated with different optimization methods

Abstract

This paper is about the structural design optimization of the torsional arc spring and the dual-mass flywheel (DMF) using three different population-based optimization techniques: Particle swarm optimization (PSO), differential evolution (DE), and genetic algorithm (GA). For this purpose, the equations of the motions of the vehicle powertrain are derived and implemented into the dynamic analysis to minimize the vehicle torsional vibrations. The parameters and initial angles of the arc spring are optimized by considering the objective function that is the sum of the maximum acceleration amplitudes of the crankshaft vibrations. The results demonstrated that the proposed design procedure is able to provide a proper arc spring and DMF inertias to reduce the torsional vibration significantly. Moreover, it is indicated that the DE optimization techniques provide best performances than others. Finally, it is also shown that the natural frequencies can be reduced by the DMF and the optimization results are under the idling critical speed of the engine. The obtained results of this paper are of utmost importance for the arc spring manufacturer about the design process considering both DMF and spring parameters simultaneously to minimize torsional vibration of the vehicle powertrain.