Optimization of Suspension System of Self-Dumping Truck Using TOPSIS-based Taguchi Method Coupled with Entropy Measurement 2016-01-1385
This study presents a hybrid optimization approach of TOPSIS-based Taguchi method and entropy measurement for the determination of the optimal suspension parameters to achieve an enhanced compromise among ride comfort, road friendliness which means the extent of damage exerted on the road by the vehicles, and handling stabilities of a self-dumping truck. Firstly, the full multi-body dynamic vehicle model is developed using software ADAMS/Car and the vehicle model is then validated through ride comfort road tests. The performance criterion for ride comfort evaluation is identified as root mean square (RMS) value of frequency weighted acceleration of cab floor, while the road damage coefficient is used for the evaluation of the road-friendliness of a whole vehicle. The lateral acceleration and roll angle of cab were defined as evaluation indices for handling stability performance. The spring stiffness and shock absorber damping of the front suspension, spring stiffness of the rear suspension, torsional stiffness of the front and rear anti-roll bar are taken as the design variables, which are considered at three levels. A L18 orthogonal array is applied to implement the simulations, and the TOPSIS is thus used to integrate all determined performance criteria of ride comfort, road friendliness and handling stability into a single performance index. Meanwhile, the weights of the quality characteristics are determined by employing the entropy measurement method. Furthermore, the best factor levels are identified according to the Taguchi method principles for single response optimization. Finally, the optimal combination of suspension parameters is confirmed to illustrate the effectiveness of the proposed hybrid optimization method.