Parameter Optimization of the Cab Suspension for Commercial Vehicles Based on the Differential Evolution Genetic Algorithms

For commercial vehicles, the parameter design and optimization of the cab suspension system are very important to ride comfort. Taking the vibration problem of a commercial vehicle as the starting point, the road load spectrum is tested and analyzed according to the user’s working scenarios, and the multibody dynamics model of the cab suspension system including actuator is established. The displacement drives of the system are obtained by the virtual load iteration method. The influence of boundary frequency to noise signals and drives standard deviation is analyzed, which is used in system identification. The method based on design of experiment is used to carry out joint experimental design and obtain the exploration space, and the cubic polynomial fitting is carried out to build a surrogate response surface model with high prediction accuracy. On the basis of differential evolution genetic algorithm, the parameters such as population number, crossover probability, and differential scale factors are studied. The optimization strategy is formulated, and the balance point is sought in optimizing diversity and convergence characteristics, so as to ensure that the ride comfort of the target vehicle is significantly improved.