Robust Kinematics Design Of McPherson Suspension Based On A Double-loop Multi-objective Particle Swarm Optimization Algorithm

In the traditional design of vehicle suspension system,mechanical parameters,such as spring stiffness and tire radial stiffness,are determined before optimizing the coordinates of suspension hard-points based on handling stability.However,the mechanical parameters of vehicle suspension systems vary with repeated changes in ambient temperature and loading conditions.Consequently,the coordinates of hard-points cannot guarantee satisfactory handling stability after long term vehicle use.To address this issue,firstly,the McPersion suspension system model was established based on the multi-body dynamics software ADMAS/Car.The relationships between the maximum absolute values of front wheel alignment parameters for a McPherson suspension system during parallel wheel travel analysis and the coordinates of suspension hard-points,spring stiffness and tire radial stiffness were determined using support vector regression(SVR).Next,a multi-objective optimization function was formulated based on the interval analysis method and accounting for mechanical parameters.Finally,a novel double-loop multi-objective particle swarm optimization(DL-MOPSO)algorithm was designed for the global optimization of the coordinates of hard-points.The ADAMS simulation results indicate that compared with the vehicle with the original coordinates of hard-points,both the DL-MOPSO algorithm and the traditional MOPSO algorithm can effectively reduce the variation ranges of front wheel alignment parameters,regardless of the values of the mechanical parameters.The results also show that DL-MOPSO performs better than MOPSO with both original and changed mechanical parameters.Except for an increase in the variation range of the caster angle by 9.68-9.80%,the variation ranges of the toe angle,camber angle and kingpin inclination angle with various mechanical parameters using the DL-MOPSO algorithm ere observed to be reduced by 45.70%-72.57%,3.92%-4.24% and 2.36%-3.06%,respectively.Therefore,the proposed DL-MOPSO algorithm provides better comprehensive vehicle handling stability than the traditional MOPSO algorithm.