Shi, W. and Wang, C., "Multi-objective Optimization of the Variable Stiffness Suspension of a Light Bus Based on Artificial Immune Algorithm," SAE Technical Paper 2014-01-0883, 2014, doi:10.4271/2014-01-0883.
In order to reasonably match the variable stiffness suspension and optimize the ride comfort and stability of a light bus, a virtual prototype model of the light bus was established in Adams-Car. Before the optimization, the tyre mechanical characteristics were tested by using a plate-type tyre tester, then the magic formula model of the tyre (Pac2002) was obtained by means of the global parameter identification method. The vertical vibration of the virtual model was simulated with the simulated B-class road profile, and its handling stability performance was also studied by simulation of the pylon course slalom test and steady static circular test. After that, an optimal method of the variable stiffness suspension was put forward. In the proposed method, the two-level stiffness (k1, k2) and the damping of the rear suspension and the torsional stiffness of the pre and post stabilizer bars were taken as the optimal variables. The Z-direction acceleration RMS of the bus frame, the yaw rate and the roll angle of the bus body were selected as the optimal target. By using an artificial immune algorithm to conduct optimizing calculation, the optimal result of the suspension parameters were obtained. At last, the sample of the light bus suspension was manufactured, and the comparative trials of the vehicle ride comfort and stability were carried out in an automotive proving ground to evaluate the optimization effect. The test results show that the proposed optimization method is right and it can be used for improving the ride comfort and stability of the vehicle with variable stiffness suspension. This also reflects that the joint optimization is a development trend of CAO (Computer-aided Optimization) technology, which has a certain guiding significance to the virtual development and optimization of automobile chassis.