基于统计优化的车辆半主动悬架自适应控制

Adaptive Control Based on Statistical Optimization for Semi-active Suspension Vehicle

推导了使得车体振动加速度均方根值最小的二自由度半主动悬架的最佳阻尼比,分析了最佳阻尼比变化的影响因素;提出了一种基于统计优化的半主动悬架自适应控制算法;该算法不依赖于控制对象的模型及参数,仅依靠振动加速度的统计值,在悬架动行程空间约束下,以一定的电流步长动态地寻找悬架的最优阻尼比;控制的目标是在高频不平的路面上使得振动加速度均方根值最小,以保证良好的舒适性,在恶劣的路面上减少悬架击穿的概率,以保证良好的越野性;跑车试验证明,该算法对路面变化、减振器温度变化、悬架系统参数变化的影响均具有良好的适应性。

The optimal damping ratio, which guarantees the lowest mean square root of vehicle vertical acceleration, based on two-freedom degree model is obtained and the factors that affect the optimal damping ratio are analyzed. An adaptive control strategy based on statistical optimization for semi-active suspension vehicle is presented. The optimal damping ratio of the suspension system is searched in terms of the presented control algorithm with a given current step under the limitation of suspension travel. The control algorithm doesn＇t depend on the suspension＇s plant model and parameters, and only needs the statistical value of vertical acceleration. The control purpose is to obtain the good ride quality on high-frequent road surface and reduce the possibility of suspension bottoming stop in order to acquire high off road performance on rough roads. It has good adaptive ability to the changes such as road and temperature of absorber and parameters of suspension, which is proved through the field-testing.