摘要
采用微型多目标遗传算法μMOGA进行可控减振器阻尼值的优化,选取前后悬架的阻尼参数作为优化变量,将车身振动加速度、悬架动行程及轮胎动位移均方根值作为优化目标,同时考虑悬架系统在不同的载荷、车速及路面等级条件下的特性,对可控减振器的三档阻尼值进行优化设计。根据优化结果,最终确定可控减振器"软/中/硬"三档阻尼值。各种悬架仿真测试证明该算法是一种高效率的多目标全局优化方法。
The μ multi-objective genetic algorithm is used to optimize the damping values of the controllable vibration damper. The damping parameters of the front and rear suspension are selected as the optimization variables, and the MSR values of the body vibration acceleration, the suspension travel movement and the tyres dynamic displacement are selected as the optimization objective. The three-levels damping values of the controllable vibration damper are optimized design by considering the characteristics of the different load, speed and road surface level for the suspension system at the same time. According to the optimization results, the three-levels damping values of the controllable vibration damper are confirmed, i. e. ＂soft-middle-hard＂. The suspensions simulation test proved that this algorithm is a kind of high efficiency of the multi-objective global optimization method.
出处
《噪声与振动控制》
CSCD
2012年第4期183-187,共5页
Noise and Vibration Control
关键词
振动与波
微型多目标遗传算法
可控减振器
优化设计
仿真
vibration and wave
μ multi-objective optimization genetic algorithms
controllable damper
optimumdesign
simulation
