The invention relates to an NAGA-II optimization method based on a semi-active suspension mixing coefficient, and the method comprises the steps: firstly determining the range of the mixing coefficient, optimizing two smoothness indexes of vehicle body acceleration and suspension dynamic deflection at the same time through a multi-objective optimization method NSGA-II, and comparing the optimization effects of the two indexes under different alpha to obtain an optimal set of alpha; a random pavement input model is established by adopting a harmonic superposition method, so that a simulation result has higher randomness and is close to an actual pavement; three automobile ride comfort evaluation indexes are used as output vectors to establish a state-space equation, so that the distortion possibility of a simulation result is relatively low; the selection of a mixed coefficient is combined with a multi-objective genetic algorithm, and two contradictory objective functions are taken as optimization objectives, so that the optimization objectives are closer to actual application; the hybrid coefficient selected by using the NSGA-II multi-objective optimization method can compromise each evaluation index, so that the comprehensive performance of the semi-active suspension about the riding comfort is optimal.
本发明涉及一种基于半主动悬架混合系数的NAGA‑II优化方法,先确定混合系数的范围,通过多目标优化方法NSGA‑II同时优化车身加速度和悬架动挠度两个平顺性指标,并对比不同α下两个指标的优化效果,得到α的最优集合。本发明采用谐波叠加法建立随机路面输入模型,使仿真结果更具有随机性从而贴近实际路面;以三大汽车平顺性评价指标作为输出矢量建立状态空间方程,使仿真结果失真可能性较低;将混合系数的选取与多目标遗传算法结合起来,以两个互相矛盾的目标函数作为优化目标,使优化目的更加贴近实际运用;使用NSGA‑II多目标优化方法选取的混合系数能折中各个评价指标,使半主动悬架关于乘坐舒适性的综合性能最优。
NAGA-II optimization method based on semi-active suspension mixing coefficient
一种基于半主动悬架混合系数的NAGA-II优化方法
2025-03-11
Patent
Electronic Resource
Chinese
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