为提升某轻型客车平顺性，进行了空气弹簧性能和悬架系统的匹配研究。建立了整车多体动力学模型,通过前悬架K&C台架试验、后悬架理论计算验证了悬架仿真模型的准确性，仿真得出脉冲路面输入下乘客位置在20km/h垂向加速度过大。搭建联合仿真平台，以扭杆弹簧和空气弹簧参数为设计变量，采用径向基神经网络和神经网络建立了驾驶员位置、乘客位置垂向加速度代理模型，并结合遗传算法对代理模型进行多目标优化，得出悬架参数优化方案。结果表明：优化后车辆以20km/h、30km/h过脉冲路面时，乘客位置的最大垂向加速度分别减小了26.46%和24.88%；在以80km/h速度过B级随机路面时，乘客位置的垂向加速度均方根值 减小了23.72%。 同时，驾驶员位置平顺性基本不变，明显改善了整车平顺性。
Abstract
In order to improve the ride comfort of a light bus, the matching research of air spring performance and suspension system was carried out. The multi-body dynamics model of the whole vehicle is established, and the accuracy of the suspension simulation model is verified through the K&C bench test of the front suspension and the theoretical calculation of the rear suspension. is too big. A co-simulation platform is built, and the parameters of torsion bar spring and air spring are used as design variables, and radial basis neural network and neural network are used to establish the vertical acceleration surrogate model of driver position and passenger position, and the surrogate model is multi-objective combined with genetic algorithm Optimization, the suspension parameter optimization scheme is obtained. The results show that: when the optimized vehicle passes the impulse road at 20km/h and 30km/h, the maximum vertical acceleration of the passenger position is reduced by 26.46% and 24.88% respectively; The rms value of the vertical acceleration of the position is reduced by 23.72%. At the same time, the smoothness of the driver's position remains basically unchanged, which significantly improves the smoothness of the entire vehicle.
关键词
空气悬架 /
平顺性 /
多目标优化 /
NSGA-II /
代理模型
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Key words
Air suspension /
ride comfort /
multi-objective optimization /
NSGA-II /
proxy model
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