基于灰狼算法的矿用自卸车油气悬架半主动控制

为解决矿用自卸车乘坐舒适性与道路友好性相矛盾的问题，提出了一种可控阻尼阀式半主动油气悬架系统。搭建了包含摩擦力的油气弹簧AMESim物理模型，建立了可控阻尼阀的多项式力学模型；设计了一种以可控阻尼阀驱动电压为半主动控制对象的改进天棚控制策略，并基于灰狼优化算法对改进天棚策略关键控制参数进行优化。联合仿真结果表明：D级随机路面下，半主动油气悬架的车身加速度相比被动悬架减小了11.4%,而轮胎动载荷仅增加了1.1%,相比传统天棚控制策略，更好地兼顾了矿用自卸车的乘坐舒适性和道路友好性。硬件在环试验结果也验证了该控制策略的有效性和可行性。

Semi-active Control of Hydro-pneumatic Suspensions for Mining Dump Trucks Based on Grey Wolf Algorithm

 A valve-controllable semi-active hydro-pneumatic suspension system was proposed to coordinate the contradictions between the ride comfort and road friendliness of a mining dump truck. The AMESim physical models of the hydro-pneumatic spring considering the friction were established for the first time. The polynomial mechanics models of the controllable damping valve were built. The modified skyhook control strategy was designed by taking the driving voltage of the controllable damping valve as the semi-active control object. And two key control parameters of the strategy were optimized based on the grey wolf optimization algorithm. The co-simulation results show that the body acceleration of the proposed suspension systems is decreased by 11.4% while the tire dynamic load is slightly deteriorated by 1.1% on the D-class random roads. Compared with the traditional skyhook control， the modified skyhook strategy attains the better trade-off between the ride comfort and road friendliness of a mining dump truck. The hardware-in-loop test results also verify the effectiveness and feasibility of the proposed control scheme.