Optimization method of suspension parameters for articulated vehicle based on ride comfort and road-friendliness
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摘要: 为了分析悬架系统对车辆舒适性和道路友好性的影响和选择合理的车辆悬架参数, 建立了七自由度的四轴拖挂车辆动力学模型。以拖车车身垂向加速度和各轴轮胎对路面的动作用力为目标函数, 通过统一目标函数法, 对拖挂车辆的各悬架参数进行多目标优化设计。优化后, 拖车车身垂向加速度下降了21.43%, 对路面具有最大作用力的拖车后轮的动载力减小了17.72%。优化结果表明: 合理选择拖挂车辆悬架参数不但可保证车辆行驶的舒适性, 而且还能明显减小重载车辆对路面的动作用力, 减轻对路面的损伤。Abstract: In order to investigate the influence of articulated vehicle's suspension system on ride comfort and road-friendliness and reasonably choose suspension parameters, a 7D dynamics model of 4-axle articulated vehicle was established.Taking the vertical acceleration of tractor and the dynamic load of every axle as object functions, a multi-objective optimization method of articulated vehicle's suspension parameters was put forward based on unified objective function method.After the optimization, tractor's vertical acceleration decreases by 21.43% and the maximal dynamic load of tractor's rear tire decreases by 17.72%.It is shown that using reasonable suspension parameters not only improves vehicle's ride comfort, but also reduces the dynamic load of truck acting on the road.
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表 1 初始仿真参数
Table 1. Initial siumulation parameters
参数 数值/kg 参数 数值/(N·m-1) 参数 数值/(N·s·m-1) 参数 数值/m 参数 数值/(kg·m2) m1 400 k1 1.03×106 c1 3 000 a1 0.778 J1 6 198 m2 553 k2 2.06×106 c2 3 000 a2 2.165 J2 100 000 m3 396 k3 2.00×106 c3 3 000 a3 2.712 J3 2 m4 396 k4 2.00×106 c4 3 000 b1 4.843 m5 2 659 k5 2.32×105 c5 2 200 b2 2.357 m6 12 460 k6 8.60×105 c6 10 000 d 1.000 k7 2.00×106 c7 84 000 表 2 子目标函数值对比
Table 2. Comparison of sub-objective function values
参数 拖车振动加速度/(m·s-2) 拖车前轮动载力/kN 拖车后轮动载力/kN 挂车前轮动载力/kN 挂车后轮动载力/kN 优化前 0.885 1 7.882 0 12.819 10.374 10.220 优化后 0.695 4 6.791 5 10.547 10.225 10.146 变化率/% -21.43 -13.84 -17.72 -1.44 -0.72 表 3 变量优化前、后对比
Table 3. comparison of variable values before and after optimization
参数 拖车前悬架刚度/(N·m-1) 拖车后悬架刚度/(N·m-1) 挂车悬架刚度/(N·m-1) 拖车前悬架阻尼/(N·s·m-1) 拖车后悬架阻尼/(N·s·m-1) 挂车悬架阻尼/(N·s·m-1) 优化前 2.32×105 8.60×105 2.00×106 2 200 10 000 84 000 优化后 1.13×105 8.20×105 1.92×106 5 200 30 500 64 250 -
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