汽车半主动座椅悬架主要参数优化研究

Research on Optimization of Initial Parameters of Semi-active Seat Suspension Based on Genetic Algorithm

半主动座椅悬架能有效改善驾驶平顺性,减少人体垂向振动,提升车内驾乘人员的乘坐体验.其中,半主动悬架的初始性能参数对悬架性能起到决定性作用.为此,本文针对半主动座椅悬架的初始性能参数(弹簧刚度和阻尼系数)的优化问题展开研究,在使用了随机路面模型、六自由度半车模型的基础上,以优化前后座椅垂向加速度之比作为适应度函数,利用遗传算法对半主动座椅悬架的刚度及阻尼系数进行优化.最后,利用MATLAB软件对优化结果进行仿真分析.结果表明,经算法优化后,座椅垂向加速度的均方根减少了16.4%,最大值下降了11.3%;座椅相对位移的均方根减少了36%,最大值下降了39.2%.

Semi-active seat suspension can effectively improve driving smoothness,reduce human vertical frequency,and improve the riding experience of drivers and occupants in the car.Among them,the initial performance parameters of the semi-active suspension play a decisive role in the suspension performance.Therefore,this paper studies the optimization of the initial performance parameters(spring stiffness and damping coefficient)of semi-active seat suspension,and optimizes the stiffness and damping coefficient of semi-active seat suspension by using genetic algorithms on the basis of establishing a random road model and a six-degree-of-freedom half-vehicle model,hence optimizing the ratio of vertical acceleration of the front and rear seats as the fitness function.Finally,a simulation analysis of the optimization results is carried out by using MATLAB software,leading to results showing that after algorithm optimization,the root mean square of the vertical acceleration of the seat is reduced by 16.4%,and the maximum value is reduced by 11.3%;the root mean square of the relative displacement of the seat is reduced by 36%,and the maximum value reports a 39.2%decrease.