A seat suspension contributes greatly to vehicle ride comfort as a result of direct contact with the human body. Friction in a seat suspension produces strong non-smooth nonlinearity in seat dynamics, which makes the simulation-based optimization on the seat suspension’s performance time-consuming. This study tries to address parameter optimization on a vehicle seat suspension with the friction force in an analytical approach. A two degrees of freedom model is firstly established for the human body-seat system with friction and subjected to bandlimited random excitation. The nonlinear model is converted into an equivalent linear model by using Gaussian linearization. The dynamic responses of the linear model have then derived analytically and validated by Monte Carlo simulations. Based on the analytical solution, a multi-objective optimization strategy is proposed for the seat suspension. The acceleration of the human body and the suspension travel are chosen as the objective indexes to evaluate seat performance. Simulation results show that the proposed optimization strategy is efficient, where a global optimum is guaranteed owing to the analytical expression of the objective function. The optimization approach taking advantage of model linearization can be applied to similar mechanical systems with friction.

由于与人体直接接触，座椅悬架极大地提高了车辆的乘坐舒适性。座椅悬架中的摩擦会在座椅动力学中产生很强的非光滑非线性，这使得基于仿真的座椅悬架性能优化非常耗时。本研究试图通过分析方法解决具有摩擦力的车辆座椅悬架的参数优化问题。首先建立了受带限随机激励的带摩擦的人体-座椅系统的二自由度模型。通过使用高斯线性化将非线性模型转换为等效的线性模型。然后通过蒙特卡罗模拟分析和验证线性模型的动态响应。根据解析解，针对座椅悬架提出了一种多目标优化策略。选取人体加速度和悬架行程作为评价座椅性能的客观指标。仿真结果表明，所提出的优化策略是有效的，由于目标函数的解析表达式，保证了全局最优。利用模型线性化的优化方法可以应用于具有摩擦的类似机械系统。