汽车行驶动力学性能的多目标优化

Multi-objective optimization of vehicle ride dynamic behaviors

在1/4车辆模型的基础上建立7自由度人体-座椅-悬架模型。选取座垫加速度、悬架动挠度和车轮动载荷作为目标函数,根据参数灵敏度分析结果选择悬架和座垫参数作为设计变量。利用无量纲化消除多行驶工况对优化计算的影响,在此基础上建立了车辆行驶动力学性能多目标优化模型。选择带精英策略的非支配排序遗传算法(NSGA-II)对优化模型进行求解,得到了Pareto最优解集与Pareto前沿。优化结果显示:适当减小座椅座垫刚度并增大阻尼有助于改善乘坐舒适性并且几乎不影响其他性能;Pareto最优解集中的悬架刚度与阻尼呈线性正相关关系,这也决定了乘坐舒适性和悬架动挠度不可能同时达到最优设计;根据车轮动载荷的设计水平可以近似确定轮胎刚度。

A human-seat-suspension model with seven degrees-of-freedom was built on a 1/4car model.The vertical acceleration,suspension work space and dynamic tire load were selected as the objective functions,and parameters of the suspension and seat cushion were selected as the design variables according to the results of parameter sensitivity analysis.Dimensionless method was introduced to make the optimization computation independent of the working conditions.Then a multi-objective optimization model was built to optimize the ride dynamic behavior of vehicle.Non-dominated Sorting Genetic Algorithm-II（NSGA-II）was employed for optimization computation and Pareto optimal set and Pareto frontier were obtained.Results show that seat cushion with small stiffness and large damping contributes to improve ride comfort without worsening other behaviors.In Pareto optimal set,the suspension stiffness is linearly directly proportional to suspension damping,which decides that optimal ride comfort and suspension work space can not be obtained simultaneously.Tire stiffness can be approximately determined based on dynamic tire load.