基于AMESim的车辆主动悬架联合仿真研究

用AMESim软件建立了1／4车体二自由度的主动悬架模型,在MATLAB／Simulink中设计了模糊控制的主动悬架．利用AMESim和MATLAB进行了联合仿真。并与基于传统数学模型的主动悬架的仿真结果进行了比较,结果表明两者的车身加速度仿真曲线形状基本上是一致的,与被动悬架相比降低了垂直加速度,有效提高了乘车舒适性,控制策略是可行的。随着被控制对象的复杂化,动力学方程的建立越来越困难,这种联合仿真技术开创了一条效果很好而又不复杂的仿真新途径。     

主动悬架系统控制策略研究

文章设计一种主动悬架控制策略,通过建立四分之一车辆主动悬架系统模型,设计模糊滑模控制策略对主动悬架系统进行控制,并使用Matlab/Simulink软件对所建立的模型进行仿真分析。通过仿真结果验证了所建模型和控制策略的准确性,同时也改善了悬架系统的性能。     

汽车主动悬架的最优控制研究

汽车主动悬架的最优控制研究,首要的问题是建立车辆的1/4主动悬架模型。通过对车辆1/4悬架模型进行数学建模分析,利用最优控制理论求解目标性能函数,并设计最优控制器,利用MATLAB下的模块SIMULINK进行仿真得出性能数据,通过比较得出,运用最优控制的主动悬架的各项性能都比被动悬架提高较多。说明最优控制方法在主动悬架设计中有良好的作用。该设计从数学建模到最优设计以及最后的仿真数值分析具有一定的实际参考价值。     

基于ADAMS和Simulink的重型车辆主动悬架控制探究

使用ADAMS软件建立起重型车辆的虚拟样机模型,基于遗传算法设计主动悬架模糊控制策略并通过MATLAB编写控制算法,基于ADAMS和Simulink进行联合仿真验证。通过车辆在不同车速、较大路面激振下的仿真结果分析,验证联合仿真的有效性。试验结果表明,该控制方法能够有效提高车辆的抗侧翻能力。     

汽车半主动悬架性能的联合仿真分析

为分析半主动悬架对汽车性能的影响,文章对半主动悬架的性能进行了仿真分析。首先在ADAMS／View开发环境中建立1/4汽车悬架模型;然后基于MATLAB／Simulink设置模糊控制规则,对半主动悬架进行模糊控制,并模拟出随机路面输入信号;最后利用ADAMS／Control模块将ADAMS和MATLAB／Simulink悬架模型联合起来进行仿真,与被动悬架进行了对比分析．可以看出,模糊控制下的半主动悬架舒适性更高,行驶安全性和操纵稳定性更好。联合仿真结果表明,半主动悬架的舒适性和平顺性均优于被动悬架。     

基于次优控制的汽车主动悬架道路友好性研究

为分析随机次优控制对汽车主动悬架系统道路友好性的影响,基于简化的二自由度四分之一汽车振动模型,设计了悬架系统的随机最优和次优控制器.采用Matlab/Simulink软件建立车辆主动悬架系统仿真模型,并对被动悬架、最优控制悬架和次优控制悬架的道路友好性进行仿真比较.结果表明,合理设计的随机次优控制悬架的道路友好性与最优控制相当或接近,且优于被动悬架,具有更好的工程应用价值.      

基于MATLAB的主动悬架的最优控制分析

本文通过建立二自由度车辆悬架模型,应用了最优控制理论设计了主动悬架控制器,并在MATLAB/SIMULINK中建立了系统模型并进行了仿真。研究结果表明主动悬架比被动悬架的控制效果要好。     

空气悬架车辆ADAMS与MATLAB联合仿真研究

利用虚拟样机技术建立了基于ADAMS/Car模块的空气悬架车辆多体模型,并在MATLAB中设计了主动悬架PID控制器.通过ADAMS的路面编辑器建立了脉冲输入和随机输入两种路面模型,进行了ADAMS与MATLAB联合仿真研究.仿真结果表明,由车辆虚拟样机模型和PID控制策略组成的空气悬架系统有效改善了车辆平顺性.     

七自由度悬架模糊控制与仿真

为提高车辆悬架减振性能,兼顾车辆行驶平顺性和操稳性,以某微型轿车为基础建立了简化的七自由度悬架模型,并提出了模糊控制方法。以车身质心加速度、俯仰角加速度、侧倾角加速度、悬架动变形、轮胎动载荷作为评价指标,在Matlab/Simulink环境中以C级白噪声路面作为激励,对模糊控制主动悬架进行仿真。结果表明,模糊控制下的主动悬架各项评价指标均得到明显改善,为主动悬架在车辆上实际应用提供了参考。     

兼具馈能与主动抗侧倾功能的电控液压悬架系统设计与研究

为解决特种车辆或载重车辆在极端工况下易侧翻的问题,提出了一种兼具馈能与主动抗侧倾功能的电控液压悬架系统。对该悬架系统的主动抗侧倾模式和馈能模式进行了功能原理设计与分析;针对主动抗侧倾模式与馈能模式,构建了电液悬架系统仿真模型;设计了电液悬架系统主动抗侧倾模糊PID控制策略和侧倾力矩分配方案,以及执行机构逻辑门限值控制策略,并基于Matlab/Simulink、TruckSim和AMESim仿真软件,搭建了电液悬架系统主动抗侧倾控制策略联合仿真平台;对装配有电液悬架系统的车辆模型在极限工况下的抗侧倾性能进行仿真分析,并对车辆在随机路面激励输入下的馈能特性进行仿真分析。结果表明,装配该电液悬架的特种车辆具备较强的防侧翻能力,并具有较好的悬架运动能量回收潜力。     

汽车主动悬架系统状态反馈控制技术研究

车辆的悬架系统对于其舒适性和操纵稳定性都起着关键作用。随着计算机技术和液压伺服元件的发展，出现了主动和半主动悬架系统，在其控制策略具有二次型性能指标的最优控制方法比较成熟。通过建立系统的数学模型和仿真计算，对全状态反馈和被动悬架进行比分析，表明主动悬架采用和有限状态的反馈较全状态反馈有明显优势，是一种比较实用的状态反馈控制方法。     

Improving crosswind stability of fast rail vehicles using active secondary suspension

Rail vehicles are today increasingly equipped with active suspension systems for ride comfort purposes. In this paper, it is studied whether these often powerful systems also can be used to improve crosswind stability. A fast rail vehicle equipped with active secondary suspension for ride comfort purposes is exposed to crosswind loads during curve negotiation. For high crosswind loads, the active secondary suspension is used to reduce the impact of crosswind on the vehicle. The control input is taken from the primary vertical suspension deflection. Three different control cases are studied and compared with the only comfort-oriented active secondary suspension and a passive secondary suspension. The application of active secondary suspension resulted in significantly improved crosswind stability.     

汽车可控悬架系统的研究进展

总结了汽车可控悬架的发展状况,详细阐述了半主动悬架、主动悬架等的结构形式及国内外最新研究成果,提出了新型可能量再生的可切换的主动/半主动悬架结构方案,并进行了台架试验。评价了用于可控悬架的主要控制策略,指出应着重研究非线性控制与智能控制方法的综合运用,研究和开发可能量回收的汽车智能悬架,重点包含制动、转向、可控悬架的底盘集成控制。     

Adaptive Control of Vehicle Suspension

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

一种用于1／2汽车主动悬架的可调模糊控制器

本文对用于1／2汽车主动悬架系统的模糊控制器进行了研究。在设计模糊控制器时，引入模糊控制规则调整因子，使得控制策略灵活，适应性强，并以模拟路面时间历程为输入对汽车1／2主动悬架模型进行计算机仿真，结果表明用这种可调模糊控制器控制的主动悬架，汽车的适性和操纵稳定性都得到了明显改善。     

汽车主动悬架系统的试验研究

在分析汽车传统被动悬架的基础上,给出了一种新型主动悬架结构。介绍了该主动悬架的工作原理,建立了二自由度的主动悬架数学模型。采用天棚控制策略,设计并研制了主动悬架样机及试验台架,进行了被动悬架与主动悬架的台架对比试验。试验结果表明,与被动悬架相比,该主动悬架能有效改善汽车的动态性能。     

Adaptive Control of Vehicle Suspension

SUMMARY

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

Optimal Adaptive Active Suspensions for a Full Car Model

In order to present a useful method for designing active suspension of a vehicle, a linear full-car model is used in this investigation. In this model, the dampers of passive system are totally replaced by actuators. The actuators are controlled with optimal full state vector feedback. After determining feedback coefficients, the responses of active and passive systems were compared and it was found that performance of active system is much superior. It is desired that, changes in vehicle parameters would not affect the system's performance and hence should not violate its optimality. In other words, the system should behave adaptively using Model Reference Adaptive Control. The optimally controlled active suspension was used as a model for the active suspension of vehicle. In this way, the suspension of vehicle is controlled in such a way that its output approaches to that of the optimal active model. Thus the suspension should behave just like the optimal one.     

Vehicle dynamics control using an active third-axle system

This paper introduces the active third-axle system as an innovative vehicle dynamic control method. This method can be applicable for different kinds of three-axle vehicles such as buses, trucks, or even three-axle passenger cars. In this system, an actuator on the middle axle actively applies an independent force on the suspension to improve the handling characteristics, and hence, its technology is similar to slow-active suspension systems. This system can change the inherent vehicle dynamic characteristics, such as under/over steering behaviour, in the linear handling region, as well as vehicle stability in the nonlinear, limit handling region. In this paper, our main focus is to show the potential capabilities of this method in enhancing vehicle dynamic performance. For this purpose, as the first step, the proposed method in both linear and nonlinear vehicle handling regions is studied mathematically. Next, a comprehensive, nonlinear, 10 degrees of freedom vehicle model with a fuzzy control strategy is used to evaluate the effectiveness of this system. The dynamic behaviour of a vehicle, when either uncontrolled or equipped with the active third axle is then compared. Simulation results show that this active system can be considered as an innovative method for vehicle dynamic control.     

Adaptive neuron control using an integrated error approach with application to active suspensions

This paper proposes a new neuron control strategy for an active vehicle suspension system, with the emphasis on the study of multivariable and uncertain suspension characteristics. The novelty of this strategy is in the use of integrated error, which consists of multiple output errors in the regulated plant. By combining the integrated error approach with the traditional neuron control (TNC), integrated error neuron control (IENC) is presented. It provides a direct control to the multiple outputs of the control plant simultaneously. Taking a quarter-car model as an example, the proposed control strategy is applied and comparative simulations are carried out with various vehicle parameters and road input conditions. Simulation results prove the effectiveness and robustness of the proposed IENC method. In addition, the newly proposed neuron scheme provides a simple yet efficient new possibility for the control of a class of uncertain multivariable systems similar to an active vehicle suspension.