林肯城市轿车后电脑控制空气悬架系统故障诊断

为了提高轿车的乘坐舒适性,一些高档轿车装用了电脑控制的悬架系统,这些系统有全电脑控制型(即轿车的前后4个悬架均由电脑控制)、后电脑控制型(即轿车的后面2个悬架由电脑控制,前面2个悬架仍采用传统型式,不受电脑控制)以及空气悬架系统和自动悬架系统.不同的车型所采用的电脑控制悬架系统是不同的,在使用和维修方面也有很大区别.     

基于滑模理论的半主动悬架控制

建立了4自由度的1/2车辆悬架模型.采用极点配置法进行切换超平面的设计,基于滑模理论并应用自由递阶法进行多变量变结构滑模控制器的设计,并用光滑函数消减系统抖振.研究了系统在随机激励条件下的车身垂向加速度与俯仰角加速度、前后悬架动行程和前后轮胎动位移等性能的控制效果,并对其进行了功率谱密度的仿真分析.仿真结果表明:该滑模控制器性能稳定,控制后悬架各性能参数在时域和频域中均得到明显改善,证明了所设计的多输入滑模控制器的有效性.     

基于径向基函数神经网络的半主动悬架滑模控制

采用天棚阻尼模型为参考模型,设计了1/4车辆悬架系统的滑模控制器,并用径向基函数神经网络对其进行了优化.研究了系统在随机激励条件下的车身加速度、悬架动行程和轮胎动位移等性能参数的控制效果,并对其功率谱密度进行了仿真分析.结果表明:该滑模控制器性能稳定,控制后悬架各性能参数在时域和频域中均得到明显改善.     

带天棚阻尼的1/2车辆主动悬架仿真研究

建立了两种带天棚阻尼的1/2车辆主动悬架控制模型,结合线性二次型最优控制理论,基于MATLAB线性二次型最优控制函数LQR(Linear Quadratic Regulator)、LQG(Linear Quadratic Gaussian)分别设计和计算两种模型中的控制力;利用MATLAB/Simulink工具建立仿真模型,在相同输入情况下对两种模型的部分性能参数进行仿真比较。结果表明基于LQR的主动悬架的质心加速度和车身俯仰角加速度响应值比基于LQG的小很多,而前后轮动载荷、前后悬架动行程响应值相差不大;理论上,基于LQG设计的带天棚阻尼的1/2车辆主动悬架系统更切实际。     

基于人车路模式的汽车主动悬架LQR控制及MATLAB仿真

车身与座椅间的非刚性连接及轮胎阻尼因素对汽车主动悬架的振动有一定影响,但该影响往往在悬架研究中被忽略,为此,建立1/4汽车三自由度模型,利用LQR控制理论对其进行控制仿真。结果表明,与被动悬架进行对比,车身垂直加速度由-4～4m/s~2降低到-2～2m/s~2,而悬架和轮胎动位移变化很小,极大改善汽车平顺性。另外,LQR控制器受性能指标加权系数影响很大,优化其系数,可进一步提高汽车平顺性,为主动悬架的后续研究提供一定参考价值。     

半主动悬架模糊PID混合控制及时滞分析

半主动悬架较被动悬架，在乘坐舒适性、操纵稳定性方面均有较大提高，同时与主动悬架相比具有性价比高、耗能小等优点，所以半主动悬架成为近年来汽车底盘研究的热点。本文基于车辆4自由度1／2半主动悬架模型，提出了模糊PID混合控制算法，并基于该算法对半主动悬架进行控制，且对半主动悬架系统的时滞问题做了定量分析。仿真结果表明，模糊PID混合控制的半主动悬架在车身加速度、车身俯仰角加速度、前后悬架动挠度、前后轮胎动载荷、前后簧载质量加速度等在时域和频域中均有所改善，且一定量的时滞对该算法亦影响较小。这对半主动悬架控制算法的研究和半主动悬架的开发具有较大参考价值。     

磁流变半主动悬架动力学特性的试验研究

通过台架试验为自制磁流变减振器建立可控阻尼力-励磁模型以便于计算机控制,并根据1/4车辆半主动悬架动力学模型确定天棚阻尼开关控制算法和LQR最优控制算法的相关参数;应用Labview模块化语言开发了数据采集与预处理、控制算法和计算机与PWM通信控制等模块,并在1/4车辆悬架试验台上进行半主动振动控制与无控制的对比试验.结果表明,自制的磁流变减振器结合所开发的控制算法能有效抑制车辆振动.     

可调减振器阻尼控制与半主动悬架的试验研究

建立车辆半主动悬架1/4模型,提出可调减振器阻尼控制的实现方法,设计半主动悬架台架试验系统。在可调减振器试验的基础上,建立了可调减振器阻尼与步进电机转角之间的关系。最后,对半主动悬架1/4物理模型进行了台架试验。结果表明,试验系统稳定可靠,阻尼控制易于实现,半主动悬架能较好地适应不同的路面输入,为半主动悬架及控制系统的进一步研究奠定了基础。     

半主动悬架的控制策略探讨

综述汽车悬架控制系统的基本类型,以半主动悬架为研究对象,推导建立汽车两自由度1/4车体模型,提出一种汽车半主动悬架系统的模糊控制方法,并利用MATLAB进行仿真,结果证明该控制策略有效.     

连续可变阻尼控制悬架控制系统及其故障诊断

<正>连续可变阻尼控制悬架控制系统又称CDC(Continuous Damping Control)悬架控制系统,属于半主动悬架控制系统,其按照路面情况和行驶条件,利用电磁阀连续调节减振器的阻尼,以确保最佳的操控稳定性和乘坐舒适性。该悬架控制系统在奇瑞瑞麒G6轿车及别克2009款君越轿车上有所应用。1 CDC悬架控制系统的组成如图1所示,CDC悬架控制系统主要由4个带CDC电     

Optimal Preview Control of Rear Suspension Using Nonlinear Neural Networks

The performance of neural networks to be used for identification and optimal control of nonlinear vehicle suspensions is analyzed. It is shown that neuro-vehicle models can be efficiently trained to identify the dynamical characteristics of actual vehicle suspensions. After trained, this neuro-vehicle is used to train both front and rear suspension neuro-controllers under a nonlinear rear preview control scheme. To do that, a neuro-observer is trained to identify the inverse dynamics of the front suspension so that front road disturbances can be identified and used to improve the response of the rear suspension. The performance of the vehicle with neuro-control and with LQ control are compared.     

Optimal Preview Control of Rear Suspension Using Nonlinear Neural Networks

SUMMARY

The performance of neural networks to be used for identification and optimal control of nonlinear vehicle suspensions is analyzed. It is shown that neuro-vehicle models can be efficiently trained to identify the dynamical characteristics of actual vehicle suspensions. After trained, this neuro-vehicle is used to train both front and rear suspension neuro-controllers under a nonlinear rear preview control scheme. To do that, a neuro-observer is trained to identify the inverse dynamics of the front suspension so that front road disturbances can be identified and used to improve the response of the rear suspension. The performance of the vehicle with neuro-control and with LQ control are compared.     

汽车非线性半主动悬架的模糊神经网络控制

考虑磁流变减振器阻尼力和悬架弹性元件非线性特性，建立车辆6自由度的半主动悬架非线性动力学模型。提出了一种基于模糊神经网络系统结构的模型参考自适应控制方法来研究汽车半主动悬架的非线性控制问题，并考虑半车模型前后悬架的输入时滞，对其进行了仿真研究。研究结果表明：运用模糊神经网络非线性控制方法能够使人体和车身垂直加速度、俯仰角加速度都得到很大的衰减，证实这种模糊神经网络控制方法可大大减少路面对车身的振动冲击，提高汽车行驶平顺性。     

Nonlinear Backstepping Active Suspension Design Applied to a Half-Car Model

A fresh nonlinear backstepping design scheme, which is developed for the control of half-car active suspension systems to improve the inherent tradeoff between ride quality and suspension travel, is proposed in this paper. Since ride quality is dependent on a combination of vertical and angular displacements of a vehicle body, the design of active suspensions must have the potential to minimize heave and pitch movements in order to guarantee the ride comfort of passengers. The other important factor to be emphasized in the design of active suspensions is the suspension travel which means the space variation between the car body and the tires. In order to avoid damaging vehicle components and generating more passenger discomfort, the active suspension controllers must be capable of preventing the suspension from hitting its travel limits. Our design strategy, with two intentionally additional nonlinear filters, shows the potential to achieve these conflicting control objectives. The novelty of our active suspension design is in the use of two particular nonlinear filters at both the front and rear wheels. The effective bandwidths of these two nonlinear filters depend on the magnitudes of the front and rear suspension travels, individually. When suspension travel is small, the proposed controllers soften the suspension for enhancing passenger comfort. However, our control design shifts its attention to rattlespace utilization by stiffening the suspension when suspension travel approaches its limits. As a result, the improvement of tradeoff between ride quality and suspension travel can be guaranteed and is then demonstrated through comparative simulations.     

Effect of Connecting the Front and Rear Air Suspensions of a Vehicle on the Transmissibility of Road Undulation Inputs

Airsprings have been used for vehicle suspensions over the last 40 years. They are mostly used as independent suspensions. Analysis of air springs available in literature is mostly limited to a single-degree-of-freedom system or a two-degrees-of-freedom system only in the translation mode. This paper deals with a model of a vehicle where the front and the rear springs are connected by a capillary tube. A two-degrees-of-freedom model having motion in bounce and pitch mode is presented. Equations of mass flow are linearized on the assumption of small variations in volume and pressure. Expressions for the transmissibility and the phase angle in the bounce and the pitch mode are derived. Road inputs to the front and the rear axles are assumed to be identical except for a phase difference between them. The effect of the capillary flow coefficient and that of the phase angle between the front and the rear axle excitation are studied. It is shown that an optimum value of the capillary flow coefficient exists which minimizes the transmissibility of motion in both modes over the entire frequency range. It is also observed that a phase angle of 180 degrees presents ideal transmissibility characteristics. Thus, a promising application of air springs for a vehicle suspension is presented.     

A Pitch-Plane Model of a Vehicle with Controlled Suspension

A vehicle model incorporating front and rear wheel suspensions and seat suspension is presented. The suspension control includes algorithms to provide both dynamic and steady state (levelling) control. Vehicle response to (a) vertical inputs due to ground disturbances at the wheels and (b) longitudinal inputs due to the inertial forces during braking and accelerating, are investigated. It is shown that the static (self-levelling) control causes a slight deterioration in dynamic performance. The active ride control produces improvements of ride comfort under dynamic conditions compared to an equivalent passively suspended vehicle. In steady state the proposed control eliminates the error heave of the body caused by tilting of the vehicle with active suspension.     

基于AI选型的汽车悬架系统参数化设计流程构造

建立了用于汽车悬架系统选型的多层前馈型人工神经网络模型,它采用自适应调整的BP算法。选型推理的依据有：轴距、前轮距、后轮距、整备质量、驱动形式、最高车速、制动形式、发动机最大功率和发动机排量。推理结果为前、后悬架的具体型式。经测试,其与实际情况的吻合率,对前悬架达到了100％,对后悬架达到了70％。进而开发出典型悬架型式的三维参数化设计模板,并集成相关技术环节,构造出基于AI选型的悬架系统参数化设计的一般流程。     

基于ADAMS的空气悬架客车平顺性仿真与试验

以多体系统动力学理论为基础,应用机械系统仿真分析软件ADAMS,创建空气悬架客车前悬架、后悬架的多体系统动力学模型,包括转向系、发动机、车身、前后轮胎等在内的整车虚拟样机模型。并通过编制路面谱文件对虚拟模型进行平顺性仿真和悬挂系统固有频率仿真试验,结果显示该车的平顺性能比较理想。将仿真结果与样车道路试验结果进行对比,发现二者比较吻合,从而验证了所创建的虚拟样机模型的可靠性。研究结果表明虚拟试验可以有效地分析汽车的平顺性。     

Effect of Connecting the Front and Rear Air Suspensions of a Vehicle on the Transmissibility of Road Undulation Inputs

SUMMARY

Airsprings have been used for vehicle suspensions over the last 40 years. They are mostly used as independent suspensions. Analysis of air springs available in literature is mostly limited to a single-degree-of-freedom system or a two-degrees-of-freedom system only in the translation mode. This paper deals with a model of a vehicle where the front and the rear springs are connected by a capillary tube. A two-degrees-of-freedom model having motion in bounce and pitch mode is presented. Equations of mass flow are linearized on the assumption of small variations in volume and pressure. Expressions for the transmissibility and the phase angle in the bounce and the pitch mode are derived. Road inputs to the front and the rear axles are assumed to be identical except for a phase difference between them. The effect of the capillary flow coefficient and that of the phase angle between the front and the rear axle excitation are studied. It is shown that an optimum value of the capillary flow coefficient exists which minimizes the transmissibility of motion in both modes over the entire frequency range. It is also observed that a phase angle of 180 degrees presents ideal transmissibility characteristics. Thus, a promising application of air springs for a vehicle suspension is presented.     

汽车磁流变非线性悬架模糊控制

建立了整车悬架系统的三维模型,根据试验数据得出了前后悬架弹簧的非线性特性曲线。前后悬架减振器均采用磁流变减振器,采用Bouc-Wen参数化模型为其阻尼力模型。采用模糊控制算法为整车半主动控制算法,采用ADAMS和Matlab联合对整车平顺性进行仿真。结果表明,采用模糊控制算法控制磁流变非线性悬架可提高整车的平顺性。