用于电子稳定程序的汽车模型和控制策略

电子稳定程序(ElectronicStabilityProgram)是行驶车辆的一种主动安全系统,它综合了制动防抱死系统,驱动力控制系统和横摆力矩控制系统,使行驶车辆的安全性得到很大的提高。本文首先建立用于电子稳定程序的汽车模型,包括车身模型、悬架模型、转向模型、轮胎模型、制动系统模型、发动机模型和传动系模型。然后建立了主动横摆控制的控制逻辑,通过加入制动防抱死系统和牵引力控制系统,构成了电子稳定程序的控制逻辑。最后对移线运动、紧急转向、制动转向、驱动转向4个典型的工况进行仿真,从而验证了电子稳定程序控制逻辑的正确性。     

驾驶机器人车辆的多模式切换控制EI北大核心CSCD

为实现不同驾驶工况下精确的车速与轨迹跟踪,提出了一种驾驶机器人车辆多模式切换控制方法。通过分析驾驶机器人操纵自动挡车辆踏板与转向盘的运动,建立了驾驶机器人加速与制动机械腿和转向机械手的运动学模型和车辆纵横向动力学模型。在此基础上,设计了加速/制动机械腿切换控制器、模糊PID/模糊PID+Bang-Bang车速切换控制器和模糊PID/模糊PID+Bang-Bang转向切换控制器。加速/制动机械腿切换控制器以目标车辆加速度为切换规则,协调控制加速和制动机械腿,车速切换控制器以车速误差作为Bang-Bang控制器的模式决策准则和模糊PID控制器的输入,转向切换控制器以轨迹跟踪侧向误差作为Bang-Bang控制器的模式决策输入,并以当前与下一个控制时刻横摆角速度之差作为模糊PID控制器的输入。仿真和试验结果验证了所提出方法的有效性。     

驾驶机器人车辆的多模式切换控制

为实现不同驾驶工况下精确的车速与轨迹跟踪,提出了一种驾驶机器人车辆多模式切换控制方法。通过分析驾驶机器人操纵自动挡车辆踏板与转向盘的运动,建立了驾驶机器人加速与制动机械腿和转向机械手的运动学模型和车辆纵横向动力学模型。在此基础上,设计了加速/制动机械腿切换控制器、模糊PID/模糊PID+Bang-Bang车速切换控制器和模糊PID/模糊PID+Bang-Bang转向切换控制器。加速/制动机械腿切换控制器以目标车辆加速度为切换规则,协调控制加速和制动机械腿,车速切换控制器以车速误差作为Bang-Bang控制器的模式决策准则和模糊PID控制器的输入,转向切换控制器以轨迹跟踪侧向误差作为Bang-Bang控制器的模式决策输入,并以当前与下一个控制时刻横摆角速度之差作为模糊PID控制器的输入。仿真和试验结果验证了所提出方法的有效性。     

主动前轮转向系统与防抱死制动系统协调控制

针对汽车转向制动工况,研究汽车主动前轮转向系统(AFS)和防抱死制动系统(ABS)的协调控制;建立七自由度整车模型、前轮主动转向系统模型、防抱死制动系统模型以及轮胎模型,设计了转向系统控制器和制动系统控制器,以及两子系统的协调控制器,并对提出的控制策略进行了仿真分析和对比验证。仿真结果表明:在转向制动工况下,与独立控制系统相比较,协调控制系统能够在保持车辆制动稳定性的同时缩短制动距离,充分发挥两子系统的优势,进一步了提高汽车的操纵性和安全性。     

车辆转弯制动横向轨迹控制驾驶员模型研究

为了较为真实地反映车辆转弯制动工况,建立了含Pacejka"魔术公式"非线性联合工况轮胎模型的4轮8自由度车辆系统模型,并基于预瞄跟随理论、加速度反馈控制和模糊PID控制技术建立了车辆转弯制动横向轨迹控制驾驶员模型。针对不同初始速度和制动强度,利用MATLAB/Simulink进行了横向轨迹控制仿真分析。分析结果表明,驾驶员控制模型能很好地跟踪横向轨迹,模型的可行性和有效性得到验证,同时不同仿真条件下结果的一致性也说明该控制方法具有较强的自适应能力和鲁棒性,为进一步研究复杂工况下的驾驶员模型及横向轨迹控制提供了一条可行的途径。     

汽车主动前轮转向与防抱死制动系统集成控制研究

以车辆动力学软件Carsim和Matlab/Simulink为平台,分别建立了基于滑模变结构控制的主动前轮转向(AFS)和滑移率门限控制的防抱死制动系统(ABS)控制器模型,并将2种控制系统进行了集成,建立了联合仿真模型。仿真结果表明,在分离路面紧急制动工况下,通过将AFS与ABS进行集成控制,能够进一步提高ABS的制动效能,在保持车辆制动稳定性的同时缩短了制动距离。     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制，提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响，建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动，建立油门机械腿和制动机械腿的运动学模型。在此基础上，分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器，并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入，分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中，为了减少控制抖振，滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰，避免了油门控制与制动控制之间的频繁切换，并实现了精确稳定的车速控制。     

A Study on the Performance Simulation and Control Scheme for In-wheel Motor Driven Vehicles

为多域车辆的陆地行驶,设计了轮边电机驱动系统,构建了基于轮边驱动系统的车辆模型,并对驱动控制方法进行了研究.在转向动力学理论分析基础上,在ADAMS中建立了多体动力学模型;提出了车辆驱动与转向的控制策略,在Matlab/Simulink环境建立了控制模型,运用联合仿真方法对车辆在直线加速、转向和制动等典型工况下的行驶性能进行仿真验证.结果表明车辆的主要性能符合预期目标,驱动控制策略有效.     

智能汽车极限工况下联合制动与转向的自动紧急避撞研究

为提高智能汽车极限工况下的自动紧急避撞能力,提出了一种联合制动与转向的综合控制方法。首先,建立了包含转向、制动和悬架子系统耦合特性的18自由度统一动力学模型,并对其进行了水平路面上的转向制动仿真。接着,提出了联合制动与转向的自动紧急避撞系统总体框架,其中路径规划选用五次多项式规划算法,纵向采用滑模跟踪控制,侧向采用基于2自由度参考模型的最优四轮转向跟踪控制。最后,参考乘用车双移线极限工况测试国际标准,构建自动紧急避撞驾驶场景,对上述模型在不同车速下的自动紧急转向避撞和联合制动与转向避撞进行了对比仿真。结果表明:当车速较高时,车辆实际轨迹与理想跟踪轨迹存在一定滞后,极限工况下仅通过转向操作难以成功避撞;而联合制动与转向的避撞控制系统可进一步提高车辆极限工况下的自动紧急避撞能力,最大通过车速可由50提高至60 km/h。     

转向工况下车辆主动悬架的侧倾控制EI北大核心CSCD

鉴于车辆簧上质量的振动和车轮的振动耦合,特别是转向工况下,车轮转向角对车辆侧倾的影响,为减小车辆的侧倾并有效抑制车辆的振动,建立了带主动悬架的整车模型,并运用微分几何理论设计了侧倾及减振控制律,对整车模型进行解耦。经过解耦后,簧上质量的俯仰、侧倾和垂向运动互相独立;车轮转角对车辆侧倾的影响得到有效的抑制。仿真结果表明,采用微分几何解耦后,车辆的侧倾角、俯仰角和垂向振动以及横摆角速度的超调量皆大幅度地减小,车辆乘坐的舒适性和转向的稳定性显著提高。     

Active front wheel steering model and controller for integrated dynamics control systems

We report a model and controller for an active front-wheel steering (AFS) system. Two integrated dynamics control (IDC) systems are designed to investigate the performance of the AFS system when integrated with braking and steering systems. An 8-degrees-of-freedom vehicle model was employed to test the controllers. The controllers were inspected and compared under different driving and road conditions, with and without braking input, and with and without steering input. The results show that the AFS system performs kinematic steering assistance function and kinematic stabilisation function very well. Three controllers allowed the yaw rate to accurately follow a reference yaw rate, improving the lateral stability. The two IDC systems improved the lateral stability and vehicle control and were effective in reducing the sideslip angle.     

Modeling and control of an anti-lock brake and steering system for cooperative control on split-mu surfaces

The brake and steering systems in vehicles are the most effective actuators that directly affect the vehicle dynamics. In general, the brake system affects the longitudinal dynamics and the steering system affects the lateral dynamics; however, their effects are coupled when the vehicle is braking on a non-homogenous surface, such as a split-mu road. The yaw moment compensation of the steering control on a split-mu road is one of the basic functions of integrated or coordinated chassis control systems and has been demonstrated by several chassis suppliers. However, the disturbance yaw moment is generally compensated for using the yaw rate feedback or using wheel brake pressure measurement. Access to the wheel brake pressure through physical sensors is not cost effective; therefore, we modeled the hydraulic brake system to avoid using physical sensors and to estimate the brake pressure. The steering angle controller was designed to mitigate the non-symmetric braking force effect and to stabilize the yaw rate dynamics of the vehicle. An H-infinity design synthesis was used to take the system model and the estimation errors into account, and the designed controller was evaluated using vehicle tests.     

汽车防抱死制动系统的自抗扰控制研究

汽车防抱死制动系统（Anti-lock Braking System,ABS）的作用是确保汽车制动时行驶方向的稳定性、可靠性,但是目前仍存在非线性、时变性以及参数不确定性等问题。为保证汽车制动行驶过程中的操纵稳定性和安全性,进一步实现各工况下防抱死制动系统的优化控制,以影响整车稳定的变量滑移率为研究对象,分析所设计策略的控制效果。搭建汽车动力学模型、制动系统模型、轮胎模型和滑移率模型等主要模型,设计基于滑移率的ABS二阶非线性自抗扰控制器。运用MATLAB/Simulink软件对基于自抗扰控制（Active Disturbance Rejection Control,ADRC）的ABS制动过程和基于模糊PID控制的ABS制动过程进行仿真,对比研究最佳滑移率、载荷、水泥-冰对接路面、扰动等对制动过程中的轮速、车速以及滑移率等动态性征反映的稳定性和抗扰能力的影响,同时研究其对最终制动距离和最终制动时间反映的制动性能的影响。最后,将自抗扰控制器和模糊PID控制器装配于试验车辆的ABS,进行水泥路面和冰-水泥对接路面制动过程的实车试验。研究结果表明：基于二阶非线性自抗扰控制算法的ABS制动的最终制动距离和最终制动时间更短、制动效果更优,制动过程中的轮速、车速和滑移率在响应速度、稳定性和抗扰能力等方面均更佳;试验结果与仿真结果吻合,证明了仿真模型及其仿真结果的可行性和正确性。     

Vehicle dynamic stability improvements through gain-scheduled steering and braking control

This paper is concerned with the synthesis of a robust gain-scheduled ?_∞ MIMO vehicle dynamic stability controller (VDSC) involving both steering and rear braking actuators. This VDSC aims at improving automotive vehicle yaw stability and lateral performances. The aim of this work is to provide a methodology to synthesise such a controller while taking into account the braking actuator limitations and use the steering actuator only if it is necessary. These objectives are treated in an original way by the synthesis of a parameter-dependent controller built in the LPV framework and by the solution of an LMI problem. The proposed solution is coupled with a local ABS strategy to guarantee slip stability and make the solution complete. Nonlinear time and frequency domain simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations, show the efficiency and robustness of the proposed solution.     

智能汽车自动紧急转向避撞的跟踪控制方法对比研究

为了提高智能汽车的主动安全性,提出3种不同的自动紧急转向避撞跟踪控制方法。首先建立汽车避撞简化模型,对制动、转向及两者相结合的3种不同避撞方式进行对比分析。其次,为深入研究汽车避撞过程中的实际响应,建立包含转向、制动及悬架3个子系统耦合特性的底盘18自由度统一动力学模型,并进行相关试验验证。随后构建智能汽车自动紧急转向避撞控制框架,对五次多项式参考路径和七次多项式参考路径的横摆角速度和横摆角加速度进行对比分析。接着以线性2自由度转向动力学模型为参考对象,对最优控制四轮转向、最优控制前轮转向、前馈与反馈控制相结合的前轮转向3种不同的跟踪控制系统分别进行设计。最后,以汽车底盘18自由度统一动力学模型为研究对象,对上述3种避撞控制系统进行仿真试验对比分析。研究结果表明：与制动避撞相比而言,转向避撞所需的纵向距离有较大降低,随着车速的增加和路面附着系数的越低,效果越明显;七次多项式参考路径比五次多项式参考路径的避撞过渡过程更为平缓,当实际车速与控制器所用车速不一致时,前者避撞性能表现更优;最优四轮转向控制系统在高、低2种不同附着路面都具有较好的避撞效果,最优前轮转向控制系统次之,而前馈与反馈相结合的前轮转向控制系统在低附着路面上则表现出严重的失稳。     

Advanced emergency braking under split friction conditions and the influence of a destabilising steering wheel torque

The steering system in most heavy trucks is such that it causes a destabilising steering wheel torque when braking on split friction, that is, different friction levels on the two sides of the vehicle. Moreover, advanced emergency braking systems are now mandatory in most heavy trucks, making vehicle-induced split friction braking possible. This imposes higher demands on understanding how the destabilising steering wheel torque affects the driver, which is the focus here. Firstly, an experiment has been carried out involving 24 subjects all driving a truck where automatic split friction braking was emulated. Secondly, an existing driver–vehicle model has been adapted and implemented to improve understanding of the observed outcome. A common conclusion drawn, after analysing results, is that the destabilising steering wheel torque only has a small effect on the motion of the vehicle. The underlying reason is a relatively slow ramp up of the disturbance in comparison to the observed cognitive delay amongst subjects; also the magnitude is low and initially suppressed by passive driver properties.     

基于ARM7的汽车底盘系统分层式协调控制试验研究

采用分层协调控制策略,进行了汽车电动助力转向系统和防抱死制动系统集成控制的研究.分别设计了底层控制器和上层协调控制器,底层控制器包括电动助力转向和防抱死制动两个单独的控制器,用以执行各子系统的控制任务;上层协调控制器则对两系统进行协调分析,并及时修改底层控制决策.试验结果表明,自行开发的底层控制器逻辑正确,上层协调控制器能够较好地协调两系统问的矛盾,解决了汽车在转向过程中施加紧急制动时车辆的操纵稳定性和平顺性变差的间题,使整车综合性能得到提高.     

Integrated fuzzy/optimal vehicle dynamic control

There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers.     

Minimizing the Path Radius of Curvature for Collision Avoidance

When a driver is suddenly presented with an obstacle in his path, or realizes that his speed is too great for the curved road ahead, commonly he saturates both inputs of steering and braking and thereby jeopardizes his chances of successfully avoiding a collision or negotiating the turn. Although anti-lock braking systems (ABS) avoid saturation of the braking and steerability usually remains, there is evidence to suggest that the vehicle performance with this system could be greatly improved. Could the steering, in addition to the braking, be automatically controlled to improve the performance? Because these threatening situations are so variable, it is very difficult to find a controller which can override both driver inputs and is always beneficial. Using a very simple model of the vehicle, the concept of minimizing the average radius of curvature of the path through controlling both driver inputs is shown to always be beneficial, and worthwhile. The results also carry over to a more realistic model.