Using the Sliding‐Mode PWM Method in an Anti‐Lock Braking System

This study attempted to integrate the Pulse Width Modulation (PWM) method and sliding mode control theory to develop quasi‐continuous control for an automobile anti‐lock braking system. Two controllers are designed in this study. One applies directly by applying quasi‐continuous control to achieve ABS slip control. In addition, the quasi‐continuous control method was applied to develop pressure tracking control, and then this pressure tracking controller and the acceleration signal of the tire were implemented together to construct an anti‐lock braking controller. Both controllers were investigated on a dynamic test stand. Wet road braking was simulated by spraying water on the contact surface between the tire and the flywheel. Excellent braking results not only verify the performance of the sliding PWM method but also provide an alternative to an ABS controller without slip feedback.     

Robust cascaded automatic cruise control of electric vehicles

This article focuses on automatic cruise control for electrically driven vehicles. The objective is to track a given vehicle‐velocity profile. For this type of application, the so‐called wheel slip plays a key role, as it is a measure for the force transmitted from the wheel to the road. Conventional wheel‐ slip controllers are usually activated if the absolute value of the slip exceeds pre‐assumed thresholds. Furthermore, it is distinguished between a braking and acceleration maneuver using separately designed and implemented controllers. In contrast, the proposed concept requires neither an activation strategy for the slip controller nor a distinction between braking and acceleration. The cascaded control structure is based upon adaptive‐gains super twisting sliding‐mode algorithm, and the friction force estimator is realized as a second‐order sliding‐mode observer with constant gains. The effectiveness and robustness of the proposed concept are demonstrated in numerical simulations using a complex multibody vehicle model. Copyright © 2015 John Wiley & Sons, Ltd.     

防抱制动系统滑模状态观测和控制系统仿真

该文在考虑不平路面随机激励作用下车辆垂向振动的基础上 ,首先建立了四分之一车辆制动模型 ,而后充分运用滑移模式变结构的分析和设计方法 ,提出了车轮最佳滑移率的滑模实时在线辨识滑模优化算法 ,在对系统可观测性论证的基础上 ,设计了非线性滑模状态观测器 ,给出了单通道防抱制动系统基于滑移率的滑模控制算法 ,通过计算机仿真 ,验证了该控制算法的可行性和有效性 ,为设计具有高鲁棒性的防抱制动系统做了一定的理论探索和仿真工作     

基于TruckSim的三轴汽车自寻最优ABS控制设计

为提高三轴汽车的制动安全性能,在TruckSim中建立了三轴整车模型,针对以往研究中自寻最优理论不能应用到整车模型的问题,设计了简单可行的控制逻辑,将该理论应用到三轴整车模型。在TruckSim中建立了对开路面、对接路面、低附着路面、高附着路面四种工况,采用TruckSim与Simulink联合仿真,加入传统逻辑门限ABS作为对比,验证控制器的可行性。仿真结果表明,在四种工况下,自寻最优ABS的制动性能都要优于传统ABS,其中,在低附着路面工况下,自寻最优ABS的优越性最突出,制动距离减少24.5m,制动时间减少2.04s。说明自寻最优ABS可以自动搜索轮胎的最佳滑移率,提高三轴汽车的制动安全性能。     

A novel method for non-linear control of wheel slip in anti-lock braking systems

Anti-lock braking system (ABS) provides active safety for vehicles during braking by regulation of the wheel slip at its optimum value. Due to the non-linear characteristics and model uncertainties in vehicle dynamics, a non-linear controller with increased robustness should be designed for ABS. In this paper, to achieve this aim, an optimization-based braking torque control law is developed for ABS using the prediction of the wheel slip response from a continuous non-linear vehicle dynamics model. To increase the robustness of the controller, the integral feedback technique is appended to the design method. The derived control law and its special cases are evaluated and discussed. At the end, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of braking on dry and slippery roads. The simulation results indicate that, the wheel slip tracking error is remarkably decreased by the proposed controller. Moreover, the achieved control input is entirely smooth and suitable for implementation.     

基于ABS的重型车辆联合制动的特性研究

针对重型车辆利用联合制动方式进行制动时,不能获得最大制动力的问题,将ABS控制与联合制动方式相结合,采用基于Kiencke的μ-s模型,在制动过程中利用带遗忘因子的最小二乘法进行路面识别,通过μ-s的曲线斜率,对路况跃变进行识别,使车辆获得最佳的滑移率,从而获得最大制动力.仿真试验证明:基于ABS的联合制动方式可以获得...     

Vehicle state estimation for anti-lock control with nonlinear observer

Vehicle state estimation during anti-lock braking is considered. A novel nonlinear observer based on a vehicle dynamics model and a simplified Pacejka tire model is introduced in order to provide estimates of longitudinal and lateral vehicle velocities and the tire-road friction coefficient for vehicle safety control systems, specifically anti-lock braking control. The approach differs from previous work on vehicle state estimation in two main respects. The first is the introduction of a switched nonlinear observer in order to deal with the fact that in some driving situations the information provided by the sensor is not sufficient to carry out state estimation (i.e., not all states are observable). This is shown through an observability analysis. The second contribution is the introduction of tire-road friction estimation depending on vehicle longitudinal motion. Stability properties of the observer are analyzed using a Lyapunov function based method. Practical applicability of the proposed nonlinear observer is shown by means of experimental results.     

基于路面识别实时控制车轮滑移率的ABS系统

汽车防抱死制动系统(ABS)是一种很重要的汽车主动安全技术。并针对路面具体情况,对车辆防抱制动系统的滑移率实时控制进行研究。该文在MATLAB/Simulink仿真环境下,建立车辆动力学模型,实现了对路面状况识别,同时对基于滑移率控制的防抱制动系统的计算机仿真。仿真结果表明,该系统能真实地反映汽车ABS系统的实际工作过程,达到了满意的控制效果。     

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

A fuzzy logic controller for an ABS braking system

Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy, d) On rough roads, the tire slip ratio varies widely and rapidly due to tire bouncing, and e) The braking system contains transportation delays which limit the control system bandwidth. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal, based on current and past readings of the slip ratio and brake pressure. The controller detects wheel blockage immediately and avoids excessive slipping. The ABS system performance is examined on a quarter vehicle model with nonlinear elastic suspension. The parallelity of the fuzzy logic evaluation process ensures rapid computation of the controller output signal, requiring less time and fewer computation steps than controllers with adaptive identification. The robustness of the braking system is investigated on rough roads and in the presence of large measurement noise. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance on various road types and under rapidly changing road conditions     

基于轮胎/路面磨擦状况估计的轮胎故障观测器设计

轮胎故障是造成交通事故的主要原因之一.但是目前大多数轮胎故障监测方法由于需 要使用各种复杂的传感器因此制造代价高昂且不可靠.为此,提出了一种新型实用的轮眙故障观 测器.基于考虑外界不确定干扰的新型动态轮胎/路面磨擦模型,该观测器仅仅使用汽车驱动力 及轮胎转速数据,跟踪估计轮胎/路面磨擦系数的变化,并通过对磨擦状况的分析对轮胎状态做 出合理的判断.由于转速传感器是汽车防滑刹车控制系统(ABS)的基本组成部分,因此该观测器 可与ABS结合工作,低成本的实现轮胎故障监测.     

Intelligent exponential sliding-mode control with uncertainty estimator for antilock braking systems

The purpose of the antilock braking system (ABS) is to regulate the wheel longitudinal slip at its optimum point in order to generate the maximum braking force; however, the vehicle braking dynamic is highly nonlinear. To relax the requirement of detailed system dynamics, this paper proposes an intelligent exponential sliding-mode control (IESMC) system for an ABS. A functional recurrent fuzzy neural network (FRFNN) uncertainty estimator is designed to approximate the unknown nonlinear term of ABS dynamics, and the parameter adaptation laws are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the stable control performance. Since the outputs of the functional expansion unit are used as the output weights of the FRFNN uncertainty estimator, the FRFNN can effectively capture the input–output dynamic mapping. In addition, a nonlinear reaching law, which contains an exponential term of sliding surface to smoothly adapt the variations of sliding surface, is designed to reduce the level of the chattering phenomenon. Finally, the simulation results demonstrate that the proposed IESMC system can achieve robustness slip tracking performance in different road conditions.     

电动汽车低速电气制动防抱死功能的研究

研究电动汽车制动防抱死功能优化问题,电动汽车在冰雪路面上进行纯再生制动时,驱动轮极有可能抱死,从而造成车辆操纵稳定性下降。为解决上述问题,根据驱动电机在基速以下的调速特性,提出了调压调速型电气ABS模型。以单轮电动汽车模型为研究对象,设计了以车轮滑移率为控制目标的滑动模式防滑控制器。在Matlab/Simulink环境下建立了电气ABS仿真模型,仿真结果表明所建模型具有良好的稳定性;同时表明制动过程由初期的反接制动、为主体的中期再生制动及后期的反接制动构成;且制动精度明显高于传统ABS。研究结果对电动汽车再生制动系统的设计具有一定的参考价值。     

基于非线性干扰观测器的飞机全电刹车系统滑模控制设计

飞机防滑刹车具有典型的强非线性、强耦合和参数时变等特点, 并且跑道环境的干扰容易对飞机的地面滑跑性能造成不利影响. 本文提出了一种基于非线性干扰观测器的飞机全电防滑刹车系统滑模控制设计方法. 首先, 考虑了实际刹车不确定性干扰条件下的防滑刹车动力学建模问题, 通过对高阶非线性刹车系统进行反馈线性化处理, 简化了基于严格反馈的模型. 其次, 基于对主轮打滑原因的深入分析, 设计了非线性干扰观测器对干扰进行在线估计, 并在控制律设计中引入补偿部分. 通过构造递归结构的快速终端滑模控制器来跟踪实时变化的最佳滑移率并建立稳定性条件, 实现了飞机全电防滑刹车系统的有限时间快速稳定并有效抑制了主轮锁定打滑. 通过在不同跑道状态下进行模拟仿真, 验证了本文提出的飞机防滑刹车控制策略可以有效地提高刹车效率.     

Non-linear velocity observer for vehicles with tyre–road friction estimation

A non-linear observer is proposed for the estimation of the longitudinal and lateral velocities of automotive vehicles due to highly non-linear friction. To take the unknown time-varying road conditions into account, a real-time tyre–road friction estimation algorithm is provided for adaptation to changes of different road adhesion characteristics. Besides, the coupling effects of the longitudinal and lateral forces are fully exploited to design the non-linear observer based on the longitudinal and lateral acceleration measurements. The observer is computationally efficient and is based on a standard sensor configuration commonly available in modern cars. The uniform global asymptotical stability of the adaptive observer is guaranteed under a certain persistency-of-excitation condition. Moreover, a stronger local stability result can also be obtained, i.e. uniform local exponential stability. The performance of the observer is compared with that of existing approaches under different manoeuvres and road conditions.     

Existence,stability and robustness analysis of limit cycles in hybrid anti-lock braking systems

We investigate the stability and robustness properties of anti-lock braking systems (ABS) based on actuators with on/off dynamics. Namely, we propose a hybrid ABS controller which gives rise to an asymptotically stable limit cycle on the wheel slip. The proposed approach allows to derive exact information on the maximum allowable uncertainty in the measured variables which guarantee the cycle stability. Moreover, a structural stability analysis is performed with respect to different road conditions and to the actuator rate limit.     

Sliding‐Mode Velocity Control of a Two‐Wheeled Self‐Balancing Vehicle

Underactuated vehicles are those in which the number of control inputs is less than the degrees of freedom to be controlled. Using actuated wheels, velocity control of the two‐wheeled self‐balancing vehicle drives the vehicle at a desired speed and balances the body of the vehicle. First, we investigate the effects of friction on the wheel and derive the hybrid model of rolling and slipping. Second, we propose a nonlinear sliding mode velocity control scheme for the pure rolling model of the two‐wheeled vehicle. We present the design of the corresponding sliding surfaces and internal dynamics of the two‐wheeled vehicle. Our stability analysis reveals that the proposed sliding mode method can guarantee the asymptotic stability of the error dynamics for velocity control of the underactuated vehicle. Compared to linear optimal control, our numerical simulations demonstrate that the proposed sliding mode schemes can effectively control the velocity under the circumstances of parametric variations, emergency braking, and rapid acceleration in slippery road conditions. The proposed velocity control and the simulation improve our understanding on designing velocity control of the two‐wheeled self‐balancing vehicle.     

Structured estimation of tire forces and the ground slope using SM observers

In agricultural context, the principal cause of serious accidents for all-terrain vehicles(ATVs) is rollover. The most important parameters related to this risk is the ground slope. In this paper, we propose a structured observer to estimate the system states and the longitudinal tire forces using only wheel angular velocities measurement. The robust estimation is based on a second order sliding mode observer. This estimation is then used to build up a ground slope estimation. The algorithm is composed by two cascaded estimators. This structured estimation is then applied to the model of an agricultural vehicle G7(GregoireTM) integrated in the driving simulation environment SCANeRTM-Studio.     

Tire–road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation

A sequential tire cornering stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire cornering stiffness coefficient and TRFC. The proposed tire cornering stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.     

电动汽车电-液并联ABS制动系统能量回收研究

为了提高续驶里程,针对某款越野车改装的电动汽车制动系统,提出一种基于ABS的电-液并联制动系统。此系统采用固定比例的前后轴制动力分配方式,结合恒定充电电流与最大回馈功率复合的再生制动控制方式,以基于滑移率的PID控制ABS系统来调节电、液制动力比例,在确保制动安全可靠的同时实现制动能量回收。根据上述理论建立数学模型,并利用AMESim和Simulink进行联合仿真,在3种典型工况下分析制动性能和能量回收效率。结果表明：基于ABS的电-液并联制动系统综合制动性能良好,且3种工况下的一次制动最小能量回收效率分别达到28%、28%和11%。