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.     

Estimation of road frictional force and wheel slip for effective antilock braking system (ABS) control

The introduction of electric braking via brake‐by‐wire systems in electric vehicles) has reduced the high transportation delays usually involved in conventional friction braking systems. This has facilitated the design of more efficient and advanced control schemes for antilock braking systems (ABSs). However, accurate estimation of the tire‐road friction coefficient, which cannot be measured directly, is required. This paper presents a review of existing estimation methods, focusing on sliding‐mode techniques, followed by the development of a novel friction estimation technique, which is used to design an efficient ABS control system. This is a novel slip‐based estimation method, which accommodates the coupling between the vehicle dynamics, wheel dynamics, and suspension dynamics in a cascaded structure. A higher‐order sliding‐mode observer–based scheme is designed, considering the nonlinear relationship between friction and slip. A first‐order sliding‐mode observer is also designed based on a purely linear relationship. A key feature of the proposed estimation schemes is the inclusion of road slope and the effective radius of the tire as an estimated state. These parameters impact significantly on the accuracy of slip and friction estimation. The performance of the proposed estimation schemes are validated and benchmarked against a Kalman filter (KF) by a series of simulation tests. It is demonstrated that the sliding‐mode observer paradigm is an important tool in developing the next generation ABS systems for electric vehicles.     

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     

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.     

Integrated vehicle control through the coordination of longitudinal/lateral and vertical dynamics controllers: Flatness and LPV/‐based design

This paper deals with global chassis control of automotive vehicles. It focuses on the coordination of suspension and steering/braking vehicle controllers based on the interaction between the vertical and lateral behaviors of the vehicle. It is shown that the lateral acceleration and resulting roll motion of the car generate load transfers that considerably affect vehicle stability. A control law is designed in hierarchical way to improve the overall dynamics of the vehicle and cope with coupled driving maneuvers like obstacle avoidance using steering control and stop‐and‐go control using braking or driving wheel torque. This global control strategy includes two types of controllers. The first one is the longitudinal/lateral nonlinear flatness controller. Based on an appropriate choice of flat outputs, the flatness proof of a 3 DOF two‐wheel nonlinear vehicle model is established. Then, the combined longitudinal and lateral vehicle control is designed using algebraic estimation techniques to provide an accurate estimation of the derivatives and filtering of the reference flat outputs. The second part of the proposed strategy consists of a linear parameter‐varying/ suspension controller. This controller uses lateral acceleration as a varying parameter to account for load transfers that directly affect the suspension system. The coordination between the vehicle vertical and lateral dynamics is highlighted in this study, and the linear parameter‐varying/ framework ensures a specific collaborative coordination between the suspension and the steering/braking controllers, to achieve the desired performance. Simulations on a complex full vehicle model have been validated using experimental data obtained on‐board a real Renault Mégane Coupé. Copyright © 2017 John Wiley & Sons, Ltd.     

An intelligent approach to the lateral forces usage in controlling the vehicle yaw rate

A direct yaw moment control system (DYC) is designed to improve the handling and stability of a four‐wheel‐drive electric vehicle. The main task of this paper is to use the lateral forces in the process of optimally controlling vehicle stability. This is performed by defining a variable optimum region for the slip ratio of each wheel. A hierarchical structure is selected to design the control system. The higher‐level control system controls the yaw rate of the vehicle based on the fuzzy logic technique. The lower‐level control system, installed in each wheel, maintains the slip ratio of the same wheel within an optimum region using the fuzzy logic technique. This optimum region for each wheel is continuously modified based on the impact of the lateral force on the generated control yaw moment and the friction coefficient of the road. Therefore, an algorithm for estimation of the friction coefficient is proposed. Computer simulations are carried out to investigate the effectiveness of the proposed method. This is accomplished by comparison of the results of control methods with a fixed slip ratio region and the results of the proposed method with a variable slip ratio region in some maneuvers. The robustness of the proposed controller against hard braking and noise contamination, as well as the effect of steering wheel angle amplitude, is verified. The simulation results show that the influence of the proposed method on enhancing vehicle performance is significant. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Design Of Anti‐Slip Controller For An Electric Vehicle With An Adhesion Status Analyzer Based On The Ev Simulator

The In this paper, a simulator of a one‐wheel Electric Vehicle system is designed for testing an anti‐slip controller using the Motor‐Generator system. The drive motor of the M‐G system is used to simulate the drive wheel of the Electric Vehicle, and the load motor is used to simulate the load force of the chassis. In the driving process, the torque of the load motor is changed according to the drive force of the chassis that is calculated by the program. So it can simulate the dynamic process of the tire‐road system. Based on this simulator system, an anti‐slip controller based on an Adhesion Status Analyzer is proposed. Information about the wheel speed is acquired by using a Back EMF Observer. A load torque disturbance observer is designed to stabilize the acceleration of the wheels. The Adhesion Status Analyzer is used to generate safe acceleration commands for the anti‐slip controller. When a slip occurs, the anti‐slip controller will decrease the torque quickly, and at the same time, by estimating the dynamic status of adhesion, the Adhesion Status Analyzer will restrain the acceleration command within a safe area. The effectiveness of the proposed approach is verified by using the EV slip simulator.     

基于滑模变结构的飞机防滑刹车控制器设计

以飞机全电刹车为研究背景,采用滑模变结构控制策略,设计刹车防滑控制策略,解决传统刹车效率低、机轮深度打滑、低速刹车性能差等问题.在控制策略中,以最佳滑移率为目标函数,设计滑模面,实现刹车防滑控制.由于滑模控制的强鲁棒性,可有效提高系统的抗干扰能力.仿真结果可知,滑移率控制在最佳滑移率附近,刹车效率高,可消除机轮深度打滑现象,防滑效果优良.     

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.     

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.     

低附着路面的弯道制动控制策略研究

为了解决车辆在低附着弯道路面制动中载荷转移造成的汽车失稳问题,建立7自由度整车模型。通过分析整车弯道制动过程的动态特性,推导出制动力与滑移率的关系,提出了纠正转向中车辆失稳的措施,设计了以滑移率为主的门限值控制方法。仿真验证了该方法能够有效提高制动稳定性。     

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。     

Intelligent Adaptive Motion Control Using Fuzzy Basis Function Networks for Electric Unicycle

This paper presents two intelligent adaptive controllers, called self‐balancing and speed controllers, for self‐balancing and motion control, respectively, of an electric unicycle using fuzzy basis function networks (FBFN), which are employed to approximate model uncertainties and unknown friction between the wheel and the terrain surface. Both controllers are established based on the linearized model of the vehicle whose model uncertainties and parameter variations are caused by different riders and terrain. An adaptive backstepping controller together with online learning FBFN and sensing information of the rider's body inclination then is presented to achieve self‐balancing motion control. By adding an electronic throttle as the input device of speed commands, a decoupling sliding‐mode controller with online learning FBFN is proposed to accomplish self‐balancing and speed control. The performance and merit of the two proposed control methods are exemplified by conducting four simulations and three experiments on a laboratory‐built electric unicycle.     

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.     

Controller design for vehicle stability enhancement

A Vehicle Dynamics Control (VDC) system is developed for tracking desired vehicle behavior. The cascade structure of control system consists of yaw moment major controller and wheel slip minor controller. The Linear Quadratic Regulator (LQR) theory is exploited for yaw moment controller and the sliding mode theory is applied for wheel slip controller design. The use of yaw moment control was investigated by regulating the wheel slip ratio for improving handling and stability of vehicle. The performance of the control system is evaluated under various emergency maneuvers and road conditions through pure computer simulations and Hardware In-the-Loop Simulation (HILS) system. The results indicate the proposed system can significantly improve vehicle stability for active safety.     

Chattering‐free sliding mode control for a class of nonlinear mechanical systems

Second‐order sliding mode control (2‐smc) and dynamic sliding mode control (dsmc) eliminate the disturbing characteristic of chattering in static sliding mode control under the assumption that the derivative of the sliding surface is available or complex inequalities at the acceleration level can be constructed. In this paper, passivity‐based adaptive and non‐adaptive chattering‐free sliding mode controllers are proposed assuming that the upper bound of the norm of the derivative of the sliding surface is available, a weaker and easy to implement assumption in comparison to those of 2‐smc and dsmc. The closed‐loop system accounts explicitly for the invariance condition without reaching phase, and therefore for a desired transient response with global exponential convergence of tracking errors. Preliminary experiments are presented. Copyright © 2001 John Wiley & Sons, Ltd.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

Switched Second‐Order Sliding Mode Control with Partial Information: Theory and Application

This paper proposes a novel switched second order sliding mode (S‐SOSM) control strategy in a partial information setting, i.e., when only the sliding variable is accessible for measurements. Such a control approach allows one to deal with systems characterised by different levels of uncertainties associated with different regions of the state space and to accommodate different control objectives in the different regions by switching among appropriate SOSM controllers. The proposed approach is shown to ensure global finite‐time convergence to the origin of the closed‐loop system trajectory. The braking control of two‐wheeled vehicles is considered as a case‐study to test the controller performance.     

电动汽车TCS滑模控制器设计

针对电动汽车在冰雪低附着极端工况极易出现的驱动轮过度滑转问题,以电动汽车驱动电机转矩为控制变量,设计了一种电动汽车驱动防滑防牵引力控制系统(Traction control system,TCS)滑模控制器,控制器通过调节驱动电机转矩,将滑转率控制在目标值附近,使汽车持续获得最大路面附着,防止车轮过度滑转,对应用滑模控制出现的抖振问题,设计了一种改进的指数型趋近律,用以削弱系统抖振。仿真结果表明,设计的TCS滑模控制器通过控制驱动电机转矩能将汽车的滑转率控制在目标值附近,使得汽车持续获得最大的路面附着,充分抑制汽车打滑,提高了汽车行驶稳定性,在整个控制过程中驱动电机转矩和状态变量收敛快速且十分平滑,抖振削弱效果良好。     

Interior‐Point Method to Optimize Tire Force Allocation in 4‐Wheeled Vehicles Using High‐Level Sliding Mode Control with Adaptive Gain

Nonlinear vehicle control allocation is achieved by distributing the control task to tire forces with nonlinear saturation constraints. The overall vehicle control is accomplished by developing a hierarchical scheme. First, a high‐level sliding mode control with adaptive gain is considered to obtain the body force/moment for stable vehicle motion. The proposed controller only requires online adaptation of control gains without acquiring the knowledge of upper‐bounds on system uncertainties. Then, optimal distribution of tire forces (ODF) with nonlinear saturation constraints is considered. The high‐level control objectives are mapped to individual tire forces by formulating a nonlinear optimization problem. The interior‐point (IP) method is adopted for a nonlinear programming task at each time step. Evaluation of the overall system is accomplished by simulation testing with a nine‐degrees‐of‐freedom vehicle nonlinear model. Comparison with a well‐recognized control system shows the effect of saturation constrained ODF (SCODF) on improving vehicle handling and stability.