Control of Wheel Slip Ratio Using Sliding Mode Controller with Pulse Width Modulation

For the control of anti-lock brake system (ABS), a longitudinal four-wheel vehicle model with brake actuator is described and a sliding mode controller with pulse width modulation (PWM) method has been developed for passenger vehicles. In our research, we introduce actuator dynamics of solenoid-solenoid valve type in system equation and derive the sliding mode control input theoretically. We propose using PWM method to compensate for the discrete nature of actuator dynamics by duty control. The effectiveness of the proposed control algorithms was confirmed by vehicle test on an in-door test bench that was specially constructed for the purpose concerned.     

Design of Nonlinear Sliding Mode Controller with Pulse Width Modulation for Vehicular Slip Ratio Control

For the control of anti-lock brake system (ABS), a longitudinal four-wheel vehicle model with brake actuator is described and a sliding mode controller with pulse width modulation (PWM) method has been developed for passenger vehicles. In our research, we introduced actuator dynamics in the system equation and derived the equivalent control input theoretically. We propose using the PWM method to compensate for the discrete nature of actuator dynamics by duty control. Stability of the PWM controller for sliding mode control (SMC) was theoretically checked. The effectiveness of the proposed control algorithms was confirmed by vehicle tests on an In-door test bench that was specially constructed for the purpose concerned.     

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。     

Design of a hydraulic anti-lock braking modulator and an intelligent brake pressure controller for a light motorcycle

The object of this paper is to design a new hydraulic modulator and an intelligent sliding mode pulse width modulation (PWM) brake pressure controller for an anti-lock braking system, for application to light motorcycles. The paper presents a design principle and a mathematical analysis of the hydraulic anti-lock braking modulator. The intelligent sliding mode PWM brake pressure controller based on vehicle acceleration is designed and tested. A three-phase pavement experiment and a rear brake influence test are undertaken to verify the performance of the controller and the modulator. A light motorcycle is built for the real vehicle anti-lock braking experiments. The experimental results show that both the intelligent controller and the hydraulic modulator designed in the study perform well in the anti-lock braking operation.     

Heavy-duty vehicle modelling and longitudinal control

This paper addresses modelling, longitudinal control design and implementation for heavy-duty vehicles (HDVs). The challenging problems here are: (a) an HDV is mass dominant with low power to mass ratio; (b) They possess large actuator delay and actuator saturation. To reduce model mismatch, it is necessary to obtain a nonlinear model which is as simple as the control design method can handle and as complicated as necessary to capture the intrinsic vehicle dynamics. A second order nonlinear vehicle body dynamical model is adopted, which is feedback linearizable. Beside the vehicle dynamics, other main dynamical components along the power-train and drive-train are also modelled, which include turbocharged diesel engine, torque converter, transmission, transmission retarder, pneumatic brake and tyre. The braking system is the most challenging part for control design, which contains three parts: Jake (engine compression) brake, air brake and transmission retarder. The modelling for each is provided. The use of engine braking effect is new complementary to Jake (compression) brake for longitudinal control, which is united with Jake brake in modelling. The control structure can be divided into upper level and lower level. Upper level control uses sliding mode control to generate the desired torque from the desired vehicle acceleration. Lower level control is divided into two branches: (a) engine control: from positive desired torque to desired fuel rate (engine control) using a static engine mapping which basically captures the intrinsic dynamic performance of the turbo-charged diesel engine; (b) brake control: from desired negative torque to generate Jake brake cylinder number to be activated and ON/OFF time periods, applied pneumatic brake pressure and applied voltage of transmission retarder. Test results are also reported.     

Heavy-duty vehicle modelling and longitudinal control

This paper addresses modelling, longitudinal control design and implementation for heavy-duty vehicles (HDVs). The challenging problems here are: (a) an HDV is mass dominant with low power to mass ratio; (b) They possess large actuator delay and actuator saturation. To reduce model mismatch, it is necessary to obtain a nonlinear model which is as simple as the control design method can handle and as complicated as necessary to capture the intrinsic vehicle dynamics. A second order nonlinear vehicle body dynamical model is adopted, which is feedback linearizable. Beside the vehicle dynamics, other main dynamical components along the power-train and drive-train are also modelled, which include turbocharged diesel engine, torque converter, transmission, transmission retarder, pneumatic brake and tyre. The braking system is the most challenging part for control design, which contains three parts: Jake (engine compression) brake, air brake and transmission retarder. The modelling for each is provided. The use of engine braking effect is new complementary to Jake (compression) brake for longitudinal control, which is united with Jake brake in modelling. The control structure can be divided into upper level and lower level. Upper level control uses sliding mode control to generate the desired torque from the desired vehicle acceleration. Lower level control is divided into two branches: (a) engine control: from positive desired torque to desired fuel rate (engine control) using a static engine mapping which basically captures the intrinsic dynamic performance of the turbo-charged diesel engine; (b) brake control: from desired negative torque to generate Jake brake cylinder number to be activated and ON/OFF time periods, applied pneumatic brake pressure and applied voltage of transmission retarder. Test results are also reported.     

Fault-tolerant braking control with integerated EMBs and regenerative in-wheel motors

This paper presents a fault-tolerant brake torque controller for four-wheel-distributed braking systems with in-wheel motors and Electro-Mechanical Brakes (EMB). Mechanical and electrical faults can degrade the performance of the EMB actuators and, thus, their effects need to be compensated in vehicle dynamics level. In this study, the faults are identified as performance degradation and expressed by the gains of each actuator. Assuming the brake force distribution and the regenerative braking ratios, the over-actuated braking system is simplified into a two-input system. A sliding mode controller is designed to track the driver’s braking and steering commands, even if there exist faults in EMBs. In addition, adaptive schemes are constructed to achieve the fault-tolerant control in braking. The proposed controller and strategies are verified in the EMB HILS (Hardware-in-loop-simulation) unit for various conditions.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

基于带切换增益模糊调节的滑模控制算法的车辆电液制动系统

针对汽车线控电液制动系统建立了单轮车辆模型,研制了一种新的状态观测器对车速进行估算,试验结果表明该方法正确实用.采用切换增益模糊调节的滑模控制算法对非线性时变的车辆实施基于最佳滑移率的制动控制,在Matlab/Simulink中的仿真结果和验证试验都表明在汽车线控制动系统应用该算法是可行、有效的,在该算法的控制下汽车可获得比一般滑模控制更好的制动性能.     

基于扰动观测的客车ESC自适应神经网络滑模控制

为了提高客车电子稳定性控制系统（ESC）的控制精度,针对实际车辆系统建模中存在各种非线性扰动项以及传统滑模控制（Sliding Mode Control,SMC）中抖振较大的问题,提出一种自适应神经网络滑模控制算法。基于2自由度车辆模型,首先设计一个二阶滑模（Second-order Sliding Mode,SOSM）估计器对车辆的质心侧偏角进行估计,然后利用径向基（Radial Basis Function,RBF）神经网络对车辆系统建模中的各种非线性扰动项进行实时估计,并进行Lyapunov稳定性证明,RBF神经网络估计车辆系统建模的各种非线性扰动项可以有效减小滑模控制符号项的系数,从而减小滑模抖振水平。为了更进一步优化传统滑模控制的参数调节过程,减小滑模抖振并提高系统控制精度,再次利用RBF神经网络对传统滑模控制中的关键参数进行自适应调节。最后为了验证算法的有效性,搭建客车电控气压制动系统硬件在环试验台,在硬件在环试验台上对算法的有效性和精度进行试验验证。研究结果表明：客车ESC在自适应神经网络滑模算法的控制下,横摆角速度和质心侧偏角能够较好地跟随上理想的横摆角速度和理想质心侧偏角,横摆角速度和质心侧偏角的跟随误差降低;利用RBF神经网络估计客车建模中的各种非线性扰动项和利用RBF神经网络自适应调节传统滑模控制的关键参数,可以有效提高客车ESC的控制精度。     

基于视觉识别的线控制动压力滑模控制

制动安全是车辆主动安全的关键技术之一.制动决策和执行器控制是影响线控制动系统性能的两个主要因素.路面自适应性和控制器鲁棒性分别对制动决策和执行器控制有着重要影响,制约着线控制动系统的发展.本文中以一种液压调控的线控制动系统为基础,针对路面自适应性和控制器鲁棒性问题,提出一种双层结构的制动系统控制器,上层采用计算机视觉的...     

线控双电机转向系统滑模同步控制及其硬件在环仿真

为了满足高等级自动驾驶转向执行机构的高安全性需求，研究一种采用冗余双电机转向执行机构的线控转向系统，针对双电机在转角伺服控制过程中存在的不同步问题，提出一种基于滑模控制的同步控制策略。首先，对采用冗余双电机转向执行机构的线控转向系统进行结构原理的分析，建立线控系统转向执行机构模型和车辆二自由度模型；然后，为实现转向执行机构的转角伺服控制，在位置、速度、电流的三闭环控制策略的基础上设计速度同步控制器。为解决2个转向执行电机运行过程中存在的速度不同步问题，采用滑模控制方法，将2个电机的转速差值作为控制器的输入量，得到双电机电流的补偿量，并将其叠加至双电机的目标电流中。同时，将上述控制策略与传统PID控制进行对比仿真试验，验证了基于滑模同步控制的线控双电机执行器能够更好地协调双电机的转速，实现双电机同步运行。最后，搭建线控转向硬件在环试验台，对所设计的控制策略的有效性进行验证。结果表明：所设计的双电机线控转向系统滑模同步控制策略能够在实现转角伺服控制的同时，减少双电机的速度不同步现象，保证线控转向系统转角伺服的同步性能。     

分布式驱动电动汽车回馈制动失效的液压补偿控制

分布式驱动电动汽车各驱动轮转速和转矩可以单独精确控制,便于实现整车动力学控制和制动能量回馈,从而提升车辆的主动安全性和行驶经济性。但车辆在回馈制动过程中,一旦1台电机突发故障,其他电机产生的制动力矩将对整车形成附加横摆力矩,从而造成车辆失稳,此时虽可通过截断异侧对应电机制动力矩输出来保证行驶方向,但会使车辆制动力大幅衰减或丧失,同样不利于行车安全。为了解决此问题,提出并验证一种基于电动助力液压制动系统的制动压力补偿控制方法,力图有效保证整车制动安全性。以轮毂电机驱动汽车为例,首先建立了整车动力学模型以及轮毂电机模型,通过仿真验证了回馈制动失效的整车失稳特性以及电机转矩截断控制的不足;然后,建立了电动助力液压制动系统模型,并通过原理样机的台架试验验证了模型的准确性;接着,基于滑模控制算法设计了制动压力补偿控制器,并在单侧电机再生制动失效后的转矩截断控制基础上完成了液压制动补偿控制效果仿真验证;最后,通过实车试验证明了所提控制方法的有效性和实用性。研究结果表明：在分布式驱动电动汽车单侧电机再生制动失效工况下,通过异侧电机转矩截断控制和制动系统的液压主动补偿,能够使车辆快速恢复稳定行驶并满足制动强度需求。     

基于混杂理论的电磁与摩擦集成制动方法

鉴于传统电子液压制动系统连续制动易产生"热衰退"现象，结构缺陷导致的制动响应慢，制动系统与电控系统衔接差等缺点，提出了一种基于混杂自动机模型的电磁与摩擦集成制动方法。首先分析集成制动器制动时的工作特点以及不同情况下对应的工作模式（纯电磁制动、纯摩擦制动以及集成制动），并确定3种制动模式的切换条件，通过逻辑门限算法将其实现。根据制动时车辆既具有连续运动状态又有离散状态的混杂特性，使用MATLAB/Stateflow建立基于制动模式切换系统的推广自动机模型，并根据制动模式切换控制策略，对3种制动模式切换进行试验，验证制动模式切换控制策略的合理性。最后选取车辆制动初速度为28 m·s^-1的直线制动工况，分别在高附着系数（0.85）以及低附着系数（0.3）的路面条件下，通过试验平台对控制算法和制动系统性能进行试验验证。研究结果表明：所提出的汽车混杂理论模型以及优化方法在在低附着系数（0.3）路面条件下，集成制动方法较传统液压制动系统缩短5.12%的制动距离，缩短制动时间0.3 s；在高附着系数（0.85）路面条件下，集成制动方法较传统液压制动系统缩短5.66%的制动距离，缩短制动时间0.2 s，能有效提高制动效能。     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

Direct tire force generation algorithm based on non-iterative nonlinear inverse tire model

The function of vehicle dynamics control system is adjusting the yaw moment, the longitudinal force and lateral force of a vehicle body through several chassis systems, such as brakes, steering and suspension. Individual systems such as ESC, AFS and 4WD can be used to achieve desired performance by controlling actuator variables. However, integrated chassis control systems that have multiple objectives may not simply achieve the desired performance by controlling the actuators directly. Usually those systems determine the required tire forces in an upper level controller and a lower level controller regulates the tire forces through the actuators. The tire force is controlled in a recursive way based on vehicle state measurement, which may not be sufficient for fast response. For immediate force tracking, we introduce a direct tire force generation method that uses a nonlinear inverse tire model, a pseudo-inverse model of vehicle dynamics and the relationship between longitudinal force and brake pressure.     

基于滑模自抗扰的电制动系统动态负载模拟

为精准模拟传动系弹性及齿隙作用下电制动系统非线性机械负载,提出了自适应模糊滑模自抗扰的测功机控制算法。首先,针对一款前驱电动汽车,建立融合感应电机模型的车辆及台架机电一体化模型,引入典型正常制动和防抱死制动控制作为测试对象。其次,构建扩张状态观测器估计台架系统未建模动态,以自适应模糊滑模控制测功机实时模拟高度非线性机械负载。最后,开展了制动控制策略台架测试的仿真研究。结果表明:提出的方法可精确模拟电制动系统动态负载,有效提高制动控制算法台架测试精度。     

Integrated control of ground vehicles dynamics via advanced terminal sliding mode control

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.     

An investigation of the effects of pneumatic actuator design on slip control for heavy vehicles

Progress in reducing actuator delays in pneumatic brake systems is opening the door for advanced anti-lock braking algorithms to be used on heavy goods vehicles. However, little has been published on slip controllers for air-braked heavy vehicles, or the effects of slow pneumatic actuation on their design and performance. This paper introduces a sliding mode slip controller for air-braked heavy vehicles. The effects of pneumatic actuator delays and flow rates on stopping performance and air (energy) consumption are presented through vehicle simulations. Finally, the simulations are validated with experiments using a hardware-in-the-loop rig. It is shown that for each wheel, pneumatic valves with delays smaller than 3 ms and orifice diameters around 8 mm provide the best performance.     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.