Fuzzy Logic Traction Controllers and their Effect on Longitudinal Vehicle Platoon Systems

This paper presents two fuzzy logic traction controllers and investigates their effect on longitudinal platoon systems. A fuzzy logic approach is appealing for traction control because of the nonlinearity and time-varying uncertainty involved in traction control systems

The fuzzy logic traction controllers we present regulate brake torque to control wheel slip, which is the normalized difference between wheel and vehicle speed. One fuzzy controller estimates the peak slip corresponding to the maximum tire-road adhesion coefficient and regulates wheel slip at the peak slip. The controller is attractive because of its ability to maximize acceleration and deceleration regardless of road condition. However, we find through simulations the controller's performance degrades in the presence of time-varying uncertainties. The other fuzzy logic controller regulates wheel slip at any desired value. Through simulations we find the controller robust against changing road conditions and uncertainties. The target slip is predetermined and not necessarily the peak slip for all road conditions. If the target slip is set low, stable acceleration and deceleration is guaranteed, regardless of road condition

We also study the effect of traction control on longitudinal vehicle platoon systems using simulations. The simulations include acceleration and deceleration maneuvers on an icy road. The results indicate traction control may substantially improve longitudinal platoon performance, especially when icy road conditions exist.     

PID plus fuzzy logic method for torque control in traction control system

A Traction Control System (TCS) is used to control the driving force of an engine to prevent excessive slip when a vehicle starts suddenly or accelerates. The torque control strategy determines the driving performance of the vehicle under various drive-slip conditions. This paper presents a new torque control method for various drive-slip conditions involving abrupt changes in the road friction. This method is based on a PID plus fuzzy logic controller for driving torque regulation, which consists of a PID controller and a fuzzy logic controller. The PID controller is the fundamental component that calculates the elementary torque for traction control. In addition, the fuzzy logic controller is the compensating component that compensates for the abrupt change in the road friction. The simulation results and the experimental vehicle tests have validated that the proposed controller is effective and robust. Compared with conventional PID controllers, the driving performance under the proposed controller is greatly improved.     

并联式混合动力电动汽车模糊逻辑控制策略的设计与仿真

在兼顾发动机效率和排放前提下,考虑电池充放电平衡,提出了一种模糊逻辑控制策略.将其嵌入仿真软件ADVISOR中,并在不同道路循环和不同控制策略中进行仿真计算.结果表明,模糊逻辑控制有较好的经济性、鲁棒性,能合理分配发动机和电动机转矩,并保持电池SOC较小的变化范围.     

基于滑移率和减速度的ABS模糊控制仿真研究

在ABS逻辑门限值控制方法的基础上,通过分析道路试验数据,利用M atlab的模糊工具箱建立了模糊控制系统,采用7自由度整车模型在S imu link中进行仿真计算。仿真结果表明,基于滑移率和减速度的ABS模糊控制比逻辑门限值方法具有更好的自适应性,并可减少道路试验的工作量。     

智能车灯的模糊控制器设计

针对传统汽车照明系统只能用手动控制,在路况复杂或者环境恶劣的情况下不能及时有效地提供良好照明的问题,文章介绍了一种自适应车灯前照明控制系统（AFS）并对其控制方法进行了研究。运用模糊控制理论并使用MATLAB／SIMUuNK软件中的FUZZY模块,对水平和垂直方向上的车灯偏转设计了模糊控制器。指出AFS应用前景广阔,模糊控制技术可以为将来智能车灯的发展提供参考。     

模糊逻辑在汽车电子控制中的应用

本文简要介绍了汽车电子控制和模糊逻辑控制的特点，综述了模糊逻辑在汽车发动机控制，自动变速器控制，ＡＰＳ悬架控制，故障诊断，巡航控制等方面的应用。     

汽车驾驶员车速控制模式的模拟研究

系统地对汽车驾驶员在一定行车环境中的安全性认知与车速控制的决策、推理过程进行了定量研究,通过进行一系列勘测、测试和心理评价试验,应用模糊集合、模糊统计试验、模糊控制和模糊逻辑推理等分析方法,建立了描述汽车驾驶员在既定道路条件下行车时基于安全性考量的逻辑推理规则和车速控制模型,最后进行了相应的实测验证。模拟预测结果与实测结果吻合较好,证明了研究所采用方法和建立模型的正确性。     

基于路面自动识别的ABS自适应神经模糊控制器仿真研究

有效、快速的道路状况自动识别对于提高ABS性能具有重要意义。通过仿真试验分析,提出了一种比传统方法更快更高效的路面识别方法,并设计了以滑移率为控制目标的ABS模糊神经网络控制器。结合车辆模型熏对单一附着系数路面和变附着系数路面进行了ABS制动模拟试验。结果表明熏基于路面自动识别ABS模糊控制系统能快速、准确判断出路面状况的变化熏自动调整、优化控制器控制参数熏使车辆获得最大地面制动力,与传统利用车身加速度进行路面识别的逻辑门限控制器相比,该控制器反应更灵敏,控制更精确。     

Novel coordinated algorithm for Traction Control System on split friction and slope road

A Traction Control System (TCS) is used to avoid excessive wheel-slip via adjusting active brake pressure and engine torque when vehicle starts fiercely. The split friction and slope of the road are complicated conditions for TCS. Once operated under these conditions, the traction control performance of the vehicle might be deteriorated and the vehicle might lack drive capability or lose lateral stability, if the regulated active brake pressure and engine torque can’t match up promptly and effectively. In order to solve this problem, a novel coordinated algorithm for TCS is brought forward. Firstly, two brake controllers, including a basic controller based on the friction difference between the two drive wheels for compensating this difference and a fuzzy logic controller for assisting the engine torque controller to adjust wheel-slip, are presented for brake control together. And then two engine torque controllers, containing a basic PID controller for wheel-slip control and a fuzzy logic controller for compensating torque needed by the road slope, are built for engine torque control together. Due to the simultaneous and accurate coordination of the two regulated variables the controlled vehicle can start smoothly. The vehicle test and simulation results on various road conditions have testified that the proposed method is effective and robust.     

半主动悬架模糊控制仿真

为缓和路面传递给车身的冲击,改善汽车行驶的平顺性和操作稳定性,文章建立了二自由度1／4车体半主动悬架非线性动力学模型,利用MATLAB模糊逻辑控制工具箱设计半主动悬架的模糊控制器,通过运用MATLAB／SIMULINK,对悬架系统进行了仿真分析。结果表明,该控制方法能有效地降低车身垂直加速度、悬架的动挠度和车轮动载荷,提高了汽车的平顺性和操纵稳定性。     

基于模糊PID控制的汽车道路模拟系统研究与仿真

根据模糊控制理论,以汽车道路模拟系统为研究对象,将模糊控制与常规的PID控制相结合,设计出一套模糊PID控制系统。并对正弦波、方波以及随机波进行仿真再现,仿真结果表明,该模糊PID控制器比常规PID控制器具有更高的控制精度和更好的动态性能。     

越野汽车挡位决策的自适应模糊控制

为提高装备自动变速器的越野汽车换挡控制系统对复杂路况的自适应能力,在基本模糊控制模块基础上,建立了具有两级递阶结构的越野车自适应模糊换挡控制系统.基本模糊控制模块将油门开度、车速和加速度3参数进行模糊化和模糊推理,实现挡位决策;自适应控制模块按照检测的车速和加速度对直线行驶阻力和附着力进行在线辨识,并由此进行量化因子的自调整.仿真结果表明所设计的模糊控制系统具有良好的自适应能力.     

Design of Regenerative Anti-Lock Braking System Controller for 4 In-Wheel-Motor Drive Electric Vehicle with Road Surface Estimation

This paper presents a regenerative anti-lock braking system control method with road detection capability. The aim of the proposed methodology is to improve electric vehicle safety and energy economy during braking maneuvers. Vehicle body longitudinal deceleration is used to estimate a road surface. Based on the estimation results, the controller generates an appropriate braking torque to keep an optimal for various road surfaces wheel slip and to regenerate for a given motor the maximum possible amount of energy during vehicle deceleration. A fuzzy logic controller is applied to fulfill the task. The control method is tested on a four in-wheel-motor drive sport utility electric vehicle model. The model is constructed and parametrized according to the specifications provided by the vehicle manufacturer. The simulation results conducted on different road surfaces, including dry, wet and icy, are introduced.     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

A novel fuzzy logic correctional algorithm for traction control systems on uneven low-friction road conditions

The traction control system (TCS) might prevent excessive skid of the driving wheels so as to enhance the driving performance and direction stability of the vehicle. But if driven on an uneven low-friction road, the vehicle body often vibrates severely due to the drastic fluctuations of driving wheels, and then the vehicle comfort might be reduced greatly. The vibrations could be hardly removed with traditional drive-slip control logic of the TCS. In this paper, a novel fuzzy logic controller has been brought forward, in which the vibration signals of the driving wheels are adopted as new controlled variables, and then the engine torque and the active brake pressure might be coordinately re-adjusted besides the basic logic of a traditional TCS. In the proposed controller, an adjustable engine torque and pressure compensation loop are adopted to constrain the drastic vehicle vibration. Thus, the wheel driving slips and the vibration degrees might be adjusted synchronously and effectively. The simulation results and the real vehicle tests validated that the proposed algorithm is effective and adaptable for a complicated uneven low-friction road.     

Integrated control of brake pressure and rear-wheel steering to improve lateral stability with fuzzy logic

This study introduces an integrated dynamic control with steering (IDCS) system to improve vehicle handling and stability under severe driving conditions. It integrates an active rear-wheel steering control system and a direct yawmoment control system with fuzzy logic. Direct yaw-moment control is achieved by modifying the optimal slip of the front outer wheel. An 8-degree-of-freedom vehicle model was used to evaluate the proposed IDCS for various road conditions and driving inputs. The results show that the yaw rate tracked the reference yaw rate and that the body slip angle was reduced when the IDCS was employed, thereby increasing the controllability and stability of the vehicle on slippery roads. The IDCS system reduced the deviation from the center line for a vehicle running on a split m road.     

汽车雷达多目标跟踪的模糊数据关联

介绍了一种量测(新测目标)到目标(已知目标)之间的模糊数据关联方法，将模糊聚类均值方法和决策逻辑方法相结合，利用Mahalanobis距离代替聚类运算中的欧氏距离，使量测与目标预测值之间的相似性度量更准确，应用决策逻辑确定量测与目标预测值的关联关系。仿真表明这种方法简单，在杂波环境下，有较高的跟踪精度，这种方法可以用于道路条件下，基于汽车雷达的多目标的可靠跟踪。     

并联混合动力汽车模糊逻辑控制策略的设计

利用模糊逻辑控制技术,设计了并联混合动力汽车的模糊逻辑扭矩控制策略。选取了控制器的输入、输出变量,构建了有25条规则的模糊推理器。在3种不同的循环工况下,分别对二值逻辑策略和模糊逻辑策略进行了仿真试验,结果显示,所设计的模糊逻辑控制策略能够很好地控制发动机工作,且具有很好的自适应能力和鲁棒性。     

车辆离合器起步阶段模糊控制的研究

利用模糊控制理论和方法，基于驾驶员经验，编制了控制软件；采用Motorola MC68376微处理器和霍尔效应零速传感器，解决了AMT离合器在低速时转速信号的及时准确感应和及时处理的问题。试验结果表明，新的控制系统避免了起步冲击和不能很好适应驾驶员起步意网与路况的问题。