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.     

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.     

Predictive control of a vehicle trajectory using a coupled vector with vehicle velocity and sideslip angle

In this paper, a predictive algorithm for vehicle trajectory control using the vehicle velocity and sideslip angle is proposed. Since the driving state of a vehicle generates nonholonomic constraint equations, it is difficult to control the trajectory with a conventional control algorithm. Furthermore, control vectors such as vehicle velocity and sideslip angle are coupled together; hence, a separate control for each variable is not suitable. In this study, a coupled control vector that combines the velocity and sideslip angle is proposed for the predictive control of vehicle trajectory. Since the coupled control vector is derived from the status of the vehicle’s motion, it is easy to generate a feedback control vector for the predictive controller. The coupled vector cannot be directly used as input to the vehicle systems; therefore, the vehicle input vector should be calculated from the control vector using a nonlinear function. Since nonlinear functions are not inserted in the control loop, they are calculated by the controller. Therefore, this method does not require a linearization process in the control logic, which enhances the stability and accuracy of the predictive controller.     

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.     

基于模糊逻辑控制策略的混合动力汽车仿真研究

以燃油经济性和排放性能为主要控制目标,提出一种基于模糊逻辑的能量分配控制策略,应用ADVISOR仿真软件,对制定的控制策略在不同的道路循环工况下进行仿真。仿真结果表明,所设计的模糊逻辑控制策略能够合理分配发动机和电机的转矩,可使发动机工作在效率较高、排放较低的中等负荷区,整车的燃油经济性较好、排放较低。     

Development of engine control using the in-cylinder pressure signal in a high speed direct injection diesel engine

Emission regulations are becoming more stringent and remain a principal issue for vehicle manufacturers. Many engine subsystems and control technologies have been introduced to meet the demands of these regulations. For diesel engines, combustion control is one of the most effective approaches for reducing not only engine exhaust emissions but also cylinder-by-cylinder variation. However, the high cost of pressure sensors and the complex engine head design for additional equipment present difficulties for manufacturers. In this paper, cylinder pressure-based engine control logic is introduced for a multi-cylinder high speed direct injection (HSDI) diesel engine. The time for 50% of the mass fraction to be burned (MFB50) and the IMEP are valuable for determining the combustion status. These two in-cylinder quantities are measured and applied to the engine control logic. Fuel injection timing is controlled to adjust the operating MFB50 to the target MFB50 using PID control logic, and the fuel injection quantity is controlled to adjust the measured IMEP to the desired IMEP. The control logic is demonstrated at steady state and during transient conditions and is applied to an NEDC mode test.     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.     

Comparison of Dynamic Models of Mr Damper for Hardware in the Loop Simulation of Large-Sized Buses

The present study has focused on the comparison of MR damper dynamic models for the purpose of hardware in the loop simulation. A vehicle dynamic model for large-sized bus and a control logic for MR damper was built. Two typical MR damper models, viz. Bouc-Wen and hyperbolic tangent model have been considered in this study and the advantages and disadvantages of each model on the aspect of HILS system is discussed. We discussed the limitations of each model based on the analysis of the vehicle dynamic simulation. The results showed that the existing models are not suitable for HILS system. We proposed the modified hyperbolic tangent model by adopting low-pass filters. The results from the simulation showed the advantages of the modified model which were validated through HILS system.     

ISG并联混合动力汽车的优化控制研究

优化控制是提高混合动力各方面性能的关键技术。本文提出一种优化模糊控制方法,离线进行发动机优化控制计算后,运用模糊控制算法实现综合优化控制。仿真实验证明,其优于基础的电辅助逻辑控制。通过调整各优化目标的权值和修改模糊控制规则,可灵活地实现不同的控制目标。     

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.     

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.     

Improvement of drivability and fuel economy with a hybrid antiskid braking system in hybrid electric vehicles

When braking on wet roads, Antilock Braking System (ABS) control can be triggered because the available brake torque is not sufficient. When the ABS system is active, for a hybrid electric vehicle, the regenerative brake is switched off to safeguard the normal ABS function. When the ABS control is terminated, it would be favorable to reactivate the regenerative brake. However, recurring cycles from ABS to motor regenerative braking could occur. This condition is felt to be unpleasant by the driver and has adverse effects on driving stability. In this paper, a novel hybrid antiskid braking system using fuzzy logic is proposed for a hybrid electric vehicle that has a regenerative braking system operatively connected to an electric traction motor and a separate hydraulic braking system. This control strategy and the method for coordination between regenerative and hydraulic braking are developed. The motor regenerative braking controller is designed. Control of regenerative and hydraulic braking force distribution is investigated. The simulation and experimental results show that vehicle braking performance and fuel economy can be improved and the proposed control strategy and method are effective and robust.     

New lead-acid battery management system based on generator regulation

A novel regulation system for a vehicle generator and lead-acid battery is proposed in this paper. By integrating the regulation method, the output voltage of the generator is determined and controlled by the algorithm to save electrical energy and protect the lead-acid battery. The regulation algorithm is implemented in Matlab/Simulink, and the logic function of the system is verified using the dSPACE/AutoBox workbench. The experimental results show that the new algorithm improves the performance of the fuel economy of the vehicle and the battery state-of-health compared to the traditional control method.     

基于规则的HEV逻辑门限控制策略

混合动力汽车的控制策略对汽车运行时各性能十分重要,也对汽车油耗的高低有着重要的意义。文章以混合动力客车为基础,对其运行中的几种工作模式进行了分析。然后根据汽车的行驶车速下限、实时车速及电池状态,制定了基于规则的逻辑门限控制策略。最后,在CRUISE中搭建了整车模型,并嵌入控制策略完成仿真。结果表明：文章制定的控制策略满足了汽车经济性能,是正确合理的。     

Design of Integrated Chassis Control logics for AFS and ESP

The performance of most electronic chassis control systems in the past has been optimized individually. Recently, a great research effort has been dedicated to the integration of chassis control systems in an effort to improve the vehicle performance. This involves orchestration of individual control modules so that they can jointly contribute to the enhancement of their control effect. In this research, two integrated control logics for AFS (Active Front Steering) and ESP (Electronic Stability Program) have been developed. Of the two logics, one uses a supervisor that rules over the individual modules. The other logic uses a CL (Characteristic Locus) method, which is a frequency-domain multivariable control technique. The two logics have been tested under various driving conditions to investigate their control effects. The results indicate that the proposed integrated control logics can yield vehicle performance that is superior to that of the individual control modules without any integration scheme.     

多控制器硬件在环测试平台开发

针对插电式燃料电池汽车电控系统实车调试环境复杂、参数多变、极限条件难以模拟等特点,介绍了一种基于ETAS板卡硬件及ETAS软件相结合的硬件在环测试平台开发.依据控制系统的控制策略、电气接口、总线通讯,设计了测试平台的硬件配置、软件程序、测试界面,并快速进行了控制算法验证及故障诊断实验.实验表明,该测试平台能有效地验证控制算法、模拟故障注入、监控系统状态、追踪缺陷来源,可缩短开发周期、节省开发成本、优化测试环境,对整车汽车电子控制系统开发及调试具有重要价值.     

DCT挡位决策控制系统智能化研究

阐述了DCT智能换挡控制系统中体现驾驶意图和行驶工况各种模式的主要特征。采用模糊逻辑技术对驾驶意图和行驶工况进行统一识别,并在已划分的各种模式基础上进行了各模式下标准换挡规律的智能修正。利用所建立的DCT换挡控制系统仿真模型,选取急加速意图和上坡工况进行了DCT智能挡位决策控制仿真分析。结果表明,所提出的DCT挡位决策控制系统能更好地发挥车辆的性能,验证了DCT挡位决策的智能化控制效果。     

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).