Application of fuzzy control algorithms for electric vehicle antilock braking/traction control systems

The application of fuzzy-based control strategies has gained enormous recognition as an approach for the rapid development of effective controllers for nonlinear time-variant systems. This paper describes the preliminary research and implementation of a fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking systems (ABSs). As the dynamics of the braking systems are highly nonlinear and time variant, fuzzy control offers potential as an important tool for development of robust traction control. Simulation studies are employed to derive an initial rule base that is then tested on an experimental test facility representing the dynamics of a braking system. The test facility is composed of an induction machine load operating in the generating region. It is shown that the torque-slip characteristics of an induction motor provides a convenient platform for simulating a variety of tire/road /spl mu/-/spl sigma/ driving conditions, negating the initial requirement for skid-pan trials when developing algorithms. The fuzzy membership functions were subsequently refined by analysis of the data acquired from the test facility while simulating operation at a high coefficient of friction. The robustness of the fuzzy-logic slip regulator is further tested by applying the resulting controller over a wide range of operating conditions. The results indicate that ABS/traction control may substantially improve longitudinal performance and offer significant potential for optimal control of driven wheels, especially under icy conditions where classical ABS/traction control schemes are constrained to operate very conservatively.     

Mechatronic design and control of hybrid electric vehicles

The work in this paper presents techniques for design, development, and control of hybrid electric vehicles (HEV). Toward these ends, four issues are explored. First, the development of HEV is presented. This synopsis includes a novel definition of degree of hybridization for automotive vehicles. Second, a load-leveling vehicle operation strategy is developed. In order to accomplish the strategy, a fuzzy logic controller is proposed. Fuzzy logic control is chosen because of the need for a controller for a nonlinear, multidomain, and time-varying plant with multiple uncertainties. Third, a novel technique for system integration and component sizing is presented. Fourth, the system design and control strategy is both simulated and then implemented in an actual vehicle. The controller examined in this study increased the fuel economy of a conventional full-sized vehicle from 40 to 55.7 mi/h and increased the average efficiency over the Federal Urban Driving Schedule from 23% to 35.4%. The paper concludes with a discussion of the implications of intelligent control and mechatronic systems as they apply to automobiles     

Adaptive feedback linearization control of antilock braking systems using neural networks

Antilock braking systems are designed to control the wheel slip, such that the braking force is maximized and steerability is maintained during braking. However, the control of antilock braking systems is a challenging problem due to nonlinear braking dynamics and the uncertain and time-varying nature of the parameters. This paper presents an adaptive neural network-based hybrid controller for antilock braking systems. The hybrid controller is based on the well-known feedback linearization, combined with two feedforward neural networks that are proposed so as to learn the nonlinearities of the antilock braking system associated with feedback linearization controller. The adaptation law is derived based on the structure of the controller, using steepest descent gradient approach and backpropagation algorithm to adjust the networks weights. The weight adaptation is online and the stability of the proposed controller in the sense of Lyapunov is studied. Simulations are conducted to show the effectiveness of the proposed controller under various road conditions and parameter uncertainties.     

Propulsion system design of electric and hybrid vehicles

There is a growing interest in electric and hybrid-electric vehicles due to environmental concerns. Efforts are directed toward developing an improved propulsion system for electric and hybrid-electric vehicles applications. This paper is aimed at developing the system design philosophies of electric and hybrid vehicle propulsion systems. The vehicles' dynamics are studied in an attempt to find an optimal torque-speed profile for the electric propulsion system. This study reveals that the vehicles' operational constraints, such as initial acceleration and grade, can be met with minimum power rating if the power train can be operated mostly in the constant power region. Several examples are presented to demonstrate the importance of the constant power operation. Operation of several candidate motors in the constant power region are also examined. Their behaviors are compared and conclusions are made     

电动汽车复合制动系统的优化控制

本文结合电动汽车的动力特征,对其电液制动控制系统进行了优化。综合分析制动强度要求、电机、电池特性,获得了最佳的制动力分配比;在这基础之上,考虑到不同附着系数的道路使用情况,得到优化的汽车前后轴的制动力系数;并通过计算机仿真技术来对该控制系统的性能进行验证。     

混合电动汽车能量流仿真系统

对于混合电动汽车,在实际运行中,为了实现电动机与发动机之间的快速切换,要求系统有较短的响应时间;为了保证汽车运行的稳定性,要求系统具有精确的电流定位;同时,为了保证系统控制的可靠与准确,对系统采样精度与控制速度的要求也较高.研究混合电动汽车的能量流控制策略,关键在于研究电池与电动机和发动机之间的关系.     

Charge balance control schemes for cascade multilevel converter in hybrid electric vehicles

This paper presents transformerless multilevel converters as an application for high-power hybrid electric vehicle (HEV) motor drives. Multilevel converters: (1) can generate near-sinusoidal voltages with only fundamental frequency switching; (2) have almost no electromagnetic interference or common-mode voltage; and (3) make an HEV more accessible/safer and open wiring possible for most of an HEV's power system. The cascade inverter is a natural fit for large automotive hybrid electric drives because it uses several levels of DC voltage sources, which would be available from batteries, ultracapacitors, or fuel cells. Simulation and experimental results show how to operate this converter in order to maintain equal charge/discharge rates from the DC sources (batteries, capacitors, or fuel cells) in an HEV.     

Robust LPV control of diesel auxiliary power unit for series hybrid electric vehicles

This paper presents a robust gain-scheduling approach for the control of diesel auxiliary power unit (APU) for series hybrid electric vehicles (SHEVs), using the linear parameter-varying (LPV) techniques. An average physical model of the diesel APU is established, which combines the subsystem models including diesel engine, synchronous generator, and three-phase diode rectifier in an elegant way. The nonlinear system model is then formulated as a quasi-LPV form with parametric uncertainty and augmented with performance objectives in a robust control framework. As a solution to this type of control problem, a robust LPV control synthesis method is proposed and its numerical implementation issues are also considered. Simulation results verify the performance of the proposed robust LPV controller.     

Hybrid vigour [hybrid electric vehicles]

In this paper, the author reports on the theory and practice behind cars powered by a combination of petrol engine and electric motor. The operating principles and future possibilities for hybrid electric vehicles are outlined