دانلود مقاله ترجمه شده سیستم کنترل کشش ترکیبی با کنترلر فازی در خودرو – مجله IEEE

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 چکیده
۱ مقدمه
۲ سیستم کنترل هیبریدی و مدل سازی آن
الف مدل موتور
ب سیستم مدل ترمز هیدرولیکی
ج مدل خودرو
د کنترلر فازی
۳ نتایج شبیه سازی
۴ نتایج تجربی
۵ نتیجه گیری

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این مقاله بررسی طراحی یک دو ورودی با تک خروجی نظارت شده با کنترل فازی پرداخته است. وظیفه ما این است که کنترل نظارت فازی را برای گشتاور ترمز داشته باشیم. گشتاور ترمزهای الکتریکی به عنوان ورودی مرجع بوده که برای ماژول های کنترل سطح پایین است. هنگامی که این کنترل کننده سطح آهنگ ورودی پایین تر دارد، نسبت لغزش مورد نظر می تواند کاهش یابد. شبیه سازی برای تغییر خط اضطراری و لغزش تایر نیز انجام می شود. نتایج نشان می دهد که نسبت نوسان را می توان با کنترل فازی پیشنهاد شده سرکوب نمود و گشتاور ترمز احیا کننده تولید شده، که برای کنترل لایه های پایین تر است، مورد نیاز بوده و تغییر می کند.

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INTRODUCTION The focus of current research towards electric, hybrid electric, and fuel cell vehicles has been on increasing energy efficiency and reducing emissions. Future vehicles will include electric drive-train components that must be capable of performing conventional anti-lock braking, traction control, and active yaw control safety functions. From the viewpoint of electric and control engineering, Hybrid electric vehicles (HEVs) have evident advantages over conventional internal combustion engine vehicles (ICVs). Firstly, Torque generation is very quick and accurate, for both accelerating and decelerating. This should be the essential advantage. In Hybrid electric vehicles, motor and TCS (traction control system)should be integrated into Ϙ Hybrid Traction Control System ( HTCS )ϙ, since a motor can both accelerate or decelerate the wheel. Its performance should be advanced one, if we can fully utilize the fast torque response of motor. Secondly, Output torque is easily comprehensible. There exists little uncertainty in driving or braking torque inputted by motor, compared to that of combustion engine or hydraulic brake. In recent years fuzzy logic control techniques have been applied to a wide range of systems. Many electronic control systems in the automotive industry such as automatic transmissions, engine control and traction control systems are currently being pursued. These electronically controlled automotive systems realize superior characteristics through the use of fuzzy logic based control rather than traditional control algorithms. Fuzzy Logic Control is a type of control, which is based on Fuzzy set theory and reasoning. David Elting and Mohammed Fennich in their research told that automotive systems realize superior characteristics through the use of fuzzy logic controllers [1] especially in nonlinear cases. The brake system is a challenging control problem because the vehicle-brake dynamics are highly nonlinear with uncertain time-varying parameters [2]. Fuzzy controllers have the benefit of not requiring a mathematical model of the plant [3], while still being highly robust [4]. Also, certain fuzzy control designs can be implemented that have the ability to learn [6] or to adapt [5] themselves to improve its performance. Because of these features, fuzzy controllers have been successfully implemented in the automotive field for controlling both wheel dynamics [6], [4], [3], and vehicle dynamics [7], [8]. Bernd M. Baumann has demonstrated the suitability of fuzzy control techniques for the power-train management of Hybrid electric vehicles [19]. However, his operation strategy represents how the individual components of the drive train will interact with one another, emphasizes the means for controlling the power flow, such as transmissions or clutches, and dependency of the components on each other. Niels J. Schouten optimizes the energy flow between the main components of the HEV and optimizes the energy generation and conversion in the individual components. The driver power command, state of charge of the battery, and electric motor speed are used by a fuzzy logic controller to compute the optimal generator power and a scaling factor for the electric motor. The driver power command, optimal generator power, and scaling factor are used to compute the optimal internal combustion engine and motor power [20]. However, its theory emphasizes the driver inputs (from brake and accelerator pedals) are satisfied consistently, the battery is sufficiently charged at all times, and the fuel economy of the PHV is optimized. In this paper, it is different from those and describes a fuzzy Controller for Hybrid Traction Control System in Hybrid Electric Vehicles (HEVs) that prevents the spinning of the drive wheels during take-off and acceleration through targeted, brief brake impulses in motor torque. It emphasizes the vehicle stable control based on the direct torque control of motor. II. Hybrid Traction Control System (HTCS) Modeling A hybrid vehicle operates using two or more different immediate power sources. The typical hybrid electric vehicle uses an electric motor and an internal combustion engine to propel the vehicle. Hydraulic motors and energy storage systems are under development, but are not commercially favored at present. The use of two different power sources allows the vehicle to be designed to exploit the advantages of each power source. A hybrid vehicle increases efficiency through improved energy management and the recovery of energy during braking. Downsizing of the conventional engine is possible with energy management strategies, while regenerative braking allows for the capture of energy which otherwise would be converted to heat by the service brakes. The secondary benefits of hybridization include traction control system (HTCS) and improved performance. The following section describes the structure of HTCS including the HTCS algorithm and sub-component models.