The Control System Of Switch Magnetic Resistance Motor (SRM) And The Application In The Automobile

The luxurious automobile uses many categories of the electrical motor. A massive usage of automobile electrical motor not only can enhance the degree of electrification and the automation of automobile, but also can make automobile reducing in weight, and make them become high intelligent, moreover, it can raise the modern level of the automobile. So research in motor is very necessary. This article is mainly to study on the study with the control system of switch magnetic resistance motor (SRM) and the application in the automobile.The development of electric vehicle is representative of direction of advance of automobiles in 21st century. And one extremely important essential technology in the electric vehicle is the Control problem of electrical motor. One electric automobile we usually use permanent magnetism synchronous motor and switch magnetic resistance electrical motor. For the application in the automobile, this paper presents an improved current controller for a switched reluctance motor (SRM) drive. In the proposed method, a B-spline neural network was used to model the SRM and estimate hack EMF and incremental inductance on-line in real-time. The on-line modeling scheme does not require a priori knowledge of SRM's electromagnetic characteristics. Based on the on-line estimated parameters, current control with an adjustable PI controller and a hack EMF decoupling technique has been implemented. The performance of the current controller has been demonstrated in simulation using a four-phase 8/6 30kW SRM.Meanwhile, the dissertation gives the research about the sensorless method for estimate the rotor position for SRD system. A sliding-mode observer (SMO) for estimate rotor position is discussed in the study, a B-spline neural network torque control system based on the SMO is designed. Due to the local weights updating algorithm of the BSNN, the appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. Simulation results demonstrate the valid robustness and precision of the scheme for estimation of rotor position, while minimizing the torque ripple and optimizing other performance.At last, according to the requirement of performance of electric vehicle, the load of drive system is analyzed, that means analyzing in need of pull when the electric automobile is running. A Closed-form Solutions based on pull analysis is proposed, and a mechanics model of the vehicle is set up using the Closed-form Solutions. Simulation results demonstrate the validity of chose a four phase, 8/6, 30kw SRM.