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العنوان
Advanced control of switched reluctance motor drives for electric vehicles /
المؤلف
Abd El-Aziz, Mahmoud Hamouda Mahmoud.
هيئة الاعداد
باحث / محمود حمودة محمود عبدالعزيز
مشرف / لاسزلوا سزامل
مناقش / سوتو سلطان
مناقش / هاجدوا اندري
الموضوع
Electric vehicles. Electric Power Engineering.
تاريخ النشر
2020.
عدد الصفحات
online resource (145 pages) :
اللغة
الإنجليزية
الدرجة
الدكتوراه
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
1/12/2020
مكان الإجازة
جامعة المنصورة - كلية الهندسة - قسم هندسة القوة الكهربائية
الفهرس
Only 14 pages are availabe for public view

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Abstract

Advanced Control of Switched Reluctance Motor Drives for Electric Vehicles Electric vehicles (EVs) are the way forward for green transportation and for establishing a low-carbon economy. With the rapid electrification of transportation, it is very important to have a comprehensive understanding of the criteria used in motor selection. The switched reluctance motor (SRM) is the simplest of all-electric machines. It promises a reliable and low-cost variable-speed drive for EVs. However, its main drawback is the double salient structure which causes highly nonlinear magnetic characteristics. Besides, it makes the modeling and control of SRMs a difficult task. It also causes acoustic noise and torque ripple. This thesis focuses on the development of an efficient and robust SRM drive for EVs. To achieve this goal, a complete drive system for SRM is designed, built, and integrated on a test bench that allows verifications and testing of SRM for vehicle propulsion. Besides, a highly trusted model for the tested SRM that contains all the nonlinearities is developed based on flux and torque measurements. Moreover, a new analytical technique for optimum excitation of SRM drives over the entire speed range has been developed. Besides, an optimization-based problem is set to calculate the optimum control parameters of SRM. It optimizes the motor performance based on its dynamic torque-speed characteristics instead of the common analysis of static torque curves. The optimum control parameters are defined for each operating point. Then, the obtained data are used to train a feed-forward artificial neural network (ANN) in order to implement the control algorithm. Furthermore, an indirect instantaneous torque control (IITC) scheme using torque sharing function (TSF) for torque ripple reduction of SRM drive has been achieved. It can provide maximum torque per ampere (MTPA) production. Besides, a modified TSF is introduced to compensate for torque ripples in order to extend the speed range. Also, a direct instantaneous torque control (DITC) is proposed. The excitation parameters are optimized for MTPA, torque ripple reduction, and efficiency improvement. Also, a simple structure average torque control (ATC) technique is proposed for EVs. The simple average torque control (SATC) can provide all the vehicle requirements including wide speed range, high dynamics, reduced torque ripple, and high efficiency. Finally, universal control of SRM drives is proposed for EVs. It uses a DITC and SATC for low and high speeds, respectively. A smooth transition between DITC and SATC is guaranteed through the excitation parameters.