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العنوان
Analysis and Optimal Design of Brushless DC Micromotor\
المؤلف
Mohammed,Ahmed Sayed Abd-Rabou
هيئة الاعداد
باحث / أحمد سيد عبد ربه محمد
مشرف / أحمد عبد الستار عبد الفتاح
مشرف / مصطفي ابراھيم محمد مرعي
مناقش / حسن السيد أحمد إبراهيم
تاريخ النشر
2019.
عدد الصفحات
178p.:
اللغة
الإنجليزية
الدرجة
الدكتوراه
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
1/1/2019
مكان الإجازة
جامعة عين شمس - كلية الهندسة - كهربة قوى
الفهرس
Only 14 pages are availabe for public view

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from 204

Abstract

This thesis presents a novel analysis and design of axial flux brushless DC micromotor for implantable drug delivery applications for chemotherapy of liver cancer. In order to design the micromotor, an analytical model has been formulated. The 3D finite elements simulation has been used to validate the analytical model accuracy as well as the experimental results of a previous work, before using it to find the optimal design. The variations of the geometrical dimensions, electrical parameters, and their effects on the output torque and back EMF have been also examined. Finite element computations have been used for numerical experiments on geometrical design variables in order to evaluate the coefficients of a second-order empirical model for the response surface representation. Mono-objective and multi-objective optimization problems are introduced. The Bat Algorithm (BA) is used to solve the mono-objective optimization process to minimize the motor volume and improve joules efficiency in separate optimization problems with the constraints of maximum required torque and maximum back EMF. The optimization results were compared with other metaheuristic algorithms, including Genetic Algorithms (GA), and Particle Swarm Optimization (PSO). The bat algorithm results show an improvement over GA and PSO results. Moreover, multi-objective design optimization technique using Multi-Objective Multi-Verse optimization algorithm (MOMVO) is introduced. The two objectives of the optimization process are to minimize the micromotor volume and improve Joules efficiency with the constraints of maximum required torque and maximum required back EMF. The optimization results were compared with efficient multi-objective algorithm, the Non-Dominated Sorting Genetic Algorithm Version II (NSGA-II). The MOMVO algorithm results show an improvement over NSGA-II results. Prototypes of large scale PCB motor is designed and manufactured to verify the analytical model and simulation of micromotor.