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Iranian Journal of Electrical and Electronic Engineering، جلد ۱۶، شماره ۳، صفحات ۳۶۳-۳۷۰
عنوان فارسی
چکیده فارسی مقاله
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عنوان انگلیسی Optimization of Specific Power of Surface Mounted Axial Flux Permanent Magnet Brushless DC Motor for Electrical Vehicle Application
چکیده انگلیسی مقاله Optimization of specific power of axial flux permanent magnet brushless DC (PMBLDC) motor based on genetic algorithm optimization technique for an electric vehicle application is presented. Double rotor sandwiched stator topology of axial flux permanent magnet brushless DC motor is selected considering its best suitability in electric vehicle applications. Rating of electric motor is determined based on vehicular dynamics and application needs. Double rotor sandwiched stator axial flux PMBLDC motor is designed considering various assumed design variables. Initially designed axial flux PMBLDC motor is considered as a reference motor for further analysis. Optimization of the specific power of electric motor for electric vehicle applications is a very important design issue. The Genetic Algorithm (GA) based optimization technique is proposed for optimization of specific power of axial flux permanent magnet brushless DC motor. Optimization with an objective of maximum specific power with the same torque rating is performed. Three-dimensional finite element analysis is performed to validate the proposed GA based specific power optimization. Close agreement between results obtained from finite element analysis and analytical design establishes the correctness of the proposed optimization technique. The performance of the improved motor is compared with the initially designed reference motor. It is analyzed that the specific power of axial flux PMBLDC motor is enhanced effectively with the application of GA based design optimization technique.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله | A. N. Patel
Electrical Engineering Department, Institute of Technology, Nirma University, India.


| B. N. Suthar
Electrical Engineering Department, Government Engineering College, India.
نشانی اینترنتی http://ijeee.iust.ac.ir/browse.php?a_code=A-10-3201-2&slc_lang=en&sid=1
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کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده Artificial Intelligence Techniques
نوع مقاله منتشر شده Research Paper
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