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Neural Network based Direct Torque Controller of SRM for EV Application

التفاصيل البيبلوغرافية
العنوان: Neural Network based Direct Torque Controller of SRM for EV Application
المؤلفون: D Ganesh, Saxena Vijay, Singh Daljeet Pal, Faujdar Pramod Kumar
المصدر: E3S Web of Conferences, Vol 540, p 02003 (2024)
بيانات النشر: EDP Sciences, 2024.
سنة النشر: 2024
المجموعة: LCC:Environmental sciences
مصطلحات موضوعية: direct torque control, ann, electric car, srm, svpwm, Environmental sciences, GE1-350
الوصف: the control aspects of the elecytric vehicle are presented in this paper. The electric car which is driven by a 6/4 Switched Reluctance Motor (SRM) powered by four battery banks is presented in this paper. The new topology of converter is proposed to drive SRM effectively for application of electric car. The direct torque controller is implemented with the help of neural network for effective speed controller with minimum ripples in torque. The required pulses are generated with space vector Pulse Width Modulation (PWM) technique. The electromagnetic torque generated by SRM needs to be maintained at ripples free for smooth operation of electric car. The mathematical validation is implemented to achieve the required power rating of SRM for Toyota Car. The proposed topology of converter has a facility of using four battery banks; hence the charging time of batteries will be minimized. The proposed model is designed on the platform of the MATLAB/Simulink package which is dumped into OPAL-RT modules to establish Hardware – in the – Loop (HIL) for presentation of various results. Various results are discussed with validate explanations of the proposed method.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 2267-1242
Relation: https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/70/e3sconf_icpes2024_02003.pdf; https://doaj.org/toc/2267-1242
DOI: 10.1051/e3sconf/202454002003
URL الوصول: https://doaj.org/article/64ab4ec521c54edda7fedc85d08a5ee8
رقم الأكسشن: edsdoj.64ab4ec521c54edda7fedc85d08a5ee8
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22671242
DOI:10.1051/e3sconf/202454002003