Application of artificial neural network for speed control of BLDC motor 90KW in electrical bus

• Autorzy: Pamuji Feby Agung , Prihantari Kharisma Julieta , Riawan Dedet Candra , Asfani Dimas Anton , Suryoatmojo Heri , Guntur Harus L. , Sudarmanta Bambang , Arumsari Nurvita

Identyfikatory

DOI

10.15199/48.2022.02.47

Warianty tytułu

PL

Zastosowanie sztucznej sieci neuronowej do sterowania prędkością silnika BLDC 90KW w autobusie elektrycznym

• Języki publikacji: EN

Abstrakty

EN

There are many research on electric vehicles to reduce environmental pollution due to vehicles that use fossil fuels. The advantages of using a BLDC motor are high efficiency, high torque, reduced noise, long lifetime, and easy maintenance. Using of BLDC motors in electric vehicles is sometimes not optimal due to varying set points and presence of loads. Then a speed motor is needed to be controlled so the motor can work properly. In this research using the Artificial Neural Network (ANN) method. The ANN on this speed controller is practical as a 3-phase inverter input voltage control so the speed of BLDC motor can match the set point. In the simulation in this research, controlled based ANN is applied to electric buses with large torque, from the simulation it can be seen that Controlled based ANN can work well.

PL

Istnieje wiele badań dotyczących pojazdów elektrycznych mających na celu zmniejszenie zanieczyszczenia środowiska przez pojazdy wykorzystujące paliwa kopalne. Zalety stosowania silnika BLDC to wysoka sprawność, wysoki moment obrotowy, obniżony poziom hałasu, długa żywotność i łatwa konserwacja. Stosowanie silników BLDC w pojazdach elektrycznych czasami nie jest optymalne ze względu na różne nastawy i obecność obciążeń. Następnie konieczne jest sterowanie prędkością silnika, aby silnik mógł działać prawidłowo. W badaniach wykorzystano metodę Sztucznej Sieci Neuronowej (ANN). SSN na tym regulatorze prędkości jest praktycznym sterowaniem napięcia wejściowego falownika 3-fazowego, dzięki czemu prędkość silnika BLDC może być zgodna z wartością zadaną. W symulacji w niniejszych badaniach, kontrolowany SSN jest stosowany do autobusów elektrycznych o dużym momencie obrotowym, z symulacji widać, że SSN w oparciu o sterowanie może dobrze działać.

Słowa kluczowe

EN

brushless DC motor; BLDC; artificial neural network; ANN; electric vehicle

PL

silnik bezszczotkowy; BLDC; sztuczna sieć neuronowa; pojazd elektryczny

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2022
• Tom: R. 98, nr 2
• Strony: 203--210
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Pamuji Feby Agung

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0002-0603-9761

autor

Prihantari Kharisma Julieta

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0003-3474-9549

autor

Riawan Dedet Candra

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0002-7680-4625

autor

Asfani Dimas Anton

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0002-9705-5686

autor

Suryoatmojo Heri

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0001-8855-9869

autor

Guntur Harus L.

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0002-4998-2979

autor

Sudarmanta Bambang

• Institut Teknologi Sepuluh Nopember

• https://orcid.org/0000-0002-9824-6820

autor

Arumsari Nurvita

• Shipbuilding Institute of Polytechnic Surabaya

• https://orcid.org/0000-0002-3658-0989

Bibliografia

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