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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Proceeding of the Electrical Engineering Computer Science and Informatics
AHMADI, SOFYAN
Pascasarjana Program Magister Jurusan Teknik Elektro Universitas Jember
Computer Science & IT Electrical & Electronics Engineering Engineering

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Steering System of Electric Vehicle using Extreme Learning Machine Sofyan Ahmadi; Khairul Anam; Azmi Saleh
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2096

Abstract

The development of electric vehicle technology is currently increasing and growing very fast. Some efforts have been conducted, one of which is using BLDC (brushless direct current) motors to improve efficiency. This study utilized extreme learning machine (ELM) embedded on the microcontroller as well as the differential method for controlling the rotational speed of the BLDC motor. The experimental results on the acceleration testing by traveling a distance of 200 meters achieved the average current of 1.09 amperes. The average power efficiency test is 104 watts. Furthermore, the results of the efficiency experiment with a track length of 3.3 km (kilometers) in 10 minutes obtained the energy efficiency of 177.34 km/kWh (kilowatt for one hour)
Peningkatan Efisiensi Energi pada Kendaraan Listrik dengan Elektronik Diferensial Berbasis ANN (Artificial Neural Network) AHMADI, SOFYAN; ANAM, KHAIRUL; WIDJONARKO, WIDJONARKO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 3: Published September 2020
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i3.642

Abstract

ABSTRAKSeiring dengan perkembangan teknologi kendaraan listrik yang saat ini semakin canggih dan berkembang sangat cepat, upaya pengembangan kendaraan listrik terus dilakukan, salah satunya penggunaan motor BLDC dalam kendaraan listrik untuk meningkatkan efisiensi. Penelitian ini menggunakan kontrol ANN (Artificial Neural Network) pada mikrokontroler serta metode differential untuk pengontrolan kecepatan putar motor BLDC. Pengujian Percepatan dengan menempuh jarak 200 meter arus rata-rata sebesar 1,05 ampere. Daya rata-rata pada pengujian efisiensi sebesar 101 watt. Hasil efisiensi dari pengujian dengan panjang lintasan sejauh 3,3 km dengan waktu tempuh 10 menit didapatkan hasil efisiensi energi dari sistem kendaraan sebesar 179,34 km/kwh.Kata kunci: Motor BLDC, Elektronik Diferensial, Neural network-Logic, Akselerasi, Efisiensi. ABSTRACTAlong with the development of electric vehicle technology that is currently increasingly sophisticated and growing very fast. efforts to develop electric vehicles continue to be done, one of them the use of BLDC motor in electric vehicles to improve efficiency. In this study using ANN (Artificial Neural Network) control on the microcontroller as well as the differential method for controlling the rotational speed of the BLDC motor. Acceleration Testing with a distance of 200 meters average flow of 1.05 amperes. The average power on the 101 watt efficiency test. The efficiency of the test with the length of the track as far as 3.3 km with the travel time of 10 minutes obtained the efficiency of energy in the vehicle system of 179.34 km / kwh.Keywords: BLDC Motor, Electronic Differential, Neural network-Logic, Acceleration,Efficiency.
Co-Authors Anam, Khairul Anam, M. Khairul Azmi Saleh Widjonarko .