MEV Journal of Mechatronics, Electrical Power, an d Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, 2019 AIM AND SCOPE Journal of Mechatronics, Electrical Power, and Vehicular Technology (MEV) is an internationally peer-reviewed journal aims to provide authoritative global source of scientific information for researchers and engineers in academia, research institutions, government agencies, and industries. The Journal publishes original research papers, review articles and case studies focused on: Mechatronics: including control system, robotic, CNC Machine, sensor, signal processing, electronics, actuator, and mechanical dynamics. Electrical Power: including power generation, transmission system, new and renewable energy, turbine and generator design and analysis, grid system, and source assessment. Vehicular Technology: including electric/hybrid vehicle design and analysis, vehicle on grid, fuel efficiency, and safety analysis. Selected Applications: including all implementations or implications related to mechatronics, electrical power, or vehicular technology. MEV's vision is to become an international platform with high scientific contribution for the global community. MEV's mission is presenting important results of work, whether in the form of research, development, application, or design. IMPRINT MEV is published by Research Centre for Electrical Power and Mechatronics - Indonesian Institute of Sciences (RCEPM-LIPI). ISSN print: 2087-3379 ISSN electronics: 2088-6985 Electronics edition is available at: http://www.mevjournal.com All published article are embedded with DOI number affiliated with Crossref DOI prefix 10.14203 PUBLICATION FREQUENCY MEV is managed to be issued twice in every year. 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Ir. Sutami 36 A, Surakarta, 57126, INDONESIA Prof. Josep M Rossell Control, Dynamics and Applications (CoDAlab), Department of Mathematics Universitat Politècnica de Catalunya (UPC), Avda. Bases de Manresa, 61-73 08242 - Manresa (Barcelona), SPAIN Prof. Taufik Director of Electric Power Institute, California Polytechnique San Luis Obispo, CA 93407, UNITED STATES Prof. Dr. Tagawa Yasutaka Tokyo University of Agriculture and Technology Naka-machi 2 - 24 – 16, Koganei – shi, Tokyo, 184 – 8588, JAPAN Prof. Dr. Bambang Riyanto School of Electrical Engineering and Informatics, Bandung Institute of Technology Jl. Ganesha No. 10, Bandung 40135, INDONESIA Prof. Dr. Adi Soeprijanto Department of Electrical Engineering, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember (ITS) Campus ITS Keputih, Surabaya 60111, INDONESIA Dr. Jose Guivant School of Mechanical and Manufacturing Engineering, The University of New South Wales Ainsworth Building (J17) Level 3, Room 311B, Kensington Campus, AUSTRALIA Prof. Pekik Argo Dahono School of Electrical Engineering and Informatics, Bandung Institute of Technology Jl. Ganesha No. 10, Bandung 40135, INDONESIA Assoc. Prof. John Young School of Engineering and IT, The University of New South Wales, Australian Defence Force Academy, PO Box 7916, Canberra BC ACT 2610, AUSTRALIA Prof. Keum Shik Hong Department of Mechanical Engineering, Pusan National University, KOREA, REPUBLIC OF George Anwar, Ph.D. University of California, 101 Sproul Hall, Berkeley, CA 94704, UNITED STATES Dr. Agus Sunjarianto Pamitran Dept. of Mechanical Engineering, University of Indonesia Kampus UI Depok 16424 Depok, Jawa Barat, INDONESIA Dr. Tatacipta Dirgantara Mechanical and Aerospace Engineering, Bandung Institute of Technology, Jl. Ganesha No. 10, Bandung 40135, INDONESIA Riza Muhida, Ph.D. STKIP Surya Jl. Scientia Boulevard Blok U/7 Summarecon Gading Serpong, Tangerang, Banten, 15810, INDONESIA Dr.Eng. Budi Prawara Research Centre for Electrical Power and Mechatronics – LIPI Komp LIPI Jl Sangkuriang, Blg 20, 2nd Fl, Bandung 40135, INDONESIA ADVISORY EDITOR Dr. Endra Joelianto Engineering Physics, Bandung Institute of Technology Jl. Ganesha No. 10, Bandung 40135, INDONESIA javascript:openRTWindow('http://www.mevjournal.com/index.php/mev/about/editorialTeamBio/741') javascript:openRTWindow('http://www.mevjournal.com/index.php/mev/about/editorialTeamBio/745') javascript:openRTWindow('http://www.mevjournal.com/index.php/mev/about/editorialTeamBio/743') Journal of Mechatronics, Electrical Power, an d Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, 2019 ASSOCIATE EDITORS (MAIN HANDLING EDITOR) Yanuandri Putrasari, M.Eng. Ulsan University 93 Daehak-ro, Mugeo-dong, Nam-gu, Ulsan, South Korea, REPUBLIC OF KOREA Dian Andriani, M.Eng. Research Centre for Electrical Power and Mechatronics – LIPI Komp LIPI Bandung, Blg 20, 2nd Fl, Bandung 40135, INDONESIA Tinton D Atmaja, M.T. Research Centre for Electrical Power and Mechatronics – LIPI Komp LIPI Bandung, Blg 20, 2nd Fl, Bandung 40135, INDONESIA Roni Permana Saputra, M.Eng Dyson School of Design Engineering Robot Intelligence Lab Imperial College, London, UNITED KINGDOM Aam Muharam, M.T. ASEM, Interdisciplinary Graduate School of Engineering Kyushu University Fukuoka, JAPAN Ghalya Pikra, M.T. Research Centre for Electrical Power and Mechatronics – LIPI Komp LIPI Bandung, Blg 20, 2nd Fl, Bandung 40135, INDONESIA Journal of Mechatronics, Electrical Power, an d Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, 2019 © 2019 RCEPM-LIPI. All rights reserved. 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Notice No responsibility is assumed by the Publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Although all advertising material is expected to conform to ethical (medical) standards, inclusion in this publication does not constitute a guarantee or endorsement of the quality or value of such product or of the claims made of it by its manufacturer. Journal of Mechatronics, Electrical Power, and Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 v Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, July 2019 FOREWORD FROM EDITOR-IN-CHIEF Journal of Mechatronics, Electrical Power, and Vehicular Technology (MEV) is an international journal indexed by many internationally recognized indexers. Its Digital Object Identifier (DOI) Prefix is 10.14203. In this issue, six papers are published with the authors diversity came from Indonesia, Taiwan, Japan, Australia, and Italia. The papers come from multidisciplinary topics including mechatronics, electrical power, and vehicular technology. They may be classified as follows. Two papers are related to mechatronics which address speed control of a sensorless BLDC motor and computer vision-based distance estimation for VANET application. Three papers fall in electrical power topic. The first paper presents load characteristic analysis of a double-side internal coreless stator axial flux PMG. The second paper proposes a method for optimization of quasi-flat linear PM generator using simulated annealing algorithm for WEC in Indonesia. The third paper describes a smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control. One paper deals with vehicular technology topic i.e. exhaust emissions analysis of gasoline motor fueled with corncob-based bioethanol and RON 90 fuel mixture. Since the first volume, our journal provides discretion in financial term by waiving the article processing charge.We would like to acknowledge our immense gratitude to our International Editorial Board members, reviewers and authors. We hope this publication would contribute to the enhancement of science and technology. Bandung, December 2019 Editor-in-Chief Journal of Mechatronics, Electrical Power, and Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 vi Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, 2019 LIST OF CONTENTS Sensorless-BLDC motor speed control with ensemble Kalman filter and neural network Muhammad Rif’an, Feri Yusivar, Benyamin Kusumoputro ................................................................. 1-6 Vehicular networking and computer vision-based distance estimation for VANET application using Raspberry Pi 3 Mulia Pratama, Giambattista Gruosso, Widodo Budi Santoso, Achmad Praptijanto .................... 7-16 Load characteristic analysis of a double-side internal coreless stator axial flux PMG Ketut Wirtayasa, Pudji Irasari, Muhammad Kasim, Puji Widiyanto, Muhammad Fathul Hikmawan .................................................................................................................................................. 17-23 Exhaust emissions analysis of gasoline motor fueled with corncob-based bioethanol and RON 90 fuel mixture Widiyanti, Muhammad Alfian Mizar, Christian Asri Wicaksana, Didik Nurhadi, Kriya Mateeke Moses ......................................................................................................................................... 24-28 Quasi-flat linear PM generator optimization using simulated annealing algorithm for WEC in Indonesia Budi Azhari, Francisco Danang Wijaya ................................................................................................. 29-35 Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control Kamil Faqih, Wahyu Primadi, Anik Nur Handayani, Ari Priharta, Kohei Arai ............................... 36-47 Further articles can be found at http://www.mevjournal.com http://www.mevjournal.com/ Journal of Mechatronics, Electrical Power, and Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 vii Journal of Mechatronics, Electrical Power, and Vehicular Technology Volume 10, Issue 1, 2019 ABSTRACTS SHEET e-ISSN: 2088-6985 Date of issues: 17 December 2019 p-ISSN: 2087-3379 The descriptions given are free terms. This abstract sheet may be reproduced without permission or change. Muhammad Rif’an a, *, Feri Yusivar b, Benyamin Kusumoputro b (a Department of Electrical Engineering, Universitas Negeri Jakarta, Indonesia; b Department of Electrical Engineering, Universitas Indonesia, Indonesia ) Sensorless-BLDC motor speed control with ensemble Kalman filter and neural network Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 1-6, 6 ill, 0 tab, 17 ref. The use of sensorless technology at BLDC is mainly to improve operational reliability and play a role for wider use of BLDC motors in the future. This research aims to predict load changes an d to improve the accuracy of estimation results of sensorless-BLDC. In this paper, a new filtering algorithm is proposed for sen sorless brushless DC motor based on Ensemble Kalman filter (EnKF) and neural network. The proposed EnKF algorithm is used to estimate speed and rotor position, while neural network is used to estimate the disturbance by simulation. The proposed algorithm requires only the terminal voltage and the current of three phases for estimated speed an d disturbance. A model of non-linear systems is carried out for simulation. Variations in disturbances such as external mechanical loads are given for testing the performance of the proposed algorithm. The experimental results show that the proposed algorithm has sufficient control with error speed of 3 % in a disturban ce of 50 % of the rated-torque. Simulation results show that the speed can be tracked and adjusted accordingly either by disturbances or the presence of disturbances. (Author) Keywords: en semble Kalman filter; neural network; sensorless; brushless DC motor . Mulia Pratama a, *, Giambattista Gruosso b, Widodo Budi Santoso a, Achmad Praptijanto a (a Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences, Indonesia; b Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Italy) Vehicular networking and computer vision-based distance estimation for VANET application using Raspberry Pi 3 Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 7-16, 12 ill, 4 tab, 19 ref. This research was implementing vehicle networking using WIFI connection and computer vision to measure the distance of vehicles in front of a driver. In particular, this works aimed to improve a safe driving environment th us supportin g the current technology concept being developed for inter-vehicular networking, VANET, especially in its safety application such as Overtaking Assistance System. Moreover, it can wirelessly share useful visual information such as hazard area of a road accident. In accordance with Vehicle- to-Vehicle (V2V) concept, a vehicle required to be able to conduct networking via a wireless connection. Useful data and video were the objects to be sent over the network established. The distance of a vehicle to other vehicles towards it is measured an d sent via WIFI together with a video stream of the scenery experienced by the front vehicle. Haar Cascade Classifier is chosen to perform the detection. For distan ce estimation, at least three methods have been compared in this research and foun d eviden ce that, for measuring 5 meters, the iterative methods shows 5.80. This method performs well up to 15 meters. For measuring 20 meters, P3P method shows a better result with only 0.71 meters to the ground truth . To provide a physical implementation for both the detection and distance estimation mechanism, those methods were applied in a compact small-sized vehicle-frien dly computer device the Raspberry Pi. The performance of th e built system then analyzed in terms of streaming latency and accuracy of distance estimation and shows a good result in measuring distance up to 20 meters. (Author) Keywords: computer vision; Haar Cascade Classifier; distance estimation . Ketut Wirtayasa a, b, *, Pudji Irasari a, Muhammad Kasim a, c, Puji Widiyanto a, Muhammad Fathul Hikmawan a (a Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences, Indonesia; b Department of Electrical Engineering, National Taiwan University of Science an d Technology, Taiwan; c School of Electrical Engineering and Telecommunications, University of New South Wales, Australia ) Load characteristic analysis of a double-side internal coreless stator axial flux PMG Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 17-23, 9 ill, 4 tab, 13 ref. The main issue of using a permanent magnet in electric machines is the presence of cogging torque. Several methods have been introduced to eliminate it, one of which is by employing a coreless stator. In this paper, the load characteristic analysis of the double- side internal coreless stator axial flux permanent magnet generator with the specification of 1 kW, 220 V, 50 Hz, 300 rpm an d 1 phase is discussed. The purpose is to learn the effect of the load to the generator performance, particularly the output power, efficien cy and voltage regulation . The design an d analysis are conducted analytically and numerically with two types of simulated loads, pure resistive and resistive-in ductive in series. Each type of load provides power factor 1 and 0.85 respectively. The simulation results show that when loaded with resistive load, the generator gives a better performance at the output power (1,241 W) and efficiency (91 %), whereas a better voltage regulator (5.86 %) is achieved when it is loaded with impedance. Since the difference in the value of each parameter being compared is relatively small, it can be concluded that the generator represents good performance in both loads. (Author) Keywords: coreless stator; axial flux permanent magnet generator; load characteristics; resistive load; resistive-inductive in series. Widiyanti a, *, Muhammad Alfian Mizar a, Christian Asri Wicaksana b, Didik Nurhadi a, Kriya Mateeke Moses c (a Department of Mechanical Journal of Mechatronics, Electrical Power, and Vehicular Technology e-ISSN 2088-6985 www.mevjournal.com p-ISSN 2087-3379 viii Engineering, State University of Malang, Indonesia; b Bachelor Program, Department of Mechanical Engineering, State University of Malang, In donesia; c Graduate school of technological and vocational education, National Yunlin University of Science and Technology, Taiwan) Exhaust emission s analysis of gasoline motor fueled with corncob- based bioethanol and RON 90 fuel mixture Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 24-28, 2 ill, 1 tab, 36 ref. One of the viable solutions to the fossil fuel energy crisis was to seek alternative sources of environmentally friendly energy with the same or better quality such as bioethanol. It was possible to produce bioethanol from organic waste, e.g., corncob. This research aimed to obtain the lowest exhaust emission levels of CO and CO 2 generated from a gasoline motor that used a mixture of bioethanol containing 96 % corncob and RON 90 fuel. This research was experimental using Anova statistical data analysis method. The results showed that the lowest average of CO emission s was 0.177 vol% using E100 fuel, and the highest average was 2.649 vol% using 100 % RON 90 fuel, displayin g a significant difference. The lowest average of CO2 emission s was 6.6 vol% usin g E100 fuel, and the highest was 7.51 vol% using 100 % RON 90 fuel, which was insignificantly different. The mixture variation with the lowest CO and CO2 emission s was E100. (Author) Keywords: RON 90 fuel; corncob-based bioethanol; gasoline generator; CO an d CO2 exhaust emissions. Budi Azhari a, *, Francisco Danang Wijaya b (a Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences, Indonesia; b Department of Electrical Engineering and Information Technology, Engineering Faculty, Universitas Gadjah Mada, Indonesia ) Quasi-flat linear PM generator optimization using simulated annealing algorithm for WEC in Indonesia Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 29-35, 10 ill, 3 tab, 15 ref. Linear permanen t magnet generator (LPMG) is an essential component in recent wave energy converter (WEC) which ex ploits wave’s heave motion. It could be classified into tubular-type, flat- tricore type, and quasi-flat type. In previous researches, these three models have been studied an d designed for pico-scale WEC. Design optimization has further been conducted for flat-tricore LPMG, by usin g simulated annealing (SA) algorithm. It modified some parameters to minimize the resulted copper loss. This paper aims to optimize a quasi-flat LPMG design by applying SA algorithm. The algorithm would readjust the initial LPMG parts dimen sion. Then, the output of the optimized design would be analyzed and compared. The results showed that the optimization could reduce the copper loss by up to 73.64 % and increase the efficiency from 83.2 % to 95.57 %. For various load resistances, the optimized design also produces larger efficiency. However, the optimized design has a larger size and produces larger cogging force than the initial design. (Author) Keywords: design optimization; copper loss; simulated annealing; quasi-flat LPMG. Kamil Faqih a, *, Wahyu Primadi a, Anik Nur Handayani a, Ari Priharta a, Kohei Arai b (a Electrical Engineering Postgraduate, Electrical engineering Department, Universitas Negeri Malang, Indonesia; b Department of Information Science, Saga University, Japan) Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2019, vol. 10, no. 1, p. 36-47, 20 ill, 2 tab, 16 ref. The Utilization of renewable energy such as a photovoltaic system is the foremost alternative in transfers generated by conventional power plants, but the lack of photovoltaics is support for light intensity. The purpose of this research is to develop a pilot-scale smart grid photovoltaic system that can regulate the supply of electrical energy from either the battery or the power supply. The control system in this study uses the Mamdani fuzzy logic method in determining automatic system performance. This system monitors the intensity of light an d battery which are then used as automatic safety parameters on the power supply, battery, and photovoltaic. The results of this study display the indicator results from the microcontroller in supplying electrical energy for the use of electrical loads, Power Supply has been served the load when the battery is in a low state which have a voltage <11 Volts, the battery has been served the load when the condition of the battery is in a medium an d high condition which has a voltage of 11.5 <; ....; <13 Volts. PV has been served batteries or loads when the light intensity is cloudy an d bright which have a light intensity of 3585 <; ...; <10752 Lux. This system can reduce dependence on conventional energy without reducing the quality of the energy supply at load and Photovoltaic system dependence on light intensity does not affect the supply of energy consumption to electrical loads . (Author) Keywords: renewable energy; photovoltaic systems; fuzzy logic .