Mechatronics, Electrical Power, and Vehicular Technology
Mechatronics, Electrical Power, and Vehicular Technology (hence MEV) is a journal aims to be a leading peer-reviewed platform and an authoritative source of information. We publish original research papers, review articles and case studies focused on mechatronics, electrical power, and vehicular technology as well as related topics. All papers are peer-reviewed by at least two referees. MEV is published and imprinted by Research Center for Electrical Power and Mechatronics - Indonesian Institute of Sciences and managed to be issued twice in every volume. For every edition, the online edition is published earlier than the print edition.
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<![CDATA[Load characteristic analysis of a double-side internal coreless stator axial flux PMG ]]>
<![CDATA[Wirtayasa, Ketut]]>;
<![CDATA[Irasari, Pudji]]>;
<![CDATA[Kasim, Muhammad]]>;
<![CDATA[Widiyanto, Puji]]>;
<![CDATA[Hikmawan, Muhammad Fathul]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.17-23
<![CDATA[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 and 1 phase is discussed. The purpose is to learn the effect of the load to the generator performance, particularly the output power, efficiency and voltage regulation. The design and analysis are conducted analytically and numerically with two types of simulated loads, pure resistive and resistive-inductive 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.]]>
<![CDATA[Appendix MEV Vol 10 Iss 1 ]]>
<![CDATA[Pikra, Ghalya]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.%p
<![CDATA[Quasi-flat linear PM generator optimization using simulated annealing algorithm for WEC in Indonesia ]]>
<![CDATA[Azhari, Budi]]>;
<![CDATA[Wijaya, Fransisco Danang]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.29-35
<![CDATA[Linear permanent magnet generator (LPMG) is an essential component in recent wave energy converter (WEC) which exploits 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 and designed for pico-scale WEC. Design optimization has further been conducted for flat-tricore LPMG, by using 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 dimension. 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.]]>
<![CDATA[Back Cover MEV Vol 10 Iss 1 ]]>
<![CDATA[Pikra, Ghalya]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.%p
<![CDATA[Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control ]]>
<![CDATA[Faqih, Kamil]]>;
<![CDATA[Primadi, Wahyu]]>;
<![CDATA[Handayani, Anik Nur]]>;
<![CDATA[Priharta, Ari]]>;
<![CDATA[Arai, Kohei]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.36-47
<![CDATA[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 and 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 and high condition which has a voltage of 11.5 <; ....; <13 Volts. PV has been served batteries or loads when the light intensity is cloudy and 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.]]>
<![CDATA[Sensorless-BLDC motor speed control with ensemble Kalman filter and neural network ]]>
<![CDATA[Rif'an, Muhammad]]>;
<![CDATA[Yusivar, Feri]]>;
<![CDATA[Kusumoputro, Benyamin]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.1-6
<![CDATA[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 and to improve the accuracy of estimation results of sensorless-BLDC. In this paper, a new filtering algorithm is proposed for sensorless 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 and 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 disturbance 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.]]>
<![CDATA[Exhaust emissions analysis of gasoline motor fueled with corncob-based bioethanol and RON 90 fuel mixture ]]>
<![CDATA[Widiyanti, Widiyanti]]>;
<![CDATA[Mizar, Muhammad Alfian]]>;
<![CDATA[Wicaksana, Christian Asri]]>;
<![CDATA[Nurhadi, Didik]]>;
<![CDATA[Moses, Kriya Mateeke]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.24-28
<![CDATA[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 CO2 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 emissions was 0.177 vol% using E100 fuel, and the highest average was 2.649 vol% using 100 % RON 90 fuel, displaying a significant difference. The lowest average of CO2 emissions was 6.6 vol% using 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 emissions was E100.]]>
<![CDATA[Front Cover MEV Vol 10 Iss 1 ]]>
<![CDATA[Pikra, Ghalya]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.%p
<![CDATA[Vehicular networking and computer vision-based distance estimation for VANET application using Raspberry Pi 3 ]]>
<![CDATA[Pratama, Mulia]]>;
<![CDATA[Gruosso, Giambattista]]>;
<![CDATA[Santoso, Widodo Budi]]>;
<![CDATA[Praptijanto, Achmad]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.7-16
<![CDATA[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 thus supporting 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 and 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 distance estimation, at least three methods have been compared in this research and found evidence 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-friendly computer device the Raspberry Pi. The performance of the 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.]]>
<![CDATA[Preface MEV Vol 10 Iss 1 ]]>
<![CDATA[Pikra, Ghalya]]>
<![CDATA[ Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 10, No 1 (2019) ]]>
Publisher : <![CDATA[Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences ]]>
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DOI: 10.14203/j.mev.2019.v10.%p
