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INDONESIA
Mechatronics, Electrical Power, and Vehicular Technology
Published by Lembaga Ilmu Pengetahuan Indonesia
ISSN : 20873379     EISSN : 20886985     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
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.
Arjuna Subject : -
Articles 24 Documents
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Search results for , issue "Vol 4, No 2 (2013)" : 24 Documents clear
Front Cover MEV Vol 4 Iss 2 Muharam, Aam
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.%p

Abstract

MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car Aji, Seno; Ajiatmo, Dwi; Robandi, Imam; Suryoatmojo, Heri
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.127-134

Abstract

This paper presents a control called Maximum Power Point Tracking (MPPT) for photovoltaic (PV) system in a solar car. The main purpose of this system is to extracts PV power maximally while keeping small losses using a simple design of converter. Working principle of MPPT based fuzzy logic controller (MPPT-FLC) is to get desirable values of reference current and voltage. MPPT-FLC compares them with the values of the PV's actual current and voltage to control duty cycle value. Then the duty cycle value is used to adjust the angle of ignition switch (MOSFET gate) on the Boost converter. The proposed method was shown through simulation performed using PSIM and MATLAB software. Simulation results show that the system is able to improve the PV power extraction efficiency significantly by approximately 98% of PV’s power.
Object Recognition System in Remote Controlled Weapon Station using SIFT and SURF Methods Midriem Mirdanies; Ary Setijadi Prihatmanto; Estiko Rijanto
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.99-108

Abstract

Object recognition system using computer vision that is implemented on Remote Controlled Weapon Station (RCWS) is discussed. This system will make it easier to identify and shoot targeted object automatically. Algorithm was created to recognize real time multiple objects using two methods i.e. Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) combined with K-Nearest Neighbors (KNN) and Random Sample Consensus (RANSAC) for verification. The algorithm is designed to improve object detection to be more robust and to minimize the processing time required. Objects are registered on the system consisting of the armored personnel carrier, tanks, bus, sedan, big foot, and police jeep. In addition, object selection can use mouse to shoot another object that has not been registered on the system. Kinect™ is used to capture RGB images and to find the coordinates x, y, and z of the object. The programming language used is C with visual studio IDE 2010 and opencv libraries. Object recognition program is divided into three parts: 1) reading image from kinect™ and simulation results, 2) object recognition process, and 3) transfer of the object data to the ballistic computer. Communication between programs is performed using shared memory. The detected object data is sent to the ballistic computer via Local Area Network (LAN) using winsock for ballistic calculation, and then the motor control system moves the direction of the weapon model to the desired object. The experimental results show that the SIFT method is more suitable because more accurate and faster than SURF with the average processing time to detect one object is 430.2 ms, two object is 618.4 ms, three objects is 682.4 ms, and four objects is 756.2 ms. Object recognition program is able to recognize multi-objects and the data of the identified object can be processed by the ballistic computer in realtime.
Appendix MEV Vol 4 Iss 2 Aam Muharam
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.%p

Abstract

Economic Analysis of Cikaso Mini Hydro Power Plant as a CDM Project for Increasing IRR Irhan Febijanto
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.89-98

Abstract

Renewable energy fueled power generations are few developed by private sector in Indonesia. High-cost investment and low electricity selling price to PT PLN as a single buyer is main barriers for private sector to involve in the development of renewable energy fueled power generations. In this project, the economic feasibility of Mini Hydro Power Plant of Cikaso with capacity of 5.3 MW, located at Sukabumi Regency, West Java province was assessed. This project utilized revenue generated from carbon market to increase the economic feasibility. Procedure to register the project to United Nation for Climate Change Convention (UNFCCC) as a Clean Development Mechanism project was explained in detail. Approved Consolidation Methodology (ACM) 0002 Version 12.3.0 was used to calculate grid emission factor in Jawa-Bali-Madura the grid electricity system. It was calculated that the grid emission factor is 0.833 (t-CO2/MWh), and the carbon emission reduction generated for this project is 21,982 ton/year. From the analysis result, it can be proven that the additional revenue from carbon credit could increase the project IRR from 10.28% to 13.52%.
Design and Implementation of Battery Charger with Power Factor Correction using Sepic Converter and Full-bridge DC-DC Converter Moh. Zaenal Efendi; Novie Ayub Windarko; Moh. Faisal Amir
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.75-80

Abstract

This paper presents a design and implementation of a converter which has a high power factor for battery charger application. The converter is a combination of a SEPIC converter and a full-bridge DC-DC converter connected in two stages of series circuit. The SEPIC converter works in discontinuous conduction mode and it serves as a power factor corrector so that the shape of input current waveform follows the shape of input voltage waveform. The full-bridge DC-DC converter serves as a regulator of output voltage and operates at continuous conduction mode. The experimental results show that the power factor of this converter system can be achieved up to 0.96.
Back Cover MEV Vol 4 Iss 2 Aam Muharam
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.%p

Abstract

The Performance of EEG-P300 Classification using Backpropagation Neural Networks Arjon Turnip; Demi Soetraprawata
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.81-88

Abstract

Electroencephalogram (EEG) recordings signal provide an important function of brain-computer communication, but the accuracy of their classification is very limited in unforeseeable signal variations relating to artifacts. In this paper, we propose a classification method entailing time-series EEG-P300 signals using backpropagation neural networks to predict the qualitative properties of a subject’s mental tasks by extracting useful information from the highly multivariate non-invasive recordings of brain activity. To test the improvement in the EEG-P300 classification performance (i.e., classification accuracy and transfer rate) with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis (BLDA). Finally, the result of the experiment showed that the average of the classification accuracy was 97% and the maximum improvement of the average transfer rate is 42.4%, indicating the considerable potential of the using of EEG-P300 for the continuous classification of mental tasks.
Combustion Property Analysis and Control System for the Dynamics of a Single Cylinder Diesel Engine Bambang Wahono; Wang Xiaoli; Harutoshi Ogai
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.117-126

Abstract

Corresponding to global environment problems in recent year, the technology for reducing fuel consumption and exhaust gas emission of engine was needed. Simulation of transient engine response is needed to predict engine performance that frequently experience rapid changes of speed. The aim of this research is to develop a non-linear dynamic control model for direct injection single cylinder diesel engine which can simulate engine performance under transient conditions. In this paper, the combustion model with multistage injection and conducted experiments in the transient conditions to clarify the combustion characteristics was proposed. In order to perform the analysis of acceleration operation characteristics, it was built a Model Predictive Control (MPC) to reproduce the characteristic values of the exhaust gas and fuel consumption from the control parameters in particular. Finally, MPC is an effective method to perform the analysis of characteristic in diesel engine under transient conditions.
Control of Pan-tilt Mechanism Angle using Position Matrix Method Hendri Maja Saputra; Arif Santoso; Midriem Mirdanies; Vikita Windarwati; Riastus Nayanti; Lukni Maulana
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 4, No 2 (2013)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.109-116

Abstract

Control of a Pan-Tilt Mechanism (PTM) angle for the bomb disposal robot Morolipi-V2 using inertial sensor measurement unit, x-IMU, has been done. The PTM has to be able to be actively controlled both manually and automatically in order to correct the orientation of the moving Morolipi-V2 platform. The x-IMU detects the platform orientation and sends the result in order to automatically control the PTM. The orientation is calculated using the quaternion combined with Madwick and Mahony f ilter methods. The orientation data that consists of angles of roll ( α ), pitch ( β ), and yaw ( γ ) from the x-IMU are then being sent to the camera for controlling the PTM motion (pan tilt angles) after calculating the reverse angle using position matrix method. Experiment results using Madwick and Mahony methods show that the x-IMU can be used to find the robot platform orientation. Acceleration data from accelerometer and flux from magneto meter produce noise with standard deviation of 0.015 g and 0.006 G, respectively. Maximum ab solute errors caused by Madgwick and Mahony method with respect to X- axis are 48.45º and 33.91º, respectively. The x-IMU im plementation as inertia sensor to control the Pan-Tilt Mechanism shows a good result, which the probability of pan angle tends to be the same with yaw and tilt angle equal to the pitch angle, except a very small angle shift due to the influence of roll angle.

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