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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 16 Documents
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Search results for , issue "Vol 16, No 1 (2025)" : 16 Documents clear
Automatic water droplet splash photography: Design and analysis of an Arduino-controlled solenoid triggering device Khamdi, Nur; Nasution, Henry; Mulyadi, Mulyadi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1124

Abstract

Capturing transient water droplet splashes poses significant challenges due to their millisecond-scale corona formations, with manual methods achieving only 3 % success rates. This study developed an Arduino-based automated photography system that integrates a solenoid-driven droplet generator and optocoupler-triggered camera to address this limitation. The device calculates droplet impact timing using gravitational acceleration by synchronizing solenoid activation and camera triggering via an Arduino Nano. Experimental trials at a 50 cm droplet height demonstrated 100 % capture accuracy at 105 ms delays, outperforming manual methods (6 % success). Photographer evaluations rated splash aesthetics at 50 cm as optimal (9/10), emphasizing crown symmetry and height. The optocoupler-based system achieved sub-millisecond response times, surpassing electromechanical alternatives. By reducing memory waste from failed captures by 94 %, this approach enhances efficiency in high-speed macro photography. These results validate the system’s reliability for studying fluid dynamics and surface interactions, offering a scalable framework for automated imaging applications in scientific and artistic domains.
RHO–LSTM-based optimal scheduling at the motorcycle battery swapping station under battery heterogeneity Fauziah, Nisa Evi; Romdlony, Muhammad Zakiyullah; Muharam, Aam; Yakub, Fitri
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1172

Abstract

This research proposes a mechanism that enables the battery swapping station (BSS) to provide battery swap services for multiple types of batteries, termed battery heterogeneity, utilized in electric motorcycles. The number of batteries for each type is established. The battery charging cost is calculated in real time, and the station's profit is maximized by optimizing battery swap scheduling. The issues are modeled as a mixed-integer non-linear problem (MINLP), then linearized as a mixed-integer linear problem (MILP), using the grid electricity price from the real-time pricing mechanism to calculate the battery's charging/discharging cost. Swap scheduling is optimized using the rolling horizon optimization (RHO) approach, which takes into account a variety of constraints. These constraints include battery type, battery SoC, arrival time of the electric motorcycle, grid electricity pricing at time t, and battery power utilization. The long-short term memory (LSTM) predicts the electric motorcycles' arrival time at t+1 based on prior data. The results show that optimization scheduling generates a higher overall profit per day than unscheduled operation. Profit by the RHO-LSTM method is 23.77 % greater than by the RHO-Polynomial method and 0.26 % greater than by unscheduled operation. Furthermore, the number of batteries provided by the RHO-LSTM method is 40 % greater than by the RHO-polynomial method.
Optimizing bioethanol from sago dregs for Honai burner stoves: A case study in Papua Numberi, Johni Jonatan; Uniplaita, Tiper Korneles Muwarberto; Suwandi, Agri; Siregar, Januar Parlaungan; Ekayuliana, Arifia; Joni, Joni; Palamba, Pither; Liga, Marthen
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1053

Abstract

Indonesia harbors considerable prospects for bioethanol fuel generation. Underscoring the imperative for establishing optimal fuel concentrations and appropriate burners to facilitate sustainable energy alternatives; this study endeavored to identify the optimal bioethanol concentration sourced from sago waste for application in Honai burners, evaluating the resultant flame output for domestic energy in Papuan custom houses. This analysis adopted an integration of pre-experimental frameworks along with experimental ones. In the early trial stage, concentrations of bioethanol were thoroughly examined concerning low heat value (LHV), specific gravity, viscosity, gas chromatography, and Fourier transform infrared (FTIR) analysis to identify the best fuel characteristics. Following this, the experimental phase assessed flame characteristics, encompassing temperature, fuel mass flow rate, and emissions from combustion gases within the Honai burner. Pre-experimental findings suggest that an 80 % bioethanol concentration is ideal for the Honai burner, displaying a viscosity of 1.03 cP, a density of 0.82 g·L⁻¹, a gas chromatography content of 61.04 %, an LHV of 16.166 MJ/kg, and a heat release rate of 140 kW·m⁻². The experimental phase indicates that a 14-hole burner oriented at a 45° angle yields optimal performance, achieving stable flame temperatures between 480 °C and 750 °C with a fuel flow rate of 60 mL·min⁻¹. Analysis of combustion gases indicates minimal emissions, with carbon monoxide (CO) registering at 0.01 %, carbon dioxide (CO₂) at 0.2 %, and hydrocarbons (HC) at 27 ppm. In summary, this study offers a feasible approach to addressing energy challenges, meeting demand, enhancing accessibility, ensuring availability, and promoting regional energy autonomy for Papuan households in remote locales through the utilization of bioethanol derived from sago dregs in Honai burner cooking devices.
Front Cover MEV Vol 16 Iss 1 Pikra, Ghalya
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1268

Abstract

Artificial intelligence for field-oriented control on light rail transit Jabodebek Pribadi, Wahyu; Wicaksono, Ricto Yudi; Putra, Rakhmad Gusta; Wicaksono, Darma Arif; Yazid, Moh. Lutfi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1061

Abstract

The increasing number of vehicles in Jakarta, Indonesia, has had a negative impact on the environment. If this trend continues, it may significantly harm public health. In response to this issue, the government has introduced mass transportation solutions, such as the Jabodebek light rail transit (LRT) system. One of the key technical challenges in operating the LRT is ensuring smooth and reliable traction motor control. This study presents a simulation of the Jabodebek LRT’s traction motor performance when traversing a hilly route with a 29 ‰ gradient. A field-oriented control (FOC) method is implemented to regulate motor speed. The train operates under a constant load, with its weight gradually increasing from the lowest to the highest point of the slope. Two tuning methods are applied to optimize the controller parameters: manual (hand-tuning) and artificial intelligence-based optimization using the Firefly algorithm and the Grey Wolf optimizer (GWO). The integral of time multiplied by absolute error (ITAE) is used as the objective function to evaluate the speed control performance. The simulation results show that the Grey Wolf optimizer delivers the best performance, achieving stable speed control despite load disturbances. The optimal proportional and integral gains obtained are Kp = 16.233861 and Ki = 0.526774, respectively.
Preface MEV Vol 16 Iss 1 Pikra, Ghalya
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1269

Abstract

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