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Mechatronics, Electrical Power, and Vehicular Technology
ISSN : 20873379     EISSN : 20886985     DOI : -
Core Subject : 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.
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Articles 613 Documents
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

Real-time FFB ripeness detection using IoT-enabled YOLOv8n on Raspberry Pi 4 edge devices for precision agriculture Nurul Hazlina Noordin; Rosdiyana Samad; Abdul Haikal Abdul Malek
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1220

Abstract

This paper presents the development of an edge device for cost-effective implementation in agricultural environments. Experimental evaluations demonstrate accuracy and real-time performance, showcasing its potential for adoption in the industry. The proposed system provides a reliable tool for timely and accurate monitoring of fresh fruit bunch (FFB) ripeness, facilitating optimized crop management practices. The system employs the YOLOv8n model, renowned for its efficiency in real-time object detection tasks, and is adapted to run on the resource-constrained Raspberry Pi 4. To ensure seamless operation on edge devices, model optimization techniques such as quantization and hardware acceleration are implemented, enabling rapid decision-making based on live data feeds. A dataset comprising 4,194 annotated FFB images was utilized, with a [3,681:348:165] training-validation-test split. Performance evaluation demonstrated an average precision of 0.898 and a mean average precision (mAP) of 0.952. The system potentially enhances yield quality and sustainability while supporting data-driven decision-making in precision agriculture.
Enhanced outdoor localization of low-cost personal mobility vehicles using Extended Kalman Filter sensor fusion Vita Susanti; Mohd Saiful Azimi Mahmud; Roni Permana Saputra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1294

Abstract

Personal mobility vehicles (PMVs) are gaining popularity for short urban trips, reducing car reliance and urban pollution. The development of autonomous PMVs heavily relies on accurate localization, often using the global positioning system (GPS) as a primary sensor. However, standard GPS suffers from poor accuracy, which requires data fusion with supplementary sensors to improve precision. This study presents a sensor fusion approach using low-cost, consumer-grade hardware to enhance the PMV localization. The fusion system integrates data from an inertial measurement unit (IMU) and wheel odometry with GPS, fusing them via Kalman Filter (KF) and Extended Kalman Filter (EKF) methods. A field experiment was conducted along a 67-meter route at velocities ranging from 0.25 to 1.23 m/s. Comparative analysis has shown that the EKF method consistently outperforms the standard KF, improving positioning accuracy by approximately 29 % and reducing the maximum deviation to a range of 1.8 m to 2.7 m across different velocities. The results have confirmed the EKF as an effective and reliable strategy for achieving high-precision localization with affordable sensors, a key step towards scalable autonomous navigation for PMVs.
Back Cover MEV Vol 16 Iss 2 Ghalya Pikra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1400

Abstract

Design and implementation of a DC-DC buck converter with Type III compensator control Fahmizal Fahmizal; Muhammad Rizal Sahiddin; Priyo Herlambang; Gibran Nabil Sentana; Hari Maghfiroh
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1321

Abstract

This paper presents a low-cost hardware realization of a Type III compensated DC–DC buck converter with experimental validation under practical load conditions. The compensator is designed using MATLAB Bode plot analysis to achieve the target phase margin, and the resulting pole–zero configuration is verified through LTspice simulation before implementation on a microcontroller-based hardware prototype. Performance testing is conducted under both resistive and DC motor loads to evaluate improvements over an open-loop configuration. Experimental results show that the proposed closed-loop design significantly accelerates transient recovery, reducing settling time from 85–134 ms in the open-loop system to 0.39–5.2 ms in the compensated system, representing improvements of up to two orders of magnitude depending on the load. The closed-loop converter also achieves tighter steady-state regulation around 6 V and smaller effective voltage dips during load transients, confirming the effectiveness of the Type III compensator in enhancing both dynamic and steady-state performance. The implementation demonstrates a practical and cost-efficient approach for applying Type III compensation on low-cost hardware platforms suitable for educational and prototype-level power electronics applications.