cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota adm. jakarta selatan,
Dki jakarta
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 596 Documents
 51   52   53   54   55 
Failure assessment in lithium-ion battery packs in electric vehicles using the failure modes and effects analysis (FMEA) approach Rizky Cahya Kirana; Nicco Avinta Purwanto; Nadana Ayzah Azis; Endra Joelianto; Sigit Puji Santosa; Bentang Arief Budiman; Le Hoa Nguyen; Arjon Turnip
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.94-104

Abstract

The use of batteries in electric cars comes with inherent risks. As the crucial component of these vehicles, batteries must possess a highly dependable safety system to ensure the safety of users. To establish such a reliable safety system, a comprehensive analysis of potential battery failures is carried out. This research examines various failure modes and their effects, investigates the causes behind them, and quantifies the associated risks. The failure modes and effect analysis (FMEA) method is employed to classify these failures based on priority numbers. By studying 28 accident reports involving electric vehicles, data is collected to identify potential failure modes and evaluate their risks. The results obtained from the FMEA assessment are used to propose safety measures, considering the importance of the potential failure modes as indicated by their risk priority number (RPN). The design incorporates safeguards against mechanical stress, external short circuits, and thermal runaway incidents. The findings of this study enhance our understanding of electric vehicle (EV) battery safety and offer valuable insights to EV manufacturers, regulators, and policymakers, aiding them in the development of safer and more reliable electric vehicles.
Back Cover MEV Vol 14 Iss 1 Ghalya Pikra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Back Cover MEV Vol 14 Iss 1
Design and implementation of capacitor array as DC converters for electrical lighting in limited area Arman Jaya; Irianto Irianto; Afif Aulia Rahman; Kyungmin Sung
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.80-86

Abstract

The widely used DC-DC converters are inductor-based DC-DC converters and inductors along with combustion. The use of inductors can lead to large power losses, as well as heavy components in real terms. The proposed converter warning array aims to increase the voltage with a large increase ratio through a switching configuration process. This switching method is very simple and uses two pulses that are opposite each other so that the array converter can work optimally, whose function is to adjust the arrangement in a parallel arrangement to a series arrangement. The advantage of using a device is that it makes DC-based DC conversion lightweight and easy to implement. Tests have been carried out on 5 hanger arrays with a power of 80 W and 65 W, and the data from the test results show that the voltage increase ratio reaches 81.5 % or 4.08 times the input voltage, which indicates that the array converter warning is able to increase the input voltage according to the number of the arrays.
Impact of road load parameters on vehicle COâ‚‚ emissions and fuel economy: A case study in Indonesia Kurnia Fajar Adhi Sukra; Heru Priyanto; Dedy Indriatmono; Muhamad Agus Wijayanto; Irfan Yahya Ikhsanudin; Yoga Akbar Ermansyah
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.87-93

Abstract

Carbon dioxide (CO2) contributes to the greenhouse effect and global warming. The Indonesian government has introduced a reduction in vehicle taxes based on the number of CO2 emissions, meaning that lower CO2 emissions result in lower tax rates. To measure the CO2 emissions, vehicle testing can be conducted on a chassis dynamometer using road load (R/L) parameters to assess the vehicle's loading during the test. The United Nations Economic Commission for Europe (UN ECE) Regulation no. 101 (R101) provides predefined table values for testing, but vehicle manufacturers can also provide their own R/L values, known as actual R/L. In this study, the vehicle underwent two tests: one using the R/L values from the standard table R101 and another using the actual R/L values provided by the manufacturer through coast-down results. By employing the actual R/L values, CO2 emissions can be reduced by up to 7.3 %. This reduction is achieved by lowering the vehicle's load by up to 17 % to enable optimal vehicle performance. Additionally, there is a potential improvement in fuel economy of up to 7.9 % for vehicles. These findings can serve as a reference for establishing future standard testing procedures.
Preface MEV Vol 14 Iss 1 Ghalya Pikra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Preface MEV Vol 14 Iss 1
An optimized stator and rotor design of squirrel cage induction motor for EMU train Hilda Luthfiyah; Okghi Adam Qowiy; Arga Iman Malakani; Dwi Handoko Arthanto; Fauzi Dwi Setiawan; Teddy Anugrah Ramanel; Gilang Mantara Putra; Syamsul Kamar; Asep Andi Suryandi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.35-46

Abstract

This paper aims to objectively calculate the 480-kW squirrel cage induction motor (SCIM) design for the electric multiple unit (EMU) trains. This is done by optimizing the stator slot and rotor slot design to get efficiency and power factor targets. The stator slot design is achieved by limiting the width and height of the stator slot pitch according to the specified range. A depth-to-width ratio is used according to the range to optimize the design of the rotor bar slot. The design process of the induction motor consists of three steps: it determines the specification design target, calculates the specified parameters of the induction motor, and simulates the design to obtain the most optimal motor design using ANSYS Maxwell. The simulation performance values obtained an efficiency of 92.547 % and a power factor of 0.915. This value is obtained from the optimization of the rotor slot and has met the minimum requirements of efficiency and power factor in designing a SCIM. The design proposed in this paper can be developed and applied in the Indonesian domestic railway manufacturing industry.
Artificial intelligence in smart grids: A bibliometric analysis and scientific mapping study Georgios Lampropoulos
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.11-34

Abstract

The realization of sustainable development and sustainable development goals achievement are essential. Hence, the power sector digitalization is imminent. This bibliometric and mapping study aims to explore the use of artificial intelligence in smart grids and how the topic has evolved over the years. In total, ten research questions are set to be explored. The analysis includes 1,926 articles that were identified and retrieved from Scopus and Web of Science (WoS) over the period 2005 to 2022. The analysis includes the descriptive statistics of the related studies and the annual scientific production, the identification of the most relevant and impactful authors, articles, outlets, affiliations, and countries, and the examination of the most commonly used keywords. The most popular topics and the advancement of the research focus are also explored. The study examines the results, discusses the main findings, presents open issues, and suggests new research directions. The significant role of artificial intelligence in the realization of smart grids and the digitalization of the power sector to enable sustainable development and the achievement of sustainable development goals was evident.
Appendix MEV Vol 14 Iss 1 Ghalya Pikra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Appendix MEV Vol 14 Iss 1
Analyzing the growth and trends of vertical axis wind turbine research: Insight from a bibliometric study Elysa Nensy Irawan; Nuur Wachid Abdul Majid; Liptia Venica; Fahrur Aslami; Goro Fujita
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.55-61

Abstract

Bibliometric analysis research has been done for vertical axis wind turbine (VAWT). This study aims to determine the growth of VAWT research, the number of VAWT studies in various countries and the most influential authors to find opportunities for research collaboration, and the challenges of future VAWT research. Research data was taken from Scopus in 1801 articles from 1970-2021. The software used for data interpretation was VosViewer 1.6.19 and Tableau Public 2022.2. Based on the analysis, VAWT research has tended to increase from 1970-2021, although there was a decrease from 1987-2006. The country that has conducted the most VAWT research is China, while the author with the highest number of citations is from Italy. The most dominant research topic related to VAWT research is computational fluid dynamics (CFD), which is 50.14 % of the total. A future challenge related to VAWT research is finding a suitable turbulence model for each type of VAWT or finding an airfoil optimization method so that a model with betterperformance is obtained. Opportunities for research collaboration can be carried out with China or an author with the highest number of citations who has expertise in the field of CFD.
LSTM-based forecasting on electric vehicles battery swapping demand: Addressing infrastructure challenge in Indonesia Muhammad Zakiyullah Romdlony; Rashad Abul Khayr; Aam Muharam; Eka Rakhman Priandana; Sudarmono Sasmono; Muhammad Ridho Rosa; Irwan Purnama; Amin Amin; Ridlho Khoirul Fachri
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.72-79

Abstract

This article aims to design a model for forecasting the number of vehicles arriving at the battery swap station (BSS). In our case, we study the relevance of the proposed approach given the rapid increase in electric vehicle users in Indonesia. Due to the vehicle electrification program from the government of Indonesia and the lack of supporting infrastructure, forecasting battery swap demands is very important for charging schedules. Forecasting the number of vehicles is done using machine learning with the long short-term memory (LSTM) method. The method is used to predict sequential data because of its ability to review previous data in addition to the current input. The result of the forecasting using the LSTM method yields a prediction score using the root-mean-square error (RMSE) of 2.3079 x 10-6 . The forecasted data can be combined with the battery charging model to acquire predicted hourly battery availability that can be processed further for optimization and scheduling.

Page 53 of 60 | Total Record : 596

 51   52   53   54   55 

Filter by Year

2010 2025


Reset
Filter By Issues
All Issue Vol 16, No 1 (2025) Vol 15, No 2 (2024) Vol 15, No 1 (2024) Vol 14, No 2 (2023) Vol 14, No 1 (2023) Vol 13, No 2 (2022) Vol 13, No 1 (2022) Vol 12, No 2 (2021) Vol 12, No 1 (2021) Vol 11, No 2 (2020) Vol 11, No 1 (2020) Vol 10, No 2 (2019) Vol 10, No 1 (2019) Vol 9, No 2 (2018) Vol 9, No 1 (2018) Vol 8, No 2 (2017) Vol 8, No 1 (2017) Vol 7, No 2 (2016) Vol 7, No 1 (2016) Vol 6, No 2 (2015) Vol 6, No 1 (2015) Vol 5, No 2 (2014) Vol 5, No 1 (2014) Vol 4, No 2 (2013) Vol 4, No 1 (2013) Vol 3, No 2 (2012) Vol 3, No 1 (2012) Vol 2, No 2 (2011) Vol 2, No 1 (2011) Vol 1, No 2 (2010) Vol 1, No 1 (2010) More Issue