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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) JOIV : International Journal on Informatics Visualization
Baharom, Rahimi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Investigating power quality issues in electric buggy battery charger systems: analysis and mitigation strategies Bunyamin, Wan Muhamad Hakimi Wan; Muhamad, Samshul Munir; Saidon, Wan Salha; Baharom, Rahimi
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2534-2544

Abstract

This paper investigates power quality issues in the battery charger system of an electric buggy. Key power quality parameters such as total harmonic distortion (THD), power factor (PF), input voltage, and input current, were measured and analyzed during the charging process. The findings reveal significant power quality challenges, with THD levels exceeding IEEE 519 standards, indicating inefficiencies and potential risks such as increased heating and stress on charger components. Power factor readings reveal a substantial reactive power component, further contributing to inefficiency. To address these issues, the study recommends implementing harmonic mitigation techniques, such as passive and active filters, to reduce THD levels, using power factor correction methods, and optimizing charging algorithms to manage power demand more effectively. Continuous monitoring of charging parameters is essential for maintaining optimal performance and reliability. Adhering to standards is crucial for the efficient and reliable operation of electric vehicle (EV) charging systems, with regular compliance testing and benchmarking necessary to identify improvement areas and maintain a high-quality charging infrastructure. The proposed solutions aim to develop a sustainable and efficient charging system for electric buggies, providing valuable insights and recommendations for future research and development in power electronics and drive systems for EV applications.
MLP-NARX Bitcoin Price Prediction Model Integrating System Identification Modelling Principles Farhan Nasarudin, Muhammad Nazrin; Yassin, Ihsan Mohd; Megat Ali, Megat Syahirul Amin; Adzhar Mahmood, Mohd Khairil; Baharom, Rahimi; Rizman, Zairi Ismael
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.943

Abstract

Bitcoin is a decentralized digital currency that enables people to exchange value without requiring a third-party intermediary. Due to its many advantages, it has received much interest from institutional and individual investors. Despite its meteoric increase, the price of Bitcoin extremely volatile asset class as it purely relies on supply and demand. This presents an interesting opportunity to create a forecasting model. However, many research papers in this area does not analyse the residuals as part of the forecasting resulting in potentially biased models. In this paper, we demonstrate System Identification (SI) residual analysis techniques to the analysis of our forecasting model. The Multi-Layer Perceptron (MLP) Nonlinear Autoregressive with Exogeneous Inputs (NARX) uses historical price data and several technical indicators to predict the future price movements of Bitcoin. The Particle Swarm Optimization (PSO) algorithm was used to find optimal parameters for the model. The model was able to predict one day ahead price in the prediction test. The model has successfully captured the dynamics of the data through the tests performed on residuals. It is also proving the randomness of residuals, albeit some minor violations.
Co-Authors Abdul Munim, Wan Noraishah Wan Abidin, Ahmad Farid Adzhar Mahmood, Mohd Khairil Ahmad, Ahmad Sukri Bunyamin, Wan Muhamad Hakimi Wan Che, Hang Seng Farhan Nasarudin, Muhammad Nazrin Ghazali, Mohd Shukri Mohd Hannoon, Naeem M. S. Hashim, Norazlan Hayat, Muhammad Amirul Ashraf Zarrul Hayroman, Muhammad Hakiem Hidayat, Muhamad Nabil Megat Syahirul Amin Megat Ali Mohamad Elias, Mohamad Fathi Mohd Jamhari, Muhammad Khairul Azman Muhamad, Samshul Munir Muhammad, Khairul Safuan Munim, Wan Noraishah Wan Abdul Nooradzianie Muhammad Zin Othman, Muhammad Murtadha Rahman, Nor Farahaida Abdul Rawi, Muhammad Shawwal Mohamad Rizman, Zairi Ismael Saidon, Wan Salha Wan Abdul Munim, Wan Noraishah Yassin, Ihsan Mohd Zainuri, Muhammad Ammirrul Atiqi Mohd Zolkiffly, Mohd Zaid