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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO JTT (Jurnal Teknologi Terpadu) JAREE (Journal on Advanced Research in Electrical Engineering)
Suhariningsih Suhariningsih
Politeknik Elektronika Negeri Surabaya
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering

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Estimation of State of Charge (SoC) Using Modified Coulomb Counting Method With Open Circuit Compensation For Battery Management System (BMS) Puspita Ningrum; Novie Ayub Windarko; Suhariningsih Suhariningsih
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 5, No 1 (2021): April
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v5i1.150

Abstract

Battery is one of the important components in the development of renewable energy technology. This paper presents a method for estimating the State of Charge (SoC) for a 4Ah Li-ion battery. State of Charge (SoC) is the status of the capacity in the battery in the form of a percentage which makes it easier to monitor the battery during use. Coulomb calculations are widely used, but this method still contains errors during integration. In this paper, SoC measurement using Open Circuit Voltage Compensation is used for the determination of the initial SoC, so that the initial SoC reading is more precise, because if the initial SoC reading only uses a voltage sensor, the initial SoC reading is less precise which affects the next n second SoC reading. In this paper, we present a battery management system design or commonly known as BMS (Battery Management System) which focuses on the monitoring function. BMS uses a voltage sensor in the form of a voltage divider circuit and an ACS 712 current sensor to send information about the battery condition to the microcontroller as the control center. Besides, BMS is equipped with a protection relay to protect the battery. The estimation results of the 12volt 4Ah Li-ion battery SoC with the actual reading show an error of less than 1%.Keywords: battery management system, modified coulomb counting, state of charge
Perbandingan Performa Metode Maximum Power Point Tracking Human Psychology Optimization (HPO), Artificial Bee Colony (ABC) dan Fuzzy Logic Controller (FLC) pada Flyback Converter Kondisi Parsial Shading Moh. Zaenal Efendi; Mochammad Rody Dwirantono; Suhariningsih Suhariningsih; Lucky Raharja
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1022.2023

Abstract

Maximum Power Point Tracking (MPPT) is a method to track the power point of an energy source with the intention to generate maximum power. The surface of the Solar Panel has the possibility of being blocked when it receives sunlight. The barrier can be in the shape of shadows of objects that are nearby solar panels. The problem causes the power generated to be not optimal and makes more than one MPPT peak on the characteristics of P-V. This paper compares several methods of MPPT such as Human Psychology Optimization (HPO), Artificial Bee Colony (ABC), and Fuzzy logic Controller (FLC) under partial shading conditions, the comparison of three method by simulation. This algorithm hooks up to a flyback converter to provide MPP. From the results of MPPT accuracy in partial shading situations, the ABC and HPO approach methods can achieve GMPP with more than 82.22 % accuracy. For convergence, ABC needs extra time to discover GMPP. From the results, the Fuzzy approach can track however nevertheless trapped on LMPP.
Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid Dimas Okky Anggriawan; Epyk Sunarno; Eka Prasetyono; Suhariningsih Suhariningsih; Muhammad Fauzi
Jurnal Teknologi Terpadu Vol 11, No 2 (2023): JTT (Jurnal Teknologi Terpadu)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jtt.v11i2.1869

Abstract

A microgrid is a cluster of electrical sources and loads that are interconnected and synchronized. Microgrid operation is typically divided into two modes, isolated or connected to the grid with a single or standalone control system. In this context, it can enhance the reliability and quality of electricity supply for connected customers. When using a microgrid system, it is important to consider the risk of series arc faults. Series arc faults are sudden bursts of flames resulting from ionization of gas between two electrode gaps. These faults can occur due to manufacturing defects, installation Errors, aging, or corrosion on conductor rods, leading to imperfect connections. Detecting series arc faults in DC microgrid system operations can be challenging using standard protective devices. Failure in the protection system can pose risks of fire, electrical shock hazards, and power loss in the DC microgrid.Therefore, a device has been designed to detect series arc faults by utilizing the fast Fourier transform method and artificial neural network, which function to analyze DC signal and make decisions when faults occur by examining the average sum of current frequency values during normal and fault conditions. In this study, the average sum of current frequency values during normal conditions was found to range from 0.35437 to 0.36906 A, while during fault conditions, it ranged from 0.21450 to 0.22793 A, with an average protection identification time of 1087 ms and an ANN output accuracy of 99.98%.
Multi-step constant current-constant voltage charging method to improve CC-CV method on lead acid batteries Mochamad Ari Bagus Nugroho; Ahmad Dzihan Alifi; Suhariningsih Suhariningsih; Epyk Sunarno; Eka Prasetyono; Dimas Okky Anggriawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.25968

Abstract

Constant current-constant voltage (CC-CV) is one of the battery charging methods that is commonly used. However, this method has several drawbacks, including the charging current in constant current (CC) mode, which can only be set to a maximum of 0.3 C on lead acid batteries, resulting in a relatively long charging duration. Therefore, in this research, the multi-step constant current-constant voltage (MCC-CV) method of battery charging system is developed where this method can use a greater charging current, resulting in a significant reduction in charging duration by using multiple current setpoints in MCC mode, with the initial setpoint current can be set beyond 0.3 C, which is 0.34 C in this system. This system uses a DC-DC single-ended primary inductance converter (SEPIC) converter as a battery charging control system, equipped with a power cut-off relay when the charging current reaches 0.05 C in constant voltage (CV) mode. From the test results obtained, the MCC-CV method can charge the battery to its full capacity faster than the CC-CV method with a difference of 15.34 minutes and the relay on the system can work properly.
Comparison of Buck and Synchronous Buck Converters for ANFIS-Controlled Li-Ion Fast Charging SUHARININGSIH SUHARININGSIH; EPYK SUNARNO; EKA PRASETYONO; MOCHAMAD ARI BAGUS NUGROHO; KHAFIDZ BAYHAQI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 3: Published July 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i3.228

Abstract

The research discusses the implementation of a fast charging system on Lithium-Ion batteries by comparing the performance of conventional Buck Converters and Synchronous Buck Converters. Charging is carried out using constant current (CC) and constant voltage (CV) methods with set points of 4A and 16.8V as the targets used, and is equipped with sensors to monitor voltage and current during the charging process. The system is controlled by the Adaptive Neuro Fuzzy Inference System (ANFIS) which is useful for maintaining charging stability at one battery specification with a full capacity of 4.2V voltage and 4A current. Test results show that ANFIS is able to maintain filling parameters within safe limits. In addition, the Synchronous Buck Converter provides better efficiency than conventional Buck Converters in terms of efficiency and controlling voltage fluctuations, so it is more optimal for use in Lithium-Ion battery fast charging systems.
Co-Authors Abel Aditya Aryaguna Ahmad Dzihan Alifi Dimas Okky Anggriawan Eka Prasetyono, Eka Epyk Sunarno KHAFIDZ BAYHAQI Lucky Raharja MOCHAMAD ARI BAGUS NUGROHO MOCHAMMAD RODY DWIRANTONO Mohammad Zaenal Efendi Muhammad Fauzi Novie Ayub Windarko Puspita Ningrum