Open AccessParallel Balancing Battery using Adaptive Power Sharing and ANN SOC Estimator
Author(s) -
Mokhamad Zuhal Muflih,
Gilang Andaru Trinandana,
Eka Prasetyono,
Dimas Okky Anggriawan
Publication year - 2021
Publication title -
jurnal rekayasa elektrika
Language(s) - English
Resource type - Journals
eISSN - 2252-620X
pISSN - 1412-4785
DOI - 10.17529/jre.v17i3.20671
Subject(s) - battery (electricity) , state of charge , computer science , power (physics) , estimator , matlab , voltage , artificial neural network , electrical engineering , automotive engineering , engineering , mathematics , statistics , physics , quantum mechanics , operating system , machine learning
The battery balancing method is commonly used in cell circuits and battery circuits to maintain the power continuity on the DC Bus. The power continuity on the DC Bus is guaranteed if the load continues to get a power source, even if either the battery or power supply malfunctions. Besides, the battery balancing method is also used to protect the battery from excessive charging current pliers flowing into the battery. Therefore, the State-of-Charge (SoC) should be concern in balancing the maintained battery condition on both systems and avoiding overcharging. Artificial Neural Network (ANN) is used in this paper to determine the value of battery SoC. Based on simulations using MATLAB 2018, SoC values with ANN showed accurate results with error values below 0.1%. Based on the simulation results, the two batteries, which are arranged to have a difference of SoC value of 0.3%, will achieve a balanced SoC value for 28.45 seconds from the simulation.