ALAT UKUR STAE OF CHARGE (SOC) BATERAI

Samabta, Faisal Wahyu and Hutama, Mochamad Aditya and Ohorella, Fauzan Fatur and Nugroho, Dicky Prasetyo (2024) ALAT UKUR STAE OF CHARGE (SOC) BATERAI. Undergraduate thesis, Universitas Muhammadiyah Malang.

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Abstract

Batteries are crucial devices in the implementation of renewable energy. They are
commonly used as storage technologies. One type frequently employed in
renewable energy systems is the Lead Acid battery. Since Lead Acid batteries are
rechargeable, the recharging process requires a well-designed system to ensure
effective battery management and prevent them from operating in conditions of
overcharge and overdischarge.
The Coulomb Counting method involves calculating the electrical charge entering
and leaving the battery. This calculation integrates the electric current flowing into
the battery over time. Coulomb Counting Variable Capacity works by implementing
an estimator using the Coulomb counting method. It takes as input the cell capacity
of the battery, which is then divided by the accumulated charge integrating the
battery current.The Kalman Filter is a type of autoregressive model used for
filtering, as it provides optimal estimation of the current condition based on optimal
estimation from previous system states and current observations. The Adaptive
Kalman Filter (AKF) is a variation of the standard Kalman Filter that adjusts its
internal parameters automatically according to observed changes in the system.
There are several methods to implement the Adaptive Kalman Filter, but the basic
idea involves updating filter parameters, such as process covariance matrix and
measurements, based on information obtained from observations and previous
estimation results.

Item Type: Thesis (Undergraduate)
Keywords: Batteries, Kalman Filter, Coloumb Counting, State of Charge
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering > Department of Electrical Engineering (20201)
Depositing User: 201810130311150 faisalwahyusamabta
Date Deposited: 16 Jul 2024 07:16
Last Modified: 16 Jul 2024 07:16
URI: https://eprints.umm.ac.id/id/eprint/8187

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