Open AccessEstimation of Soc and Soh Using Mixed Neural Network and Coulomb Counting Algorithm
Author(s) -
Abhash Ganeshan,
R Shanmughasundaram
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j1308.0881019
Subject(s) - battery (electricity) , laptop , computer science , state of charge , artificial neural network , voltage , electrical engineering , power (physics) , backup , algorithm , engineering , artificial intelligence , physics , quantum mechanics , database , operating system
The Lithium ion battery is widely used in most of the battery powered electronics and automotive products like mobile phones, laptop, wall watch, calculator and other. The Battery provides power to devices with the facility of movability. On the other hand, it also provides power backup to devices. The Battery State of charge (SOC) and state of health (SOH) are the key terms by which the available charge and its life span can be estimated. In this paper, SOC is estimated using a backpropagation neural network with 3 inputs namely, voltage, current, and temperature of the battery. Coulomb counting method is used to find the new or remaining capacity of the battery which will notify about its SOH. The whole setup is implemented in PIC16F877A with the voltage, current and temperature sensors.