RT Journal Article
SR Electronic
A1 Morgoš, Ján
A1 Klčo, Peter
A1 Hrudkay, Karol
T1 Artificial Neural Network Based Mppt Algorithm for Modern Household with Electric Vehicle
JF Communications - Scientific Letters of the University of Zilina
YR 2022
VO 24
IS 1
SP C18
OP C26
DO 10.26552/com.C.2022.1.C18-C26
UL https://komunikacie.uniza.sk/artkey/csl-202201-0025.php
AB This paper deals with implementation of artificial neural network in the maximum power point tracking (MPPT) controller algorithm for modern household where electric vehicle (EV) was purchased. The proposed MPPT algorithm was designed to achieve the best possible efficiency of the MPP (maximum power point) tracking and the best possible energy harvesting to charge the EV's battery. The artificial neural networks have strong advantage in fast input to output response of signals and the finding of MPP is faster than in commonly used algorithms. In this article, the optimised simulation model based on artificial neural network will be introduced. The proposed artificial neural network algorithm was designed for non-shielded photovoltaic panels.