Communications - Scientific Letters of the University of Zilina 2022, 24(1):C18-C26 | DOI: 10.26552/com.C.2022.1.C18-C26

Artificial Neural Network Based Mppt Algorithm for Modern Household with Electric Vehicle

Ján Morgoš ORCID...1, Peter Klčo ORCID...1, Karol Hrudkay ORCID...1
University Scientific Park, University of Zilina, Zilina, Slovakia

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.

Keywords: artificial neural network, MPPT algorithm, electric vehicle, battery, photovoltaic, (photo-voltaic) PV panel, high efficiency
Grants and funding:

This publication was realized with support of Operational Program Integrated Infrastructure 2014 - 2020 of the project: Innovative Solutions for Propulsion, Power and Safety Components of Transport Vehicles, code ITMS 313011V334, co-financed by the European Regional Development Fund.

Received: May 24, 2021; Accepted: August 23, 2021; Prepublished online: November 24, 2021; Published: January 1, 2022  Show citation

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Morgoš, J., Klčo, P., & Hrudkay, K. (2022). Artificial Neural Network Based Mppt Algorithm for Modern Household with Electric Vehicle. Communications - Scientific Letters of the University of Zilina, 24(1), C18-26. doi: 10.26552/com.C.2022.1.C18-C26
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