Design of charging system with the elimination of electric arc during switching off

Kellner, Jakub; Prazenica, Michal

doi:10.1109/elektro49696.2020.9130263

Cited by 2 publications

(1 citation statement)

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“…The trained ANN implemented to the control system (microcontroller) controls the switching converter with the requested current I* to create the optimal load for the PV panels to achieve maximum charging performance. Reference current signal is internally converted into the pulse width modulation (PWM) signals used to switching MOSFET transistors in switching converter [9][10]. The ANN controls the converter with using of PV panel voltage, PV panel current and PV panel temperature signals.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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

Morgos¹,

Klco²,

Hrudkay³

2022

Komunikácie

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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.

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Section: Theoretical Backgroundmentioning

confidence: 99%