Due to the more vigorous regulations on carbon gas emissions and fuel economy, Fuel cell electric vehicles (FCEV) are becoming more popular in the automobile industry. This paper presents a neural network-based maximum power point tracking (MPPT) controller for 1.26-kW proton exchange membrane fuel cell (PEMFC), supplying electric vehicle powertrain through a high voltage-gain dc–dc boost converter. The proposed neural network MPPT controller uses a radial basis function network (RBFN) algorithm for tracking the maximum power point of the PEMFC. High switching-frequency and high voltage-gain dc–dc converters are essential for the propulsion of FCEV. In order to attain high voltage-gain, a three-phase high voltage-gain interleaved boost converter is also designed for FCEV system. The interleaving technique reduces the input current ripple and voltage stress on the power semiconductor devices. The performance analysis of the FCEV system with RBFN-based MPPT controller is compared with the fuzzy logic controller in MATLAB/Simulink platform.

High Voltage Gain Interleaved Boost Converter With Neural Network Based MPPT Controller for Fuel Cell Based Electric Vehicle Applications

ANFIS-MPPT control algorithm for a PEMFC system used in electric vehicle applications

Energy structures from non-conventional energy source has become highly demanded nowadays. In this way, the maximum power extraction from photovoltaic (PV) systems has attracted the attention, therefore an optimization technique is necessary to improve the performance of solar systems. This article proposes the use of ABC (artificial bee colony) algorithm for the maximum power point tracking (MPPT) of a PV system using a DC-DC converter. The procedure of the ABC MPPT algorithm is using data values from PV module, the P-V characteristic is identified and the optimal voltage is selected. Then, the MPPT strategy is applied to obtain the voltage reference for the outer PI control loop, which in turn provides the current reference to the predictive digital current programmed control. A real-time and high-speed simulator (PLECS RT Box 1) and a digital signal controller (DSC) are used to implement the hardware-in-the-loop system to obtain the results. The general system does not have a high computational cost and can be implemented in a commercial low-cost DSC (TI 28069M). The proposed MPPT strategy is compared to the conventional perturb and observe method, results show the proposed method archives a much superior performance.

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MPPT Algorithm Based on Artificial Bee Colony for PV System

In this paper, a radial basis function network-based single maximum power point tracking (MPPT) control algorithm for a hybrid solar and wind energy system is designed and analyzed for standalone and grid connected applications. The extraction of maximum power from the intermittent and erratic nature renewable energy sources is the main target in the hybrid renewable energy system. In the literature, many researchers developed an individual MPPT control algorithm for solar and wind energy system, which in turn increases the number of control algorithms in a hybrid system. In this paper, a single MPPT controller is proposed to extract maximum power from both the sources simultaneously. The performance of the proposed MPPT control algorithm is analyzed in both standalone and grid connected modes, under different weather conditions. The hybrid renewable energy system is designed by considering 560-W photovoltaic system and 500-W wind system with the conventional boost converter, and it is simulated in MATLAB/Simulink environment to analyze the performance of the proposed MPPT controller.

Design and Analysis of RBFN-Based Single MPPT Controller for Hybrid Solar and Wind Energy System

In this research paper, a firefly asymmetrical fuzzy logic controller (FAFLC) based unified maximum power point tracking (MPPT) hybrid controller is proposed for grid connected power system. It is a combination of solar, wind and fuel based energy power system. The FAFLC based heuristics optimized MPPT algorithm depends on intensity of light followed by inverse square law which improves the dynamic uncertainty under complex and transient weather conditions. Also duty ratio of the cuk converter has been decided according to the position of firefly. The proposed MPPT controller works efficiently in dynamic conditions like variable solar irradiance, hydrogen consumption and wind speed which tracks high power and able to find global maximum power point (MPP). The experimental validation has been done through dSPACE DS 1104 real time control board.

https://www.ijrer.com/index.php/ijrer/article/download/6131/pdf

A Hybrid Firefly-Asymmetrical Fuzzy Logic Controller based MPPT for PV-Wind-Fuel Grid Integration

This paper proposes an integrated Cuk-SEPIC converter for standalone hybrid wind and photo voltaic (PV) system. The proposed converter is developed by sharing the converter components between Cuk and SEPIC converters and it operates in both individual and simultaneous modes, based on the availability of source and eliminates the need of input filter to suppress the high frequency harmonics. Therefore, it has the advantage of simple structure and reduced converter components.Â  The proposed converter is designed and then analyzed for the hybrid wind and PV system. This study considers a 1.8 KW wind system and a 2 KW PV system with maximum power point tracking (MPPT) algorithms of incremental conductance plus integral control and perturbs & observes methods for wind and PV system respectively. The effectiveness of the proposed converter is validated using the simulation results and usage of the converter based on availability of the renewable energy sources is presented.

https://www.ijrer-net.ijrer.org/index.php/ijrer/article/download/5078/pdf

Design and Analysis of an Integrated Cuk-SEPIC Converter with MPPT for Standalone Wind/PV Hybrid System

Coordinated MPPT and DPC Strategies for PMSG based Grid Connected Wind Energy Conversion System

In this paper, analysis an integrated Boost-Cuk converter with RBFN based MPPT technique has been presented for the solar PV application. In renewable energy sources, extracting maximum power and boosting the voltage to the desired level with low stress on power semiconductor switches are the main two main targets. The developed converter utilizes a single control switch for obtaining the higher transfer gain (M), compared to the conventional Boost and Cuk individual converter gains. This study considers a 568W PV panel and the MATLAB/Simulation results are presented to validate the effectiveness of the integrated converter with the RBFN based MPPT control system.

K. R. Prabhu

Papers

Design and Analysis of RBFN-Based Single MPPT Controller for Hybrid Solar and Wind Energy System

Design and Analysis of an Integrated Cuk-SEPIC Converter with MPPT for Standalone Wind/PV Hybrid System

Coordinated MPPT and DPC Strategies for PMSG based Grid Connected Wind Energy Conversion System

Analysis of integrated Boost-Cuk high voltage gain DC-DC converter with RBFN MPPT for solar PV application

Analysis of MISO Super Lift Negative Output Luo Converter with MPPT for DC Grid Connected Hybrid PV/Wind System