Fuzzy Based Interleaved Step-up Converter for Electric Vehicle

This work focuses on the fuzzy controller for the proposed three-phase interleaved Step-up converter(ISC).The fuzzy controller for the proposed ISC converters for electric vehicles has been discussed in detail.The proposed ISC direct current(DC-DC)converter could also be used in automobiles,satellites,industries,and propulsion.To enhance voltage gain,the proposed ISC Converter combines boost converter and interleaved converter(IC).This design also reduces the number of switches.As a result,ISC converter switching losses are reduced.The proposed ISC Converter topology can produce a 143 V output voltage and 1 kW of power.Due to the high voltage gain of this converter design,it is suitable for medium and high-power systems.The proposed ISC Converter topology is simulated in MATLAB/Simulink.The simulated output displays a high output voltage.But the output voltage contains maximum ripples.Fuzzy proposes an ISC Converter which makes closed loop responsiveness and reduces the output voltage ripple.The proposed ISC converter has the lowest ripple output voltage,which is less than 2%,because the duty cycle is regulated using the fuzzy logic controller.It offers high voltage gain,minimal ripple,and low switching loss.The performance of the proposed converter is compared to that of the fuzzy and Pro-portional Integral(PI)controllers implemented in MATLAB.

Improved Interleaved Single-Ended Primary Inductor-Converter forSingle-Phase Grid-Connected System

The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.

Weight and Efficiency Optimized DC/DC Converter Based on Multiple Interleaved Channels

Today, energy saving is one of the main objectives for engineers. In the case of mobile applications, energy can be saved by two different ways： decreasing the total masse of the system and increasing the efficiency of the overall system. This paper presents two optimization strategies to design a predefined multichannel structure of a boost converter which is dedicated to a solar airplane and used to interface PV panels and the battery system. The first strategy is a multi-criterion method that is able to trace the dependency between the converter＇s efficiency and its power density through the intermediary of the Pareto front. The second method, a mono-criterion approach, maximizes efficiency while respecting the constraint imposed on power density. The mono-criterion method that is applied to maximizing the European efficiency criterion showed that an increase in the number of channels enhanced the quantity of energy collected over a day by increasing the power density of the converter. At the end of the paper, the optimal design calculated was built to give an example of the result obtained by this design methodology. The results of the efficiency measurements made on a realized prototype are presented in this paper.

Design and Experimentation of FPGA-Based Soft-Switched Interleaved Boost Converter for Telecommunication System

This paper proposes the design and experimentation of digital control of soft-switched interleaved boost converter using FPGA for Telecommunication System. The switching devices in the proposed converter are turned on and off with Zero Voltage Switching (ZVS) and Zero Current Switching (ZCS) respectively. The circuit is operated in Continuous Conduction Mode (CCM) with various load ranges having duty cycle of more than 50%. The proposed converter is studied by developing the simulation module in MATLAB/SIMULINK. A PI controller is designed and implemented in FPGA to obtain a regulated DC output for line and load variations. Simulation and experimentation results are verified with a prototype development of the proposed converter. The results indicate that the converter performance is enhanced with closed loop control.

Interleaved high-gain boost converter powered by solar energy using hybrid-based MPP tracking technique

This paper presents a solar-powered interleaved high-gain boost converter(IHGBC)that increases voltage gain with fewer ripples in the output voltage in comparison to existing DC-DC converters.The goal of this research is to develop a hybrid-based maximum power point tracking(MPPT)approach with the combination of a flower pollination(FP)algorithm assisted with a perturb&observe(P&O)MPPT approach for solar photovoltaic(SPV)systems integrated with IHGBC.To ensure effective usage of both FP and P&O algorithms,this study incorporates and validates the hybrid-based MPPT approach.The proposed solar-powered IHGBC with a hybrid-based MPPT algorithm has been computationally modelled and simulated using MATLAB®and Simulink®for both uniform and non-uniform irradiation and analysed for voltage gain,ripples in the output waveforms and convergence time.The proposed hybrid-based MPPT is based on a number of flowers that forecast the initial global peak,assisted by P&O in the last stage for faster convergence to attain the maximum power point(MPP).As a result,the hybrid-based MPPT approach alleviates the computational issues encountered in P&O and FP-based MPP approaches.The proposed hybrid MPPT is compared with conventional MPPT for SPV and the results show that the solar-powered IHGBC using a hybrid-based MPPT technique has negligible oscillations of 0.14%with a high-voltage gain of 7.992 and a fast convergence rate of 0.05 seconds compared to individual P&O-based MPPT and FP-based MPPT techniques.The simulation results of the proposed MPPT with IHGBC outperform the conventional MPPT with high-gain converters.

A Correlative Study of Perturb and Observe Technique and GA-RBF-NN Method Supplying a Brushless DC Motor

A comparative study is done in regards to the performance of the popular Perturb and Observe algorithm and the Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) algorithm, both incorporating the Interleaved Boost converter. The Perturb and Observe method (P&O) is inarguably the most commonly used algorithm as its advantages pertaining to its ease in implementation and simplicity enable to track the Maximum Power Point (MPP). However, it is absolutely unreliable when subjected to rapidly fluctuating irradiation and temperature levels. More importantly, the system has the tendency to swing back and forth about the Maximum Power Point without reaching stability. At this juncture, the implementation of the Genetic-Assisted Radial Basis Function (GA-RBF) algorithm helps the system achieve MPP at a shorter time when compared to the Perturb and Observe technique. The ever reliable and robust Levenberg-Marquardt algorithm is included along with the MPPT controller that minimizes the Mean Square Error (MSE) and aids in faster training of the neural network. This PV system drives a brushless DC motor (BLDC), employing rotor position sensors.