Single Level Inverter Research Articles

Modeling of A Single Phase 7-Level Cascaded H-Bridge Multilevel Inverter

Recently, almost all industrial devices are mostly built on electronic devices which are precisely sensitive to harmonic. In order to meet the requirement from the industries demand aimed at a free-harmonics and high power rating source is remarkably increased in past few years. An inverter which a device or electric circuit that convert direct current to alternating current is one of the electronic devices that give concern to researchers for improvement of generating a neat power source. The inverter can be categorized into a single level and multilevel inverter. As compared to single level inverter, multilevel inverter offers minimum harmonic distortion and higher power output. This paper presents a model of multilevel inverter using 7-level Cascaded H-Bridge of multilevel DC-AC inverter to reduce total harmonic distortion with different sinusoidal pulse width modulation such as phase disposition and phase opposition disposition. Simulation output of single phase multilevel inverter cascaded H-bridge are analysed and verified in the Matlab/Simulink software. The result show that the 7-level cascaded H-Bridge multilevel inverter with phase disposition technique generate less total harmonic distortion if it is compared to the phase opposition disposition technique.

Investigation into spectral characteristics of multilevel semiconductor inverters

Calculation of spectral characteristics is investigated, and the harmonic distortion of the output voltage of a single-phase three-level voltage inverter is determined. It is shown that the application of multilevel inverters makes it possible to decrease the harmonic distortion over the entire control region of the output voltage compared with a single-level inverter.

Simulation of SPWM in Three-Phase Inverter Based on LabVIEW and Multisim

This paper presents simulation of a three-phase single-level inverter. The inverter is designed to be fed into the power grid. State-space model and sinusoidal PWM technique are described in this paper. The simulation is based on Multisim and LabVIEW co-simulation. This method of SPWM simulation has some software and harmonic which must be taken into account while using it in the real power grid. Efforts are underway to improve the three-phase single-level inverter.

Design of Control Secheme and Performance Improvement for Multilevel Dc Link Inverter Fed PMBLDC Motor Drive

PMBLDC motors are gaining a lot of popularity due to their high efficiency as the Permanent Magnets do not carry current which results in negligible copper losses as compared to asynchronous motors. This paper introduces a design for speed control of the PMBLDC motor using multilevel dc link inverter fed by a Boost Converter. The multilevel dc link inverter consist of five level voltage sources, which are controlled by switches. The motor can be driven at different speed level as per its load requirement by making use of five level MLDC Link Inverter. In case of traditional inverter which is only a one level inverter the speed cannot be controlled as per the load requirement. The MLDC link inverter provides the output voltage waveform in step shape form. Thus as the number of cells (n) increases output voltage touches the fundamental component. The input voltage is low, thus to increase the input voltage given to the MLDC link inverter the (Boost Converter) has been designed. The Boost Converter is placed in between (DBR)Diode Bridge Rectifier and (MLDCLI). Both the design and results of Single level inverter and Multilevel Dc Link Inverter are obtained and compared by using the MATLAB Software along with the use of Simulink and Simpower system Tools.

A Novel Method to Improve the Control Performance of Multilevel Inverter by Multisampling

This paper introduces multilevel inverters. Inverters can be broadly classified into single level inverter and multilevel inverter. Multilevel inverters when compared to single level inverters have advantages like minimum harmonic distortion and reduced EMI/RFI generation it can also operate on several voltage levels. In the existing system 5 level inverter is used. It reduces THD compared to the conventional switching system. In the proposed system seven level inverter by multi sampling technique is being implemented. Proposed method is implemented using SIMULINK. By using the multi sampling technique system performance can be increased as well as the harmonics can be reduced. Conventional digital control power converters usually use a technique known as uniform sampling.

Fault Detection and Classification in Power Electronic Circuits Using Wavelet Transform and Neural Network

Problem statement: The identification of faults in any analog circuit is highly required to ensure the reliability of the circuit. Early detection of faults in a circuit can greatly assist in maintenance of the system by avoiding possibly harmful damage borne out of the fault. Approach: A novel method for establishing a fault dictionary using Wavelet transform is presented. The Circuit Under Test (CUT) is three phase single level inverter. The transform coefficients for the fault free circuit as well as for the simulated faults of CUT are found. The Wavelet transform is applied to the output of CUT and Standard Deviation (SD) of the transform coefficients are extracted. Using the transform coefficients, fault dictionary has been formed. In order to identify the type of fault, a neural network classifier has been utilized. Results: The compatibility of wavelet analysis with the various classification techniques for fault diagnosis has been illustrated in this study. The results of the study demonstrate the suitability and viability of wavelet analysis in fault diagnosis of power electronic circuits. Conclusion: The proposed approach is found to be more reliable in accurate identification and isolation of faults using fault dictionary. Moreover, the neural classifier improves the efficiency of the system as neural networks do not require prior knowledge as they are capable of learning and evolving through a number of learning algorithms.