Dr. Ali Bazzi

Due to the successive switching actions in a power electronic system, considerable conducted electromagnetic interference (EMI) is generated. This has been a major concern in designing power converters, which requires additional EMI filtering efforts. Passive EMI filters are the most common solutions to EMI reduction but usually consume a large portion of the volume as well as weight in power converters. Active EMI filters (AEFs) or hybrid EMI filters (HEFs) are considered best candidates over traditional passive EMI filters to achieve higher power density in power converters. The utilization of current transformer to sense or to compensate the EMI noise can increase the volume of an AEF. In this article, a transformer-less AEF, sprung from the concept of virtual impedance enhancement, is proposed. The proposed design features feedforward control with current-sensing-voltage-compensating. The operation principle of the proposed AEF is thoroughly introduced, and its performance is evaluated through simulations and experiments. Experimental results with an ac–dc power converter and a dc–ac inverter show that the proposed AEF can be generally applied to reduce conducted EMI on either ac or dc power lines.

22 August 2019 in IEEE Transactions on Power Electronics

Journal Article

Data-Driven Approach for Fault Prognosis of SiC MOSFETs

This paper $^1$ proposes an unsupervised learning approach for fault prognosis of Silicon Carbide (SiC) MOSFETs. The proposed approach utilizes the changing trend of a device's voltage, current, temperature and other device characteristics with its degradation. The failure modes of semiconductors are reviewed along with existing methods for fault prognosis. The proposed approach is the first to address prognostics of SiC devices, and it can avoid the effects from system noise and data errors. It is not limited to offline analysis and is targeted at online implementation. It is easy to implement on standard digital platforms, and has fast computational speed. Offline data analysis is performed to verify the effectiveness of the proposed method, and a processor-in-the-loop system is used to verify its ability to perform online fault prognosis.

5 April 2018 in IEEE Transactions on Power Electronics

Journal Article

Optimal Efficiency Control in a Wind System With Doubly Fed Induction Generator

This paper proposes an optimal efficiency control scheme for a wind system with doubly fed induction generator (DFIG). The suggested control scheme combines loss minimization (LM) in the DFIG and maximum power point tracking (MPPT) in the wind turbine and therefore maximum electrical energy generation, by the same wind energy potential, is achieved. Moreover, since the cut-in wind speed is reduced, extension of the exploitable wind speed range toward the lower speed region is attained. The LM is achieved by properly controlling the flux-linkage of the DFIG with respect to the stator current and the MPPT is accomplished by regulating the rotor speed through the rotor current. The parameters of the LM and MPPT controllers can be determined experimentally and thus, the knowledge of the wind energy conversion system (WECS) model is not required. For the implementation of the proposed control strategy, a new structure of the WECS has been adopted. However, the hardware requirements of the WECS and considerably the cost has not been considerably affected compared to the conventional configuration. Selective simulation and experimental results are presented to validate the effectiveness of the proposed control strategy and demonstrate the operational improvements.

16 November 2017 in IEEE Journal of Photovoltaics

Journal Article

Model-Based Maximum Power Curves of Solar Photovoltaic Panels Under Partial Shading Conditions

Antony Xenophontos

Ali Bazzi

This paper introduces a new model-based analytical method for locating the maximum power point (MPP) of solar photovoltaic (PV) panels under partial shading conditions. It also provides an analytical model to obtain maximum power line as a function of the panel voltage for changing weather conditions. A series of analytical equations that can accurately simulate a photovoltaic P–V or I–V curve under uniform and partial shading conditions are derived from established models. The proposed analytical model can subsequently determine the approximate location of all local maxima on a P–V or I–V curve and identify the global MPP to improve MPP tracking efficiency. Results show that the proposed analytical model for single and multiple maxima match experimental measurements on a PV panel. Loci of the MPP are also verified to be in close correlation between the proposed model, existing PV single-diode two-resistor model, and experiments.

19 June 2018 in IEEE Transactions on Power Electronics

Journal Article

Smooth Fault-Tolerant Control of Induction Motor Drives With Sensor Failures

Yiqi Liu

Michael Stettenbenz

Ali Bazzi

A smooth fault-tolerant control (FTC) of induction motor drives with sensor failures is presented in this paper. The drive uses concurrently active direct torque control (DTC), indirect field-oriented control (IFOC), and volts-per-hertz (V/f) controllers as replacements of each other in the case of sensor failure or recovery. Speed encoder, current and voltage sensors are considered. The DTC and IFOC controllers are properly modified and integrated with the V/f controller in synchronous frame, which allows switching between DC-type voltage commands of different controllers. Therefore, difficult synchronization of different controllers is avoided, and a simple rate limiter is able to achieve smooth hand-off transition of different controllers. Details of the DTC, IFOC and V/f controllers as well as their integration are presented. Simulation and experimental verification of the proposed FTC are given, where normal abc-frame switching and the proposed synchronous-frame switching of controllers are compared with different switching schemes and at different machine operation conditions. Simulation and experimental results show significantly smoother hand-off transients.

About Me

Ali M. Bazzi is an Associate Professor of electrical and computer engineering (ECE) at the University of Connecticut (UCONN), USA. He received his B.E. and M.E. degrees in electrical engineering from the American University of Beirut, Beirut, Lebanon, in 2006 and 2007, respectively. He received his Ph.D. degree from the University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA in 2010. He joined UCONN in 2012 as an Assistant Professor where he established and currently directs the Power Electronics & Drives Advanced Research Laboratory (PEARL). He was a senior power electronics electrical engineer with Delphi Electronics and Safety in 2011-2012, a visiting assistant professor at UIUC during spring 2011, an engineer with Bitrode Corporation in the summers of 2008 and 2009, and a research and teaching assistant at UIUC between 2007 and 2010. His research interests include power electronics design, control, optimization, fault diagnosis, and reliability modeling in motor drives, solar photovoltaics, and other applications. He received the NSF CAREER Award in 2018, Mavis Memorial Scholarship at UIUC in 2009, the Outstanding Teaching Award from the ECE Department at UCONN in 2014, and the Research Excellence Award at UCONN in 2015 and 2018. In 2016, he became a UTC Assistant Professor for Engineering Innovation at UCONN. He has over 90 peer-reviewed and refereed technical publications and several patents.

Dr. Ali Bazzi

Dr. Ali Bazzi

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