Projects

Prof. David A. Lowther

Automotive Partnership Canada
Development of Optimal Electric Drive Trains for On-Road Vehicles

This is a collaborative R&D project between McGill University and the Canadian industry partners Linamar, TM4, and Infolytica. The goal of the proposed research is to develop a generic, high-performance electrical powertrain for electric vehicles that offers higher performance in a smaller package and at lower cost than today’s electrical powertrains.The focus of our current work is on the accurate prediction of iron losses, robust and multi-objective optimization for electrical machines design.
More information about the project can be found here.

Key Publication(s)

  1. V. Ghorbanian, A. Salimi and D. A. Lowther, "A Computer-Aided Design Process for Optimizing the Size of Inverter-Fed Permanent Magnet Motors," IEEE Transactions on Industrial Electronics, vol. 65, no. 2, pp. 1819-1827, Feb. 2018, doi: 10.1109/TIE.2017.2733460.

  2. R. C. P. Silva, T. Rahman, M. H. Mohammadi and D. A. Lowther, "Multiple Operating Points Based Optimization: Application to Fractional Slot Concentrated Winding Electric Motors," IEEE Transactions on Industrial Electronics, vol. 65, no. 2, pp. 1719-1727, Feb. 2018, doi: 10.1109/TIE.2017.2756586.

  3. V. Ghorbanian and D. A. Lowther, "A Statistical Solution to Efficiently Optimize the Design of an Inverter-fed Permanent Magnet Motor," IEEE Transactions on Industry Applications, vol. 53, no. 6, Dec. 2017, doi: 10.1109/TIA.2017.2726968.

  4. S. Hussain, M. H. Mohammadi, K. S. Sidhu and D. A. Lowther, "Effects of PWM Excitations on Iron Loss in Electrical Steels and Machines," accepted in the 2017 IEEE Industry Applications Annual Meeting, Cincinnati, OH, USA, (Oct 4, 2017).

  5. S. Hussain and D. A. Lowther, "An Efficient Implementation of the Classical Preisach Model," IEEE Transactions on Magnetics, vol. 54, no. 3, Mar. 2018, doi: 10.1109/TMAG.2017.2748100.

  6. V. Ghorbanian, S. Hussain, S. Hamidizadeh, R. Chromik and D. A. Lowther, “Demagnetization Proximity Considerations of Inverter-fed Permanent Magnet Motors”, presented in the IEEE Electric Machines and Drives Conference (IEMDC), Miami FL, USA, (May 24, 2017)

  7. T. Rahman, M. H. Mohammadi, K. Humphries and D. A. Lowther, "Comparison of Fractional Slot Concentrated Winding and PM Assisted Synchronous Reluctance Motors for Class IV Electric Vehicles," presented in the IEEE International Electric Machines and Drives Conference (IEMDC), Miami, FL, USA, May 2017.

Prof. Dennis Giannacopoulos

Finite element method is a powerful tool to solve partial differential equations. It brings unknown field quantities into a system of linear equations as "Ax=b", in which A is a sparse matrix. The Conjugate Gradient (CG) method is one of the most popular iterative methods used for solving such a large and sparse system. The dominant computation cost lies in the sparse matrix-vector multiplication (SMVM) at each iteration stage of the CG method. Currently, Field-Programmable Gate Arrays, multi-core processors, and Graphic Processing Units offer competitive computing advantage and dictates new SMVM schemes to exploits their parallelism. We are developing algorithms to format large matrices, partition computation, and equally load the processors, The aim is to achieve linear increase of computational speed as the number of cores/processing units increases irrespective of the size of the problem. These algorithms would lie in the core of some CG solvers to solve large finite element problems.

Key Publication(s)

  1. KOO J. Jahyun, Fernández David, Haddad Ashraf, Gross J. Warren, "Evaluation of a High-Level-Language Methodology for High-Performance Reconfigurable Computers", 18th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2007), July 8-11, 2007, Montreal, Quebec, Canada.
  2. Yousef Elkurdi, David Fernández, Evgueni Souleimanov, Dennis Giannacopoulos and Warren J. Gross, "FPGA architecture and implementation of sparse matrix-vector multiplication for the finite element method", Computer Physics Communications, Volume 178, Issue 8, pp. 558-570, 15 April 2008.
  3. Fernández D. M., Giannacopoulos D., Gross W. J., "Efficient Multicore Sparse Matrix-Vector Multiplication for FE Electromagnetics", IEEE Transactions on Magnetics, vol. 45, no. 3, pp. 1392-1395, March 2009.
  4. Fernández D. M., Giannacopoulos D., Gross W. J., "Multicore Acceleration of CG Algorithms using Blocked-Pipeline-Matching Techniques", Submitted to the COMPUMAG 2009 Conference to be held in Florianopolis, Brasil in November 2009.

Prof. Milica Popovic

Microwave breast cancer detection techniques have been proposed as a complementary technology to the standard x-ray mammography. They offer the potential advantages of low cost, comfortable scans, and they do not require the ionizing radiation that mammography does. Microwave-based breast imaging systems operate based on the inherent contrast in the dielectric properties between healthy and malignant tissues.

The focus of our current work is on a clinical prototype for microwave breast screening via multistatic radar using time-domain measurements. We have also designed anatomically and electrically realistic breast models (phantoms) with which we can test the system under various scenarios. Our system has been tested thoroughly with the phantoms, and we are now optimizing the measurements through patient testing in a clinical setting.

Key Publication(s)

  1. E. Porter, A. Santorelli, R. Kazemi, and M. Popovic, "Microwave Time-Domain Radar: Healthy Tissue Variations Over the Menstrual Cycle," IEEE Antennas Wireless Propag. Lett., vol. PP, no. 99, pp. 1–4, 2015.
  2. A. Santorelli, E. Porter, E. Kirshin, Y. J. Liu, and M. Popović, “Investigation of Classifiers for Tumor Detection with an Experimental Time-domain Breast Screening System,” Prog. Electromagn. Res., vol. 144, pp. 45-57, 2014.
  3. E. Porter, E. Kirshin, A. Santorelli, M. Coates, and M. Popovic, "Time-Domain Multistatic Radar System for Microwave Breast Screening," IEEE Antennas Wireless Propag. Lett., vol. 12, no. 1, pp. 229 - 232, 2013.
  4. A. Santorelli, M. Chudzik, E. Kirshin, E. Porter, A. Lujambio, I. Arnedo, M. Popovic, and J. Schwartz, "Experimental Demonstration of Pulse Shaping for Time-Domain Microwave Breast Imaging," Prog. Electromagn. Res., vol. 133, pp. 309 - 329, 2013.

Breast Cancer Detection Research Group page