Tracks

  • Track 1

    Power Converters, Devices, EMI/EMC and Packaging

    • AC/AC, AC/DC, DC/AC and DC/DC Converter, Modelling and Control.
    • Power Device Modeling and Device Drivers, Packaging of Devices, Systems and Thermal Issues. Magnetic Materials and Component Design, Passive Filter Design.
    • EMI and EMC issues in Power electronic System Design and Packaging Methods of Analysis and Filters.

  • Track 2

    Electrical Machines and Industrial Drives

    • Converters, Operation and Control.
    • Modeling, Analysis and Design of Rotating and Linear Machines.
    • Electromagnetic Devices.

  • Track 3

    Transportation

    • Power Electronics and Motor Control for EV Applications, Charging Methods and Standards
    • Wireless Charging, G2V and V2G Applications
    • Aircraft and Space Applications
    • Railway Traction Applications
    • Intelligent Transportation System

  • Track 4

    Control and Automation

    • Linear and Nonlinear Control, Intelligent Control, Predictive Control, Networked Control System and Instrumentation.
    • Industrial Automation, Internet of Things and Embedded Systems.

  • Track 5

    Renewable Energy Systems and Energy Storage

    • Distributed Power Generation, Control and Grid Interaction.
    • Role and Operation in Grids and Microgrids, Charging and Discharging, Battery Management Systems, Battery Engineering, Battery uses and Recycling.

  • Track 6

    Smart Grids & Power Quality

    • Modeling, Control and Integration of Multiple Energy Sources, Economics of Smart Grids and Microgrids.
    • Quantification and Estimation of Disturbances in Transmission and Distribution Networks, Converters and Control for Improving Power Quality.
    • Reactive and Active Power Controls, FACTS Devices.

  • Track 7

    Power Engineering Educations and Issues

    • Teaching Concepts in Power Engineering and Laboratory Innovations.
    • Policies for Distributed Generation.
    • Smart Grids and Operation with Increased Renewable Penetration.

  • Track 8

    Applications of AI and ML Techniques to Power Electronics

    • Application of machine learning for predictive maintenance in power electronic devices.
    • Health monitoring of capacitors, inverters, and other critical components using AI algorithms.
    • AI and ML applications in optimizing the integration of renewable energy sources into power systems.