Special Sessions

SS01 - Machine Vision, Control and Navigation

Oleg Sergiyenko, Engineering Institute of Autonomous University of Baja California, Mexico
Julio C. Rodríguez-Quiñonez, Engineering Faculty of Autonomous University of Baja California, Mexico
Wendy Flores-Fuentes, Engineering Faculty of Autonomous University of Baja California, Mexico
Moises Rivas-Lopez, Polytechnic University of Baja California, Mexico

The integration of machine vision, control schemes and navigation algorithms, in cyber systems, such as robotic groups, become an important challenge for Industry 4.0. Moreover, enhanced machine vision systems such as those developed through deep neural networks constantly provide new applications from industry for manufacturing developments, energy and transportation optimization, to bio-health, food harvest, environment care and education. Accordingly, it is an important challenge to determine the most effective approaches of machine vision. Although our primary interest is in automatic systems in all their aspects, several control, communication, and navigation applications have close relations with these systems. Each contribution to share their knowledge surrounding frontier technologies, innovative solutions, research results, as well as initiatives related to industrial electronics and their applications for any of these fields are welcome in this special session.

Autonomous navigation
Machine vision with deep learning
Laser scanning
Innovative solutions in stereo vision applications
Vision-based target detection and tracking
Visual servoing techniques in mobile robots
Visual control with constraints
Swarm robotics
Robot communication
Surface mapping and recognition

SS02 - Advanced Techniques for Smart Home Control and Self-Consumption

Djaffar Ould Abdeslam, University of Haute Alsace, France
Dirk Benyoucef, University of Furtwangen, Germany

This special session will be the opportunity to evaluate the latest identification, classification and control techniques for smart home and self-consumption. The objective is the energy saving, data analysis, smart measures, the improvement of power quality. The influence of the wind turbine and PV systems on the power quality becomes so significant. An application of advanced techniques and artificial intelligence is a good opportunity for energy saving. Also, the solutions based on these techniques can improve the power quality issues and reduce the power consumption. It is therefore important to use the most effective identification and control methods to meet new requirements.

Home Energy Management System
Smart measures
Energy efficiency
Power quality improvement
Analyzing the impact of prosumers in grids
Mathematical and economic modelling of the Prosumer as an autonomous system
Energy charring
Improve the peak demand management
Consumption reduction
Modelling of electrical appliances, electrical systems, and power plants
Electrical signal measurements and analysis with advanced techniques
Energy charring and Blockchain

SS03 - Advanced Control of Grid-Connected Converters for Distributed Generation and Power Quality

Hadi Y. Kanaan, Saint-Joseph University of Beirut, Lebanon
Kamal Al-Haddad, Ecole de Technologie Supérieure, Montréal, Canada
Hasan Komurcugil, Eastern Mediterranean University, Famagusta, Turkey
Mohammad Sharifzadeh, Ecole de Technologie Supérieure, Montréal, Canada
Fadia Sebaaly, Ecole de Technologie Supérieure, Montréal, Canada

Renewable sources, such as photovoltaic panels, wind generators and fuel cells, are usually connected directly to the grid for cogeneration. This connection is made through power electronics interfaces that should ensure high stability, voltage regulation, power flow control, and low electromagnetic emission, along with high power density, low cost and high reliability. In some applications where high power level is required, the switching frequency of the power semiconductors is limited and the use of multilevel or interleaved converters becomes mandatory in order to get an acceptable power quality. This session addresses the issues of advanced control techniques applied to such converters to improve their performance, efficiency, reliability and cost-effectiveness.

Advanced control of multilevel inverters
Advanced control of power electronics in DC grids
Grid-connectivity control requirements
Control of paralleled or interleaved topologies
Modeling and model-based control of switch-mode power converters
Optimal control in hybrid cogeneration systems
Predictive control of power converters
Intelligent control of power converters
Direct power control of power converters
Power quality control in renewable energy systems
New PWM techniques for power electronics control
Real-time control and simulations of high power converters

SS04 - Learning-Based Monitoring and Control of Industrial Cyber-Physical Systems

Shichao Liu, Carleton University, Ottawa, Canada
Ligang Wu, Harbin Institute of Technology, Harbin, P.R. China
Bo Chen, Zhejiang University of Technology, Hangzhou, P.R. China
Jianxing Liu, Harbin Institute of Technology, Harbin, P.R. China

Industrial cyber-physical system (ICPSs) involve interdisciplinary approaches, merging theory of cybernetics, mechatronics, information technology, design and process science. Typical examples of ICPSs include smart grids, intelligent transportation systems and water resource management systems, to name a few, by leveraging advanced industrial electronics. The monitoring and control play crucial roles in sustaining the reliable and stabile operation of ICPSs. However, these tasks indispensably involve timely acquiring and processing tremendous amount of data. Machine learning (ML) and its emerging algorithms offer the potential of dealing with large-scale data analysis and decision-making for the monitoring and control of ICPSs. In turn, these ML based applications in the monitoring and control of ICPSs can also promote the development of ML, such as approximation theory, learning algorithms, and optimization approaches. This special session solicits state-of-art research work related to the latest challenges, technologies, solutions, methods, and fundamentals in the field of machine learning based monitoring and control for ICPSs.

Machine learning based modeling for ICPSs
Machine learning based analysis for ICPSs
Machine learning based state estimation for ICPSs
Machine learning based Cyber Security for ICPSs
Reinforcement learning based control for ICPSs
Multi-agent reinforcement learning for ICPSs
Game theories for optimal decision making for ICPSs
Data privacy and transparency in ICPSs
Vulnerabilities of machine learning models in ICPSs
Applications in smart grids, intelligent transportation systems, robotics, etc.

SS05 - Near-Field Wireless Power Transfer: Design, Optimization, and Control

Minfan Fu, ShanghaiTech University, Shanghai, China
Ming Liu, Shanghai Jiao Tong University, Shanghai, China
Chengbin Ma, Shanghai Jiao Tong University, Shanghai, China

In recent years, wireless power transfer (WPT) using near-field approach has become increasingly popular, and large number of electronic devices have adopted this promising technique to fully cut off the last cord. Thanks to the near-field characteristics, both the inductive and capacitive power transfer are particularly attractive for the high-efficiency mid-range charging applications. Currently, although tremendous efforts have been done to explore the basic coupling mechanism, compensation networks, and power conversion circuits, there are still lots of unsolved issues and interesting research topics, such as complicated coupling in the near-field environment, system integration and miniature, electromagnetic compatibility and interference, and foreign body detection. Innovations on the near-field WPT are still of paramount important to enable high performance energy transmission.

Power converters for WPT (e.g., inverters or rectifiers)
Coupler design and optimization (e.g., inductive or capacitive coupler)
Multiple-transmitter and/or multiple-receiver architectures
Component-/system-level modelling and analysis
Optimization and parameter design
Sensing, control, and their implementation
Electromagnetic interference issues
Dynamic charging and its applications

SS06 - Advanced magnetic technologies for power electronics applications

Kazuhiro Umetani, Okayama University, Japan
Keisuke Kusaka, Nagaoka University of Technology, Japan
Wilmar Martinez, KU Leuven, Belgium

Improved magnetic design, analysis, and material development are recently recognized as major challenges for the power electronics applications to the industry. Recent power converters are designed to operate at increasingly high switching frequency, propelled by the emergence of the next-generation semiconductor switching devices. This trend has led to new power electronics applications such as wireless power transfer and solid-state transformer as well as remarkable miniaturization and performance improvement of conventional power electronics applications such as switching power converters, motor drives, induction heating, etc. At the same time, this trend requires more sophisticated magnetic design, analysis, and material development as they affect the system performance, efficiency, and power density in high-frequency operation. This special session aims at discussing disruptive advances in magnetic design, analysis, and material development for power electronics applications and fostering innovation that will conduct a significant technological change in industrial electronics.

Inductor and transformer design optimization for high-frequency power converters
Magnetic design for wireless power transfer and induction heating
Magnetic integration and applications
Iron and copper loss accurate modeling
Inductance and power loss measurement
Analytical and numerical optimization of the magnetic structure
High power density implementation of magnetic devices
Advance magnetic materials for power electronics
Shape and size effects on magnetic components

SS07 - Intelligent Edge Learning for Industrial IoT

Mithun Mukherjee, Nanjing University of Information Science and Technology, China
Mian Guo, Guangdong Polytechnic Normal University, China
Jaime Lloret, Universitat Politecnica de Valencia, Valencia, Spain

Academics and industry experts are advocating for going from large-centralized cloud computing infrastructures to computing nodes located at the edge of the network in the industrial Internet of Things (IIoT). The intelligent edge computing paradigm for IIoT is taking its shape where we envision it as an edge computing system that realizes the computing, communication, and caching resources using data analytic platforms and harvesting the potential beneﬁts of artiﬁcial intelligence to improve the system utility. There will be new opportunities for, i.e., supporting real-time manufacturing and intelligent smart factory. However, many fundamental questions arise at the same time. For example, how and where to process the sensor and control data from distributed IIoT objects are significant issues due to the real-time controlling remote robotic objects requirements in IIoT. Therefore, many researchers in several technologies are actively investigating edge learning is yet required to be intelligent, which motivates intelligent edge learning. On the one hand, distributed learning algorithms, such as federated learning, are required to be supported in network edge close to mobile objects. On the other hand, edge learning algorithms are desired to intelligently process distributed and shared data for real-time remote factory logistics control. The special session aims to provide a forum for scientists, engineers, and researchers to discuss and exchange novel ideas, results, experiences, and work-in-progress on all aspects of intelligent edge learning for industrial IoT.

Edge, fog, and mobile edge computing for Industrial IoT
Machine learning and computational intelligence for handling big data in Industrial applications
Information-centric networking and software-defined network for edge intelligence
Intelligent edge-based mobile computing and analysis
Real-time communication interfaces and protocols
Intelligent infrastructures at the edge
Hardware testbed or field trial for AI-driven intelligent edge computing for industrial applications
Security and related considerations in intelligent edge computing
Intelligent routing and load balancing for edge computing
Network protocols for distributed machine learning

SS08 - Artificial Intelligence in Predictive Health Management for Modern Industry

Ruonan Liu, Tianjin University, China
Boyuan Yang, Nankai University, China

Predictive Health Management is critical to ensure the safe and reliable operation of industrial systems. With the rapid development of Industrial Internet-of-Things (IIoT) and artificial intelligence (AI) technologies, modern industry has drawn great attention to the intelligent fault diagnosis, remaining useful life prediction and condition monitoring methods. Advanced AI methods are suitable to improve the industrial data mining effectiveness, realize the domain adaption problem, and enhance the reliability with respect to various modern industry systems, including deep learning, federated learning, transfer learning, few/zero-shot learning, reinforcement learning, cross-modal information fusion, interpretability and explainable AI, computer vision, semantic reasoning and digital twins in industrial technology, Internet of Things, optimization and control, fuzzy-based system, etc.

Intelligent fault diagnosis and remaining useful life prediction
Intelligent industrial big data analysis
Digital Twin
Computer vision and audio analysis in industrial application
Industrial Internet of Things in PHM
Optimization and control approaches for industrial systems
Physical-informed AI approaches for modern industry
Trustworthy AI approaches for modern industry
Intelligent scene and object recognition approaches in modern industry

SS09 - Artificial Intelligence for Power Efficiency and Power Quality

Djaffar Ould Abdeslam, University of Haute Alsace, France
Patrice Wira, University of Haute Alsace, France

This special session will be the opportunity to evaluate the latest identification, classification, and control advanced techniques for power quality improvement. The interest in power quality is increasing due to the massive use of power electronics equipment. The continuous penetration of renewable energies and electric vehicles influence power quality issues. The session will cover advances in Smart Grid, Smart Home and Smart Meters.

Advanced methods for electrical disturbances identification
Active Power Filtering for harmonic suppression
Power quality improvement in Smart Grids by artificial intelligence
Power Factor Correction
Power quality impact of plug-in electric vehicles
Power quality impact of renewable energy penetration
Advanced methods for fault detection and classification in power transmission lines
Electromagnetic compatibility

SS10 - DC Protection Systems for Future DC Grids and NGTS - Next Generation Transportation Systems

Satish Naik Banavath, Indian Institute of Technology Dharwad, India
Harish Krishnamoorthy, University of Houston, USA
Sreekanth Thamballa, University of Minnesota, USA
Anindya Ray, Sandia National Laboratories, USA
Luciano Andrés García Rodríguez, Sandia National Laboratories, USA

The development of Smart Grid brings a technological revolution from the traditional centralized ac power network. In terms of technological development, applications such as EV charging infrastructures, PV farms, battery energy storage systems, and DC data centers have become more mature, and more and more appliances are being changed to dc power architectures. DC power transfer offers certain advantages over traditional AC power, such as higher power transmission efficiency, ease of synchronous control, improved system stability and power quality, and easier integration of renewable and distributed energy resources. Therefore, the development of dc grids becomes a major trend in the future energy systems. DC power architecture has already been adopted in applications, such as marine smart ships, and dc residential grid networks. DC grid architecture based on cryogenic (superconducting converters) for the aircrafts is also under consideration. The system architectures and control algorithms are two main research areas to develop dc microgrid technology. Apart from that, the system protection is another key concern in the dc grid, as it is related to the safety and stability of the grid. The demand for cost-effective dc circuit breakers continues to grow with the dc power distribution applications. Considering the rapid growth in applications, and vast research and development activities in this research area, this special session mainly focuses on new dc grid technologies, circuit breakers, protection schemes and dc converter topologies.

DC Circuit Breakers for LVDC, MVDC and HVDC power grids/ship/aircraft electric power systems
Superconducting fault current limiters
Cryogenic Power Devices based Solid State Circuit Breaker topologies
Hybrid DC Circuit Breaker - topologies, control and protection
Power Converters for DC grids and DC transformers
Modelling, control and stability of DC grids
Reliability and safety analysis of DC grids and their components
DC micro and nano grid structures
DC grid applications related to subsea and next generation aircrafts

SS11 - Stability Analysis and Advanced Control of Renewable Power System

Hong Li, Beijing jiaotong University, China
Huanhai Xin, Zhejiang University, China

With the increasing proportion of renewable energy installation and power electronic equipment, the dynamic characteristics of power system have undergone profound changes. The reduction of system rotational inertia will reduce the robustness of system frequency. At the same time, the lack of voltage and frequency support also brings many new stability problems with unknown mechanism to the power system, which seriously threatens the safe and stable operation of the power system. On the other hand, power electronic equipment has flexible regulation characteristics and fast response ability, which also brings new regulation means to the operation and control of power system. Thus, it is necessary to carry out in-depth scientific research on stability analysis and control technology of renewable power system. This special issue intends to collect and report the latest stability analysis and control of renewable power system.

Time-domain stability analysis of grid-connected power electronic equipment
Frequency-domain stability analysis of grid connected power electronic equipment
Stability improvement of grid-connected power electronic equipment
Modeling, analysis and control of synchronous stability in renewable power system
Application of complex network theory in renewable power system
Stability mechanism and quantification of weak synchronous power grid
Frequency stability analysis and control of renewable power system
Voltage stability analysis and control of renewable power system

SS12 DC-DC Power Conversion Schemes for Integration of Renewables

Kiran Maroti Pandav, Qatar University, Doha, Qatar
Sanjeevikumar Padmanaban, Anna University, Chennai, India
Mahajan Sagar Bhaskar, Prince Sultan University, Riyadh, Saudi Arabia

Rapid depletion of fossil fuels and environmental pollution problems has led to a great interest in investigating the power generation from alternative clean energy resources. Renewable energy sources, including photovoltaic systems, wind, hydro, geothermal, marine, and biomass, are becoming increasingly crucial in DG systems. Due to clean energy sources, the DC microgrid is gaining attraction due to the ease of integrating renewable energy sources (RES). RES can directly feed the local loads connected to the DC microgrid via a power converter system, and excess energy, if available, can be provided to the primary grid. Thereby, DC microgrid enables the consumers to generate, store and manage their day-to-day energy requirements independently. The performance of the DC microgrid can be efficiently governed by adequately choosing the power electronic interface.

High voltage gain DC-DC power converter
DC-DC Multilevel Converter for PV integrated microgrid applications
Bidirectional Converter for Electric Vehicular System with Renewable Energy Sources
Multistage DC-DC converter with voltage boosting techniques
Control algorithms for a DC-DC converter in Renewable Energy Applications
Other recent topics related to DC-DC Converter
Control techniques of power electronic converters for fuel cell and PV system
Advanced control of power electronics in smart grid
Real-time control and simulations of high-power converters
Optimal design and Control of DC-DC Converter
Reduced voltage and current stress DC-DC Converters

SS13 - Advanced Nonlinear Control Methodologies of Robotic Manipulators

Jianxing Liu, Harbin Institute of Technology, P.R. China
Yue Zhao, Harbin Institute of Technology, P.R. China
Fei Yan, Southwest Jiaotong University, Chengdu, P.R. China
Zhongliang Li, Aix-Marseille University, Marseille, France
Jose Ignacio Leon Galvan, Universidad de Sevilla, Spain

In recent decades, robotics have greatly promoted the transformation and upgrading of equipment manufacturing, medical systems, service and other industries. Especially in aerospace, military, disaster relief, extreme environment operation and other special scenes, robotics have an irreplaceable position. In the applications of robots, the robustness, safety and efficiency of motion control system are still an open problem, and the motion control and robust control have always been a hot topic. This special session focuses on (but it is not limited to) the robotics motion control and robust control with multi-input-multi-output, high nonlinearity, strong coupling, and uncertainties including parameter perturbation, external interference and unmodeled dynamics, among others.

Motion control and motion planning
Robust control for robotics and manipulators
Active disturbance rejection control technology
Neural network for robotics and manipulators
Sliding mode control for robotics and manipulators
Active disturbance rejection control for robotics and manipulators
Dexterous manipulation for robotics and manipulators
Model-based predictive control for robotics and manipulators
Adaptive control for robotics and manipulators
Deep learning in robotics and automation
Optimization and optimal control, etc.

SS14 - Switched Reluctance Machines

Lefei Ge, Northwestern Polytechnical University, China
Man Zhang, University of Electronic Science and Technology of China
Jingxin Hu, RWTH Aachen University, Germany

The switched reluctance machine has the advantages of simple structure, high temperature resistance, wide speed range and strong fault tolerance, which is widely used in electric vehicles, household appliances, aerospace, and industrial transmission. Due to the highly nonlinear electromagnetic characteristics, the SRMs also have some disadvantages, such as torque ripple, source current ripple, serve vibration etc.. These disadvantages limit their further application promotion. This special session is aimed to collect the latest theoretical and technological ideas for the better development of switched reluctance machines. Optimization design methods, new analytical and modeling methods, advanced control strategies, and novel converter topologies are warmly welcomed. Topics of great interest are categorized as follows in details.

Topic A: Optimization design methods of switched reluctance machine
Topic B: New analytical and modeling methods of switched reluctance machine
Topic C: Advanced control strategies of switched reluctance machine drive system
Topic D: Novel converter topologies of switched reluctance machine
Other related topics, such as condition monitoring of switched reluctance machine, fault diagnose of switched reluctance machine and the industrial application of switched reluctance machine.

SS15 - New Challenge in Human Factors in Industrial Electrical Field

Daisuke Chugo, Kwansei Gakuin University, Japan
Sho Yokota, Tokyo University, Japan
Jinhua She, Tokyo University of Technology, Japan

Along with the rapid progress in the field of industrial electronics, the importance of human factors in the development and operation of electronic systems has been widely recognized. This special session provides people a platform to present their new research results, discuss the state-of-the-art research topics, and talk about the changes and challenges in the related fields with broad interest. Contributors are welcome to submit their papers to this special session including the design, development, simulation, verification, and testing of low/high-power electronics, human factors theory, mechatronics, human-computer interaction, artificial intelligence, etc

Approaches to standardizing display and control of technologies
Integration of digital and analog circuits
Human-agent teaming
Perceptual and cognitive abilities
Prediction of mechatronic behavior
Real-world implications of human-system interaction
Open possibilities for use of electronic systems on chip
Development of module driven system
Synthetic vision systems
System reliability

SS16 - Modeling and Simulation of Cyber-Physical Energy Systems

Peter Palensky, TU Delft, The Netherlands
Alexandru Stefanov, TU Delft, The Netherlands

Automation and digitalization have become important topics in the energy sector in recent years, as modern energy systems increasingly rely on information and communication technology to combine smart controls with hardware infrastructure. With the emergence of Cyber–Physical Systems (CPS) as a transdisciplinary field, such modern energy systems can be classified as Cyber–Physical Energy Systems (CPES), integrating the related research and development within a broader scope. An important aspect of the research and development related to CPS is to bridge the gap between the traditional engineering domains and computer science. This is especially true for CPES, where the related engineering domains have in the past come up with proven and reliable methods for designing even large and complex systems. However, existing modeling and simulation tools still struggle to cover all aspects of CPES. Hence, a combination of universal modeling languages and established, domain-specific tools (like grid simulators and telecommunication simulators) is necessary. New methods, tools and algorithms are needed that are compact, computationally inexpensive, potentially self-organizing and intrinsically stable if applied to real energy systems.

Hybrid modeling and simulation
Co-simulation of multi-domain systems
Ontologies for energy systems
Applications of cyber-physical energy systems
Distributed algorithms and control
Standards in interfacing components
Formal languages for energy systems
Smart grid modeling
Smart cities modeling
Design of simulations/experiments

SS17 - Inverter-Based Energy Sources in Future Power Systems

Omar H. Abdalla, Helwan University, Egypt
Hady H. Fayek, Heliopolis University, Egypt
Markus Makoschitz , AIT Austrian Institute of Technology, Austria
Panos Kotsampopoulos, National Technical University of Athens, Greece
Luca Dalessandro, ETIX GmbH, Switzerland
Rizkallah Miloud, Centre de recherche et d’innovation en intelligence énergétique
CR2Ie and ETX, Canada

The share of Renewable Energy (RE) in many systems and regions is hitting significant levels and the trend is very promising. The world is now generating more than 20% of its electricity from PV, wind, fuel cells, solar thermal, bioenergy converters, and other RE technologies. Governments are targeting 100% RE generation by 2050 to slow the global warming and to reduce greenhouse gas emissions. Most of these RE technologies are based on power electronics energy conversion, such as power inverters. As the enabling technology to reduce or eliminate emissions and to ensure the energy transition, the share of inverter-based generation systems will further increase worldwide. This will trigger new technical challenges and the need to optimize both technology and economic aspects of inverters. The following advanced technologies tackled by this special session will maximize the potential of integration of inverter-based energy sources in future power grids: artificial intelligence, modelling, design, validation approaches, real-time control and
self-healing techniques.

Modelling and simulation of power systems with inverter-based generation plants
Real time simulation, control, and protection of inverter-based power systems
Self-healing techniques in inverter-based power systems
Modern control techniques of inverter-based power systems
Modern protection techniques of inverter-based power systems
Advances in HIL testing of inverter-based power systems
Advanced energy management systems, wide area protection, and control
IoT applications in inverter-based power systems
Optimal operation of inverter-based power systems
Modelling, simulation, and control of renewable energies in smart grids
Inverter-based power systems as a tool for achieving sustainable development goals
Virtual power plants role in inverter-based power systems
Modelling, simulation and control of EVs in inverter-based power systems
HVDC role in inverter-based power systems

SS18 - Advanced Motion Control Systems for Soft Interaction

Tarik Uzunović, University of Sarajevo, Bosnia and Herzegovina
Tomoyuki Shimono, Yokohama National University, Yokohama, Japan
Eray A. Baran, Istanbul Bilgi University, Istanbul, Turkey
Asif Šabanović, Academy of Sciences and Arts of Bosnia and
Herzegovina/International University of Sarajevo, Sarajevo, Bosnia and Herzegovina

A seamless transition between the position tracking and the force control tasks is demanded in most of the human-robot collaboration applications. Safe application of robotic systems in human environment requires so-called soft interaction between the systems and their environment. The interaction-free motion realizes trajectory tracking by a robotic system, ideally desiring an infinite stiffness; on the other hand, contact motion demands a certain level of compliance for high performance operation. Novel algorithms which can provide the transition between those two control modes result in a soft - a natural human-like - interaction with the environment. Such behavior of robotic systems is expected particularly for the rapidly growing household robotic applications, for cobots or for any specific task where the robots are required to work together with people. Addressing those challenges, this special session tends to discuss design and application of control systems enabling soft interaction.

Position/Force Control
Impedance Control
Application of Disturbance Observers and Reaction Force Observers
Bilateral Control
Teleoperation
Soft sensors and actuators
Compliant and soft robotics
Explicit and implicit force control
Human-robot collaboration

SS19 - Efficient, High Density and Reliable Enabling Technologies for Transportation Electrification

Koyelia Khatun, Utah State University, Logan, UT, USA
Akshay Kumar Rathore, Singapore Institute of Technology, Singapore
Vinod Khadkikar, Khalifa University, Abu Dhabi, UAE

Transportation electrification is a need and Enabling Technologies play an important and critical role in their success. With the rapid demand and development of more electric vehicles, there is a critical need to assess and prepare for the impact of these technologies on transportation and development as a whole. However, developments in transportation also create new challenges for enabling technologies, infrastructure, impact on public and grid. Driven by the demand to reduce the cost and enhance the performance of on-the-move electrical energy technologies for transportation electrification, such as more electric aircraft, electric vehicles, rail, the industry is moving towards applications with more power electronics. High power density and reliable converters are critical enablers for the transportation industry to unlock significant improvements in system weight, operation life and energy consumption. This special issue aims to bring together researchers and practitioners from industry, laboratories, academia and government to present challenges and opportunities related to transportation electrification systems.

Compact and multiport power converters for on-board charging and vehicle traction applications
Hybrid energy systems for increasing operational-time and reduction in energy storage
Efficient and fault tolerant converters for less redundancy and compact systems for all kinds of EVs including fuel cell vehicles
Rail and e-Bus transportation system, automated local rapid transit and people movers
Street transportation system: e-bikes, small cabin compact passenger and delivery vehicles
Electric motor and their efficient control for e-mobility systems
Off-board EV charging infrastructures: Plug-in and wireless including fast charging, dynamic charging, and off-grid charging
Automated and unmanned vehicles
Electrification of Heavy-duty and Off-road Vehicles including Sea and Air transportation
EV architectures for hybrid electric, more electric, pure Electric and Electric range Extenders
The Impact of EV fast charging systems on utility and distribution transformers
Integration of alternative energy sources in EV charging and EV participation in smart grid (vehicle-to-grid)

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2022 IEEE International Symposium on Industrial Electronics

Anchorage, Alaska, USA June 1-3, 2022

Special Sessions