Bo Chen


Biography

Dr. Chen is the Dave House Associate Professor of Mechanical Engineering and Electrical Engineering in the Department of Mechanical Engineering – Engineering Mechanics and Department of Electrical and Computer Engineering at Michigan Technological University. She received her Ph.D. degree from the University of California, Davis, in 2005. Dr. Chen conducts interdisciplinary researches in the areas of mechatronics and embedded systems, agent technology, modeling and control of hybrid electric vehicles, cyber-physical systems, and automation. Her research projects are funded by National Science Foundation, Department of Energy, and industrial partners. Dr. Chen has authored or co-authored over 70 peer-reviewed journal and conference papers. She received the Best Paper Award at 2008 IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications.

Dr. Chen is currently serving as the Chair of the Technical Committee on Mechatronics and Embedded Systems of IEEE Intelligent Transportation Systems Society and the Chair of the Technical Committee on Mechatronic and Embedded Systems and Applications of ASME Design Engineering Division. She is an Associate Editor of the IEEE Transactions on Intelligent Transportation Systems. Dr. Chen has served as Program Chair, Symposium Chair, and Session Chair for a number of international conferences. She was the General Chair of 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications.
Areas of Expertise
Mechatronics and embedded systems
Agent Technology
Monitoring and control networks
Hybrid electric vehicles
Smart grid

Research Interests
Modeling and control of hybrid electric vehicles
EV-smart grid integration
Distributed monitoring and control
Battery control for HEV and energy storage systems
IC engine management systems
Sensor information fusion

Autonomous Microgrids: Theory, Control, Flexibility and Scalability

U.S. Dept of Defense Office of Naval Research

Project Description and Research Objectives:
From large scale electric power grids and microgrids down to small scale electronics, power networks are typically deployed using a fixed infrastructure architecture that cannot expand or contract without significant human intervention. Mobile, monolithic power systems exist but are also not readily scalable to exploit surrounding power sources and storage devices. However, if a power network is constructed from physically independent and autonomous building blocks, then it would be infinitely reconfigurable and adaptable to changing needs and environments. The aim of this project is to integrate vehicle robotics with intelligent power electronics to create self-organizing, ad-hoc, hybrid AC/DC microgrids. The main benefits of this system would be the establishment and operation of an electrical power networks independent of human interaction and can adapt to changing environments, resource and mission. In the context of U.S. Naval platforms, this autonomous electrical network could be used in land, air or sea systems.

The focus of this work will be on land based autonomous microgrid systems, but the fundamental theory developed may be applicable to air and sea based systems as well. Investigators at Michigan Technological University have developed initial hardware and testbeds to study this problem. However, a more detailed theoretical foundation is needed to be developed to apply autonomous microgrids to a wide variety of operational scenarios with various resources. It is also hypothesized that given the flexibility of this approach that it could be equally applied over a vast scale of energy assets. A microgrid that grows in situ from 10 s to 100 s to 1000 s of energy assets can be equally managed, controlled and optimized through the highly scalable approach proposed in this project.

These applications are examples of the critical need for autonomous mobile microgrid capable of operating in highly dynamic and potentially hazardous environments. Our overall goal is to create a scalable architecture to develop a system that accounts for uncertainty in predictions and disturbances, is redundant, requires minimal communication between agents, provides real-time guarantees on the performance of path planning, and reaches the targets while making electrical connections. Such architecture provide a coherent layout for the interconnection between different disciplines on this topic and minimizes the integration concerns for future developments.

Description of the Proposed Work:
• Microgrid Planning and Control
• Microgrid Topology and Optimization
• Electrical Components and Power Flow
• Game-Theoretic Control
• Physical Autonomous Positioning and Connections

Investigator: Wayne Weaver, Rush Robinett and Nina Mahmoudian

Vehicle to Grid Research

Vehicle to Grid

Overview

By treating a hybrid vehicle as a microgrid, it has the ability to exploit interconnection strategies for plug-and-play integration with deployed microgrids while being a mobile, energy exchange system between disconnected power grids. Research is focused on optimization and control of microgrids that have a significant penetration of vehicles that can be loads, sources, or energy storage devices.

Active Projects

Applications

  • Exploiting tradeoffs between high power plug-in vehicles, storage and renewable penetration
  • Optimal storage state of charge for mobile/vehicular microgrids
  • Vehicle design impact on grid connectivity
  • Use of military hybrids for FOB microgrid deployment
  • Distributed control strategies for plug-in hybrid charging for more manageable grid load
  • Information transfer between vehicles and grid (smartgrids)

Vehicle To Grid Chain

Vehicle Chart

Vehicle – to – Vehicle Resource Sharing

Mississippi State University / U.S. DoD TARDEC

The existing communication layer for Vehicle to Grid (V2G) operations has sufficient throughput and capabilities for basic connectivity, but may not have enough for tasks such as operating military vehicle systems remotely. They cyber security approach to V2G operations has had some development in industry; however military vehicles demand more scrutiny from a cyber security perspective.

Vehicle-to-Vehicle (V2V) resource sharing would enable a greatly expanded flexibility for utilization of assets for forward operating bases (FOB). Consider a FOB with a variety of vehicle assets, each with different levels of functionality. The ability to daisy-chain the vehicle assets together (including partially disabled vehicles), have the vehicles automatically determine their net capability and then share resources to accomplish a common goal (force protection for example), would enable a level of capability not currently available.

Specific Tasks: Vehicle-to-Grid Simulation, Connection Protocol Assessment, Connection Protocol Development, Throughput Assessment, and Simulation Studies.

Investigators: Gordon Parker, Wayne Weaver, Steven Y. Goldsmith

 

Lucia Gauchia

DSC_1949Dr. Lucia Gauchia received her General Engineering degree and her Ph.D. degree in Electrical Engineering from the University Carlos III of Madrid, Spain in 2005 and 2009, respectively.

Dr. Gauchia was appointed in 2013, the Richard and Elizabeth Henes Assistant Professor of Energy Storage Systems at the Electrical and Computer Engineering Department and Mechanical Engineering-Engineering Mechanics Department at Michigan Technological University (USA). She was a Postdoctoral Research Associate with McMaster University (Canada), working for the Canada Excellence Research Chair in Hybrid Powertrain and the Green Auto Powertrain Program. From 2008 to 2012 she worked at the Power Electric Engineering Department at the University Carlos III of Madrid (Spain).

Her research interests include the testing, modeling and energy management of energy storage systems for microgrid and electrical vehicle applications. She is particularly interested in the integration of energy storage for microgids, its selection and control depending on the energy storage technology and microgrid needs.

Areas of Interest

  • Energy Storage Systems
  • State estimation for batteries and supercapacitors