Bo Chen


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

CAREER: An Ecologically-Inspired Approach to Battery Lifetime Analysis and Testing

National Science Foundation

Batteries are increasingly relied upon to provide multiple services during applications (e.g. traction in an electric vehicle, vehicle-to-grid, ancillary services) and to act as the ultimate resiliency element (e.g. electric vehicles used as power units during Hurricane Sandy). However, the ability to perform these diverse services is compromised by battery aging phenomena that eventually lead to failure. Understanding of how service conditions and context affect battery aging is limited due to a) battery high context dependency on generation and load dynamics, and environmental conditions; b) the multi-scale cell and module nature of battery systems; and c) the fact that a battery itself varies with age, as batteries are repurposed after a first life (e.g. electric vehicle) into a second life (e.g. grid or residential).

This CAREER project aims to understand battery aging dynamics as context-dependent, and to provide a unified theory that links application-level events and conditions with cell- and module-level aging events. The Pl hypothesizes that a battery electrochemical nature and aging, multi-scale system, observability challenges, and its context-dependency can all be modeled using ecological tools, with ecology defined as a branch of biology that explores organism relationships to one another and to their environment. Therefore, methods proven useful to study ecological relationships are well suited to study battery life, and can provide new knowledge, testing and estimation techniques. This project draws from two pertinent areas in ecology: 1) multi-scale field testing and 2) modeling of interrelationships among ecosystem elements to understand coupled effects and improve remaining life predictions. Hence, the research objectives are: 1 ) Identify a battery context and its observability through sensors and data in real deployment conditions for two lives (electric vehicle and grid); 2) Optimize a methodology to translate real-life conditions into the laboratory; 3) Design a large multi-scale testing platform in the laboratory for new and aged cells and modules that mimics real-life conditions; 4) Explore multi-scale battery dynamics and aging by developing reasoning networks that capture the whole battery context variations throughout its scales, reaching the application level; develop theories that link these networks across lives; design battery management systems that can learn to construct and apply these networks to improve their decision making and prediction.

Intellectual Merit
This novel project will provide knowledge and perspectives to two fields by capitalizing upon the similarities between battery context-dependencies, battery life, and ecological systems. This new outlook will provide a unified theory for testing, estimation and management of batteries across cell, module, pack, and application scales and life scales in a research field that up to this point has been disconnected between scales. Testing approaches, interrelationship models, and estimation methods used in ecology are predicted to improve upon present, state-of-the-art battery research methods to provide economic, resiliency and environmental benefits by better understanding and leveraging the unique, time-dependent relationships each battery has with its context.

Broader Impacts
This work will benefit all battery portable, transportation, and grid applications as well as multiple sectors. It will include the emerging battery repurposing sector, by providing tangible methods to improve testing, estimation and management techniques. The result will be longer battery life, better performance, and less environmental waste. Educational impacts include active learning opportunities for undergraduate and graduate students via research and educational interactions with individualized testing boards linked to the newly created large multi-scale testing platform. This strategy will enable low cost, highly distributed testing environments. The Pl will disseminate tools via national education conferences to improve the nearly nonexistent battery testing training of students. This project will facilitate new paths in multi-disciplinary graduate courses. The Pl has a passion to increase representation of Hispanic females in STEM. Outreach will include hosting 4 diverse Community College students for summer research through the Michigan College and University Partnership, and participating in Society for Hispanic Professional Engineers conferences, specifically in the female Hispanic track.

Investigator: Lucia Gauchia

Kazuya Tajiri

Dr. Kazuya Tajiri earned his Bachelor degree from the University of Tokyo, and Master of Science degree from Georgia Institute of Technology in the field of turbulent combustion simulation. After three years of fuel cell research at Nissan Motors in Japan, he returned to the U.S. to continue Ph.D. research at Pennsylvania State University, and earned his Ph.D. degree in 2008. After two years of experience at Argonne National Laboratory conducting fuel cell systems modeling and analysis, he joined Michigan Technological University in 2010.

Currently, Dr. Tajiri is the director of the Multiscale Transport Process Laboratory (MTPL), and investigates the multiphase, multiscale transport phenomena in energy conversion devices and propulsion systems.
At present,two main research objectives are being conducted:
• Electrochemical devices for energy conversion
• Unsteady flow systems for propulsion / energy conversion

Vehicle to Grid Research

Vehicle to Grid


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


  • 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

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