As the primary means of energy storage in many applications such as portable devices, electric/hybrid electric vehicles (EV/HEVs), and aircrafts, the battery needs to be extremely efficient to allow for reasonable usage duration on a single charge. Among the factors that affect the efficiency of the battery, the most important is temperature. There have been many high-profile cases where batteries have over-heated in products, causing, at best, costly delays and recalls or, at worst, injury and even death. As such, battery manufacturers usually overdesign batteries to ensure safety and life due to the uncertainty of the internal states of the cell. Smarter Battery Management Systems (BMS) and advanced sensing technologies offer an opportunity to significantly reduce the weight of the battery, and the cost involved. They also help to circumvent over-heating issues arising due to aggressive use of batteries.
This presentation will demonstrate the development of predictive models of battery cells that can be implemented within a multi-domain system model of a hybrid system, particularly an EV/HEV, allowing the designer to understand the loading effect on the battery as it undergoes many different duty cycles. The presenters will also describe how multi-scale electrochemical engineering models, mathematical model reformulation, and the use of robust algorithms can improve the range of variables that are predictable and controllable in a battery in real-time within an EV/HEV. The use of battery models in a BMS will be analyzed. The interplay between the fundamental depth in modeling, choice of algorithms, and application driven problem formulation will also be presented. Equipped with this knowledge, the system design parameters can be optimized, thus minimizing the risk of battery failure, while balancing other design constraints.
Dr. Venkat Subramanian, Associate Professor, Washington University
Dr. Venkat Subramanian is an Associate Professor in the Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis. He is also the co-founder and interim Director of the Solar Energy and Energy Storage (SEES) initiative. He is currently the chair of the IEEE Division of the Electrochemical Society and the Chair of Electrochemical Engineering subgroup of the American Institute of Chemical Engineers. Dr. Subramanian has a Department of Energy – ARPA-E grant to develop model based BMS for batteries. Other research areas of interests include energy systems engineering, electrochemical engineering, computationally efficient algorithms for state-of-charge (SOC) and state-of-health (SOH) estimation of lithium–ion batteries, and multiscale simulation and design of energetic materials. He was awarded the Dean’s award for excellence in graduate study in 2001 for his doctoral research.
Dr. Sam Dao, Application Engineer, Maplesoft
Dr. Dao received his PhD degree in Mechatronics from the Dept. of Mechanical and Mechatronics Engineering at the University of Waterloo. He is currently an Application Engineer at Maplesoft. Originally part of Dr. John McPhee's research team, Dr. Dao has been involved in many research projects including multiple robot networking, hybrid electric vehicle modeling, and battery modeling.
Dexter Johnson is the author of IEEE Spectrum’s online blog The Nanoclast. He has researched and written reports and analysis in the areas of nanotechnology, sensors, IT, advanced manufacturing and economic trends within a number of different industries. He has been the program director for international conferences in the areas of telecommunications, digital content delivery and nanotechnology. In addition to his work at IEEE Spectrum, Dexter is a senior analyst with Cientifica, a UK-based business intelligence company for emerging technologies.
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