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PEEC Sustainable Transportation Seminar - Context Sensitive Battery Management Strategies for Plug-In Hybrid Automobiles


Plug-in hybrid and all-electric vehicles offer potential to transfer energy demands from liquid petroleum fuels to grid-sourced electricity. We are investigating optimization methods  to improve the efficiency and resource utilization of Plug-in Hybrid Electric Vehicles (HEVs).  Our optimization uses information about a known or estimated vehicle route to predict energy demands and optimally manage on-board battery and fuel energy resources to maximally use grid-sourced electricity and minimally use petroleum resources for a given route.  Our convex optimization method uses a simplified car model to find the optimal strategy over the whole route, which allows for re-optimization on the fly as updated route information becomes available.  Validation between the simplified model and a more complete vehicle technology model simulation developed at Argonne National Laboratory was accomplished by “driving” the complete car simulation with the simplified control model.  By driving on routes with the same total energy demand but different demand profiles we show fuel efficiency gains of 5-15% on mixed urban/suburban routes compared to a Charge Depleting Charge Sustaining (CDCS) battery controller. The method also allows optimizing the economic lifetime of the vehicle battery by considering the stress on the battery from charge and discharge cycles in the resource optimization.

Work supported by the Precourt  Energy Efficiency Center and SLAC under DOE Contract DE-AC02-76SF00515. Nicholas Moehle and Jason Platt were partially supported by Professor Stephen Boyd.

Speaker Bios

Jason Platt - Applied Physics Department, Stanford

Jason is a graduating Co-Term Masters Degree student headed to the University of California San Diego for the Ph.D.  He is interested in energy systems technology and optimal control.

Nicholas Moehle - Mechanical Engineering, Stanford

Nick is a Ph.D. candidate in Stephen Boyd’s group and has has expertise in optimal control methods and an interest in applying convex optimization methods to real-world problems.

William Dally - Professor, Electrical Engineering Department, Stanford

Bill  investigates methods for applying VLSI technology to solve information processing problems. His current projects include network architecture, multicomputer architecture, media-processor architecture, and high-speed (4Gb/s) CMOS signaling.

Dally teaches a “Green Electronics” class in the department of Electrical Engineering about energy efficient DC-DC and DC-AC power conversion.

John Fox - Senior Scientist (SLAC) and Adjunct Professor, Applied Physics, Stanford

John has appointments at both the SLAC National Accelerator Laboratory and the Department of Applied Physics. His research areas center instability control for particle accelerators and technology development for beam instrumentation. Graduate and Undergraduate courses taught in electronic instrumentation. Undergraduate course “Energy Choices for the 21st Century”. He is a Fellow of the American Physical Society and received the Stanford Dean’s Award for Distinguished Teaching. John is probably the only Fellow of the APS who is also certified by the National Institute for Automotive Service Excellence.

April 14, 2017 - 1:40 pm to 3:00 pm
Y2E2 105