Optimization for Transportation Efficiency

Date: May 2, 2pm

Location: Sycamore Conference Room (040-195)

Speaker: John Fox

Abstract: 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.

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