Optimal Operation of a Plug-In Hybrid Vehicle

Abstract

We present a convex optimization control method that has been shown in simulations to increase the fuel efficiency of a plug-in hybrid electric vehicle by over 10%. Using information on energy demand and energy use profiles, the problem is defined to preferentially use battery resources sourced from the grid over petroleum resources. We pose the general nonlinear optimal resource management problem over a predetermined route as a convex optimization problem using a reduced model of the vehicle. This problem is computationally efficient enough to be optimized “on the fly” on the on-board vehicle computer and is thus able to adapt to changing vehicle conditions in real time. Using this reduced model to generate control inputs for the detailed vehicle simulator autonomie, we record efficiency gains of over 10% as compared to the industry standard charge depleting charge sustaining controller over synthetic mixed urban-suburban routes.