Energy management for series-production plug-in-hybrid electric vehicles based on predictive DP-PMP

Abstract This paper presents an energy management strategy for parallel plug-in-hybrid electric vehicles which combines Dynamic Programming (DP) and Pontryagin’s Minimums Principle (PMP). In particular, this paper focusses on the practical challenges encountered in series-production vehicles and develops corresponding extensions: First, the paper considers the effects of uncertain prediction data received from a navigation unit. Secondly, we consider engine starting costs in the DP-PMP framework and thirdly, we allow to constrain the engine state (on/off) in certain parts of the driving cycle. These three components are integrated into a unified DP-PMP framework. Simulation studies demonstrate the practical benefit of the algorithm and show close to optimal performance in terms of fuel consumption. At the same time the algorithm is computationally cheap and allows real-time operation on series-production ECUs.