Combined energy and thermal management for plug-in hybrid electric vehicles - analyses based on optimal control theory

The calibration of fuel-efficient energy management strategies (EMSs) for plug-in hybrid electric vehicles (PHEVs) requires an in-depth understanding of the powertrain component's operation mode and, in particular, its optimal interaction. The derivation of optimal EMSs under stationary operating conditions and its application to the design process of rule-based operating strategies has thoroughly been researched in the past. However, when considering the warm-up period at cold ambient temperatures, the interaction becomes more complex and strongly influenced by transient component characteristics. The efficiency of pure electric driving (ED) and engine load point shifting (LPS) changes within the warm-up period and is even more affected by the respective driving route. Looking at the cabin heating demand suggests the possibility of an EMS being predictive and completely divergent at a first glance in order to provide a sufficient amount of waste heat for cabin heating purposes. This paper applies a forward dynamic programming (FDP) approach in order to focus on the impact of the transient internal combustion engine (ICE) temperature on an optimal operating strategy for hybrid electric vehicles (HEVs). Thresholds of efficient electric driving and engine characteristics with respect to optimal load point shifting are analyzed. Additionally, a set of representative driving routes is studied in order to gain further insights into the fuel saving potentials of predictive energy and thermal management strategies. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.