Real-time rule-based near-optimal control strategy for a single-motor multimode hybrid electric vehicle powertrain

Real-time optimal energy management is one of the key issues in designing multimode power split Hybrid Electric Vehicle (HEV) powertrains. Developing an online control strategy that is simultaneously optimal and easily implementable on an actual vehicle is not trivial. The primary objective of this study is to define an intuitive near-optimal rule-based real-time control algorithm for an HEV derived from an offline energy management strategy. Mode-shifting and torque split criteria are particularly determined from the analysis of statistics related to the operation of the offline control strategy. The observable correspondence in the estimated fuel consumption values derived from the real-time operation and the offline optimized energy management strategy respectively represents a first validation of the developed control logic. Moreover, this work aims at presenting and simulating a novel HEV design equipped with a single electric machine. In this way, new possibilities may be opened up towards simplification in discarding one of the two electric machines typically employed in HEV designs.