Abstract
An Internal Combustion Engine (ICE) suffers from extra gas injection and higher friction loss during operation in low temperatures, which provides the possibility for further improving the energy efficiency/economy with multiple power sources for a hybrid electric vehicle (HEV). However, it is challenging to provide a real-time efficient engine on/off policy that integrating the slow thermal dynamics with uncertain traffic and workload conditions. Existing solutions mainly focus on the non-linear optimization or complex learning-based methods, which unavoidably lead to high computation burden and hard to be online implemented. In this work, based on the most efficient operation point of engine, we transfer the energy optimization problem into the decision making of engine on/off, which greatly reduce the computation burden and is more practically applicable. Three rule-based engine on/off strategies, including the benchmark one that does not consider the thermal influences and two hysteresis strategies incorporating the thermal state, are compared through simulations under randomly generated driving profiles. Results verified that the proposed hysteresis strategies are feasible and the overall energy efficiency/economy can be enhanced by considering thermal influences in engine on/off decision.