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Controlled Auto-Ignition (CAI), also known as Homogeneous charge compression ignition (HCCI), has been the subject of extensive research because of their ability to providing simultaneous reduction in fuel consumption and NOx emissions in a gasoline engine. However, due to its limited operation range, combustion mode switching between CAI and spark ignition (SI) combustion is essential to cover the overall operational range of a gasoline engine for passenger car applications. Previous research has shown that the SI-CAI hybrid combustion has the potential to control the ignition timing and heat release process during both steady state and transient operations. However, it was found that the SI-CAI hybrid combustion process is often characterized with large cycle-to-cycle variations, due to the flame instability at high dilution conditions.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.