A study on the ecms parameter adaptation for the driver characteristic variation

Abstract

This paper proposes a novel supervisory control method for a parallel hybrid electric vehicle (PHEV) with a transmission mounted electric drive (TMED). An equivalent consumption minimization strategy (ECMS) is the supervisory control method and provides realtime sub-optimal energy management decisions by minimizing the “equivalent” fuel consumption of a hybrid electric vehicle (HEV). The equivalent fuel consumption is a combination of the actual fuel consumption an electrical energy use, and an equivalence factor is used to convert electrical power used into an equivalent chemical fuel quantity. In this study, the proposed ECMS parameter adaption focused on the driver characteristic variation. In the stage of development, the longitudinal driver model is developed and the represented driving patterns are defined. Results obtained in this research clarify the causal connection between the driver characteristic and the equivalence factor as the initial step of the adaptive ECMS implementable into microcontroller. The simulation results show that optimizing the control parameter is needed as the driver characteristic variation.