Abstract:
This paper presents a drive mode control method for plug-in hybrid electric vehicles (PHEVs) to reduce fuel consumption and emissions. In the PHEVs, a management strategy...Show MoreMetadata
Abstract:
This paper presents a drive mode control method for plug-in hybrid electric vehicles (PHEVs) to reduce fuel consumption and emissions. In the PHEVs, a management strategy for efficiently allocating energy resources is drive mode control according to driving routes. The drive mode control practically requires a catalyst converter to have a high temperature before starting the engine for emissions reduction. To incorporate the temperature condition into the energy management, we propose an optimization framework of the drive mode control embracing catalyst models. The newly developed temperature model employs a discrete mixed logical dynamical system representation to lessen the optimization’s computational burden. The proposed method is verified by an advanced simulator with real-world datasets. The simulation results exhibit that the proposed method achieved a 1.1 % reduction in fuel consumption than that of a commercial strategy even under a severe but realistic requirement. The comparative studies of various catalyst conditions reveal how the temperature requirement influences the performance of the drive mode strategy.
Published in: 2022 American Control Conference (ACC)
Date of Conference: 08-10 June 2022
Date Added to IEEE Xplore: 05 September 2022
ISBN Information: