A Cyber-Physical System-Based Velocity-Profile Prediction Method and Case Study of Application in Plug-In Hybrid Electric Vehicle

Abstract

Benefitting from the advances in sensor nets, wireless communication, and embedded systems, the cyber-physical system (CPS) has been implemented in many practical areas. The cyber world and the physical world in CPS are closely linked and merged, guaranteeing the reliable and efficient performance of the physical world. The service-oriented CPS has been the hot research and development. In this paper, we present a novel velocity-profile prediction method based on the specific CPS architecture. Three main efforts have been made. First, a CPS architecture which is appropriate for velocity-profile prediction is built. Second, the hybrid velocity-profile prediction (HVPP) method is developed based on the exclusive CPS architecture. The HVPP method accomplishes the velocity-profile prediction by cooperatively employing different control units in CPS. Third, a case study in a plug-in hybrid electric vehicle (PHEV) is performed to evaluate the effect of CPS-based service in the real application. Results of the case study demonstrate that the HVPP method can improve the fuel economy of PHEV significantly.