A review of intelligent road preview methods for energy management of hybrid vehicles
conference contributionposted on 26.03.2019, 16:21 authored by Wen Gu, Dezong Zhao, Byron Mason
Due to the shortage of fuel resources and concerns of environmental pressure, vehicle electrification is a promising trend. Hybrid vehicles are suitable alternatives to traditional vehicles. Travelling information is essential for hybrid vehicles to design the optimal control strategy for fuel consumption minimization and emissions reduction. In general, there are two ways to provide the information for the energy management strategy (EMS) design. First is extracting terrain information by utilizing global positioning system (GPS) and intelligent transportation system (ITS). However, this method is difficult to be implemented currently due to the computational complexity of extracting information. This leads to the second method which is predicting future vehicle speed and torque demand in a certain time horizon based on current and previous vehicle states. To support optimal EMS development, this paper presents a comprehensive review of prediction methods based on different levels of trip information for the EMS of hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle (PHEV).
The work was cofunded by the Digital Engineering and Test Centre (DETC), under a grant for the virtually connected hybrid vehicle. DETC is a unique joint industry academic centre, also as an Advanced Propulsion Centre spoke. It develops and uses virtual engineering tools and techniques to accelerate the development, test and manufacture of automotive propulsion systems. This work was supported by the Engineering and Physical Sciences Research Council of U.K. under the EPSRCUKRI Innovation Fellowship scheme (EP/S001956/1).
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering