Title :
Review of PHEV and HEV operation and control research for future direction
Author :
Overington, Shane ; Rajakaruna, Sumedha
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ. of Technol., Perth, WA, Australia
Abstract :
This paper identifies recent plug-in hybrid electric vehicle (PHEV) and hybrid electric vehicle (HEV) literature for the purpose of analysis in determining future direction. The authors have utilized and expanded on a procedure for analyzing control strategies which is found in Wirasingha et al. The existing procedure allocates control strategies into the four categories previously determined optimization based blended control, rule based blended control, multi-mode control, and hybrid only control and is given the heading control paradigms in this paper. Extending on this control strategy classification in the identification of the control paradigms, the ranking of individual controllers is undertaken in the control schemes section of this paper, to scrutinize the advantages and disadvantages of each system. This ranking system identifies three control strategies of significant interest to PHEV and HEV operation; predictive optimization, adaptive equivalent consumption minimization strategy (A-ECMS), and online optimization controllers. Additionally the analysis completed identifies a comparison of selected controller performance attributes namely: accuracy, computational complexity, a priori knowledge and portability, which determine the potential outcomes of integrating control systems with the respective strategies. From the analysis of existing literature the summary of this article realizes the PHEV and HEV operation and control design criteria that have shown significant improvements to performance and that are of particular importance for future design integration and implementation.
Keywords :
computational complexity; hybrid electric vehicles; minimisation; A-ECMS; HEV operation; PHEV operation; adaptive equivalent consumption minimization strategy; computational complexity; control strategy; control strategy classification; control systems; hybrid electric vehicle; hybrid only control; multimode control; online optimization controllers; optimization based blended control; plug-in hybrid electric vehicle; predictive optimization; rule based blended control; Computer architecture; Hybrid electric vehicles; Ice; Optimization; Propulsion; Topology; control strategies; energy conversion; energy storage; energy transfer; hybrid electric vehicle; plug-in hybrid electric vehicle;
Conference_Titel :
Power Electronics for Distributed Generation Systems (PEDG), 2012 3rd IEEE International Symposium on
Conference_Location :
Aalborg
Print_ISBN :
978-1-4673-2021-4
Electronic_ISBN :
978-1-4673-2022-1
DOI :
10.1109/PEDG.2012.6254031