DocumentCode
3110717
Title
A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
Author
Musardo, Cristian ; Rizzoni, Giorgio ; Staccia, Benedetto
Author_Institution
Center for Automotive Research at the Ohio State University. Research Department at Renault, France (phone: +33 176857995, fax: +33 176857716 e-mail: cristian.musardo@renault.com).
fYear
2005
fDate
12-15 Dec. 2005
Firstpage
1816
Lastpage
1823
Abstract
Hybrid Electric Vehicles (HEV) improvements in fuel economy and emissions strongly depend on the energy management strategy. In this paper a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented. This real-time energy management for HEV is obtained adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions. The main idea is to periodically refresh the control parameter according to the current road load, so that the battery State of Charge (SOC) is maintained within the boundaries and the fuel consumption is minimized. The results obtained with A-ECMS show that the fuel economy that can be achieved is only slightly sub-optimal and the operations are charge-sustaining.
Keywords
Automotive; Hybrid Electric Vehicle; Optimal Control; Real-time Control; Supervisory Control; Adaptive algorithm; Energy management; Hybrid electric vehicles; Automotive; Hybrid Electric Vehicle; Optimal Control; Real-time Control; Supervisory Control;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on
Print_ISBN
0-7803-9567-0
Type
conf
DOI
10.1109/CDC.2005.1582424
Filename
1582424
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