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Author:

Bin, Yang (Bin, Yang.) | Li, Yaoyu (Li, Yaoyu.) | Peng, Zhong-Ren (Peng, Zhong-Ren.)

Indexed by:

EI Scopus

Abstract:

This paper presents a spatial domain Dynamic Programming (DP) optimal power management scheme for plug-in hybrid electric vehicles, which integrates multiple trip information including speed, road grade and payload profiles. The segment-wise power demand is obtained in a closed form, based on length, initial speed, acceleration, road grade, payload and wind of a road segment. The State of Charge (SOC) change is obtained with linearisation of battery non-linear dynamics for different Power Split Ratio (PSR). An adjustable segment scheme used of analytical function is developed in order to improve the computation efficiency of the optimal power management without losing much of fuel economy. Simulation study shows that incorporating additional trip information such as road grade and predictable payload change into the optimisation can significantly improve the fuel economy. The computational efficiency is also evaluated. The proposed method can greatly facilitate the development of optimal power management strategy for PHEV with multiple information inputs. Copyright © 2010 Inderscience Enterprises Ltd.

Keyword:

Plug-in hybrid vehicles Efficiency Electric power measurement Highway administration Power management Battery management systems Computational efficiency Roads and streets Fuel economy Charging (batteries) Dynamic programming

Author Community:

  • [ 1 ] [Bin, Yang]College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Li, Yaoyu]Department of Mechanical Engineering, University of Wisconsin-Milwaukee, 3200 N. Cramer St., Milwaukee, WI 53211, United States
  • [ 3 ] [Peng, Zhong-Ren]Department of Urban and Regional Planning, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, United States
  • [ 4 ] [Peng, Zhong-Ren]And College of Transportation Engineering, Tongji University, Shanghai 200092, China

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Source :

International Journal of Electric and Hybrid Vehicles

ISSN: 1751-4088

Year: 2010

Issue: 4

Volume: 2

Page: 259-281

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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