A Study on Regenerative Braking Control Strategy for an Extended-Range Electric Vehicle

Ji Gao Niu; Chun Hua Xu

doi:10.4028/www.scientific.net/AMM.602-605.1122

Paper Titles

Controlling Chaos in Automobile Suspension System with Nonlinear Feedback Controller
p.1103

Design and Implementation on PC Control Interface of Robot Based on VxWorks Operating System
p.1109

Position and Attitude Tracking Control Law Design Using Geometric Algebra
p.1113

Research on Speed Control Problem of Industrial Sewing Machine System
p.1117

A Study on Regenerative Braking Control Strategy for an Extended-Range Electric Vehicle
p.1122

Research on Smart Home Controlling System Based on Fuzzy Data Fusion Theory
p.1127

The Method Research of Grey Neural Network Control Based on Data
p.1131

The Brazing Furnace Intelligent Control Scheme Research of Application
p.1135

Study on Maximum Power Point Tracking for Photovoltaic Arrays Based on Fuzzy-Control Strategy
p.1139

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605A Study on Regenerative Braking Control Strategy...

A Study on Regenerative Braking Control Strategy for an Extended-Range Electric Vehicle

Abstract:

In order to further improve the baking energy recovery rate of extended-range electric vehicle (E-REV), thus to extend driving distance, a high efficiency regenerative braking control strategy for E-REV was proposed. Based on the co-simulation platform with AVL-Cruise and Simulink, a dynamic model for E-REV was set up and simulation calculations on hybrid motor-mechanical regenerative braking were performed. The simulation results with typical driving cycles illustrate that the friction braking force and the regenerative braking force could be well integrated, braking energy recovery efficiency was high, and the proposed control strategy of regenerative braking in the paper is effective.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

1122-1126

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.1122

Citation:

Cite this paper

Online since:

August 2014

Authors:

Ji Gao Niu*, Chun Hua Xu

Keywords:

Control Strategy, Co-Simulation, Extended-Range Electric Vehicle, Recovery Rate, Regenerative Braking

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Bassett M, Thatcher I, Bisordi A, et al. Design of a dedicated range extender engine. SAE Technical Paper, 2011-01-0862.

DOI: 10.4271/2011-01-0862

Google Scholar

[2] Komatsu M, Takaoka T, Ishikawa T, et al. Study on the Potential Benefits of Plug-in Hybrid Systems [C]. SAE Paper 2008-01-0456.

DOI: 10.4271/2008-01-0456

Google Scholar

[3] Freyermuth V, Fallas E, Rousseau A. Comparison of Powertrain Configuration for Plug-in HEVs from a Fuel Economy Perspective [C]. SAE Paper 2008-01-0461.

DOI: 10.4271/2008-01-0461

Google Scholar

[4] Jigao Niu, Su Zhou. Fuzzy Logic Control Strategy for an Extended-range Electric Vehicle [C]. Applied Mechanics and Materials, 2012, Vol. 220-223: 968-972.

DOI: 10.4028/www.scientific.net/amm.220-223.968

Google Scholar

[5] Matthe R, Turner L, Mettlach H. VOLTEC battery system for electric vehicle with extended range [J]. SAE International, 2011, 4 (1): 1944-(1962).

DOI: 10.4271/2011-01-1373

Google Scholar

[6] Tate E D, Harpster M O, Savagian P J. Savagian. The Electrification of the Automobile: From Conventional Hybrid, to Plug-in hybrids, to Extended-Range Electric Vehicles[C]. SAE Paper 2008-01-0458.

DOI: 10.4271/2008-01-0458

Google Scholar

[7] Shu Hong, Qin Datong, Hu Minghui, et al. Regenerative Braking Energy Management Strategy for Mild Hybrid Electric Vehicles[J]. Chinese Journal of Mechanical Engineering, Vol. 45(1): 167-173.

DOI: 10.3901/jme.2009.01.167

Google Scholar