Acceleration Control for a Plug-in Series Hybrid Electric Vehicle

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Acceleration control using fuzzy logic is investigated in this paper for a plug-in series hybrid electric vehicle in order to improve the vehicle response to drivers demand. The transient process of acceleration is mainly considered in this research. Fuzzy logic is used for motor transient torque control according to drivers input and vehicle velocity, outputting a regulatory factor to increase motor torque transiently when drivers acceleration pedal is pushed down deeply and to reduce the torque increment when acceleration process is close to over. Performance of fuzzy control is tested by MATLAB simulation. Simulation results indicate that the presented fuzzy algorithm is feasible and effective for improving vehicle acceleration ability without damaging stable velocity control characteristic; in simulation, vehicle acceleration time of 0-100km/h has been reduced by 2.4 seconds.

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499-503

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] E. Sortomme, M. M. Hindi, S. D. James, et al, Coordinated charging of plug-in hybrid electric vehicles to minimize distribution system losses, J. IEEE Trans. Smart Grid, 2(2011) 198–205.

DOI: 10.1109/tsg.2010.2090913

Google Scholar

[2] A. M. Phillips, M. Jankovic, K. Bailey, Vehicle system controller design for a hybrid electric vehicle, J. Proc. IEEE Int. Conf. Control Appl. 9(2000) 297–302.

DOI: 10.1109/cca.2000.897440

Google Scholar

[3] S. G. Wirasingha, A. Emadi, Classification and review of control strategies for plug-in hybrid electric vehicles, J. IEEE Trans. Veh. Technol. 60(2011) 111–122.

DOI: 10.1109/tvt.2010.2090178

Google Scholar

[4] P. Rodatz, G. Paganelli, A. Sciarretta, et al, Optimal power management of an experimental fuel cell/supercapacitor powered hybrid vehicle, J. Control Engineering Practice. 13(2005) 41-53.

DOI: 10.1016/j.conengprac.2003.12.016

Google Scholar

[5] F. Syed, M. Kuang, M. Smith, et al. Fuzzy gainscheduling proportional–integral control for improving engine power and speed behavior in a hybrid electric vehicle, J. IEEE Trans. Veh. Technol. 58(2009) 69–84.

DOI: 10.1109/tvt.2008.923690

Google Scholar

[6] J. H. Yan,W. S. Li, Q. Y. Zhan, Failure mechanism of valve-regulated lead-acid batteries under high-power cycling, J. Power Sources, 133(2004) 135–140.

DOI: 10.1016/j.jpowsour.2003.11.075

Google Scholar

[7] F. Syed, M. Kuang, J. Czubay, et al, Derivation and experimental validation of a power-split hybrid electric vehicle model, J. IEEE Trans. Veh. Technol. 55(2006)1731–1747.

DOI: 10.1109/tvt.2006.878563

Google Scholar

[8] K. Ahn, S. Cho, S. Cha, et al, Engine operation for the planetary gear hybrid powertrain, J. Proc. Inst. Mech. Eng. D: Automobile Eng. 220(2006) 1727–1735.

DOI: 10.1243/09544070jauto279

Google Scholar

[9] S. Poorani, K. U. Kumar, S. Renganarayanan, Design of a fuzzy based controller for electric vehicles on Indian roads, J. Proc. Inst. Mech. Eng. I: Syst. Control Eng. 221(2007) 61–74.

DOI: 10.1243/09596518jsce123

Google Scholar

[10] S. G. Li, S. M. Sharkh, F. C. Walsh, et al, Energy and battery management of a plug-in series hybrid electric vehicle using fuzzy logic, J. IEEE Trans. Veh. Technol. 8(2011) 3571-3584.

DOI: 10.1109/tvt.2011.2165571

Google Scholar