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Design and Development of Real-Time Optimal Energy Management System for Hybrid Electric Vehicles
Abstract:This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1129167Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1170
 E. I. A. O. of Integrated Analysis and F. U. D. of Energy Washington, “Annual energy outlook 2009 with projections to 2030,” no. DOE/EIA-0383(2009), 2009.
 S. Onori, L. Serrao, and G. Rizzoni, “Hybrid electric vehicles: Energy management strategies,” ser. SpringerBriefs in Electrical and Computer Engineering. Springer London, 2015. (Online). Available: https://books.google.com/books?id=HCY3CwAAQBAJ
 G. Paganelli, G. Ercole, A. Brahma, Y. Guezennec, and G. Rizzoni, “General supervisory control policy for the energy optimization of charge-sustaining hybrid electric vehicles,” vol. 22, no. 4. Elsevier, 2001, pp. 511–518.
 S. Fekri and F. Assadian, “Fast model predictive control and its application to energy management of hybrid electric vehicles.” INTECH Open Access Publisher, 2011.
 A. Chasse and A. Sciarretta, “Supervisory control of hybrid powertrains: An experimental benchmark of offline optimization and online energy management,” vol. 19, no. 11. Elsevier, 2011, pp. 1253–1265.
 A. Taghavipour, N. L. Azad, and J. McPhee, “Real-time predictive control strategy for a plug-in hybrid electric powertrain,” vol. 29. Elsevier, 2015, pp. 13–27.
 A. Alessio and A. Bemporad, “A survey on explicit model predictive control,” in Nonlinear model predictive control. Springer, 2009, pp. 345–369.
 A. Taghavipour, N. L. Azad, and J. McPhee, “Multi-parametric energy management system with reduced computational complexity for plug-in hybrid electric vehicles,” in Control Conference (ECC), 2015 European. IEEE, 2015, pp. 3377–3382.
 R. Haber, R. Bars, and U. Schmitz, “Predictive control in process engineering: From the basics to the applications.” John Wiley & Sons, 2012.
 A. Sciarretta, M. Back, and L. Guzzella, “Optimal control of parallel hybrid electric vehicles,” vol. 12, no. 3. IEEE, 2004, pp. 352–363.
 L. Guzzella, A. Sciarretta et al., “Vehicle propulsion systems,” vol. 1. Springer, 2007.
 J. Liu, H. Peng, and Z. Filipi, “Modeling and analysis of the toyota hybrid system,” vol. 200, 2005, p. 3.