Modelling driving behaviour and its impact on the energy management problem in hybrid electric vehicles

REFERENCES

• E. Ericsson, Independent driving pattern factors and their influence on fuel-use and exhaust emission factors, Transp. Res. D 6 (2001), pp. 325–345. doi: 10.1016/S1361-9209(01)00003-7
   Web of Science ®Google Scholar
• Q. Gong, P. Tulpule, V. Marano, S. Midlam-Mohler, and G. Rizzoni, The role of ITS in PHEV performance improvement, 2011 American Control Conference, June–July, San Francisco, CA, 2011, pp. 2119–2124.
   Google Scholar
• C. Guardiola, B. Pla, S. Onori, and G. Rizzoni, A new approach to optimally tune the control strategy for hybrid vehicles applications, IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM’12, October, Rueil-Malmaison, France, 2012.
   Google Scholar
• L. Guzzella and A. Sciarretta, Vehicle Propulsion Systems. Introduction to Modeling and Optimization, Springer-Verlag, Berlin, 2005.
   Google Scholar
• L. Johannesson, M. Asbogard, and B. Egardt, Assessing the potential of predictive control for hybrid vehicle powertrain using stochastic dynamic programming, IEEE Trans. Intell. Transp. Syst. 8 (2007), pp. 71–83. doi: 10.1109/TITS.2006.884887
   Web of Science ®Google Scholar
• I. Kolmanovsky, I. Siverguina, and B. Lygoe, Optimization of powertrain operating policy for feasibility assessment and calibration: Stochastic dynamic programming approach, American Control Conference, May 8–10, Anchorage, AK, 2002, pp. 1425–1430.
   Google Scholar
• J. Liu and H. Peng, Modeling and control of a power-split hybrid vehicle, IEEE Trans. Control Syst. Technol. 16 (2008), pp. 1242–1251. doi: 10.1109/TCST.2007.903073
   Web of Science ®Google Scholar
• C. Musardo, G. Rizzoni, Y. Guezennec, and B. Staccia, A-ECMS: An adaptive algorithm for hybrid electric vehicle energy management, Eur. J. Control Fundam. Issues in Control, Special Issue 11 (2005), pp. 1816–1823.
   Google Scholar
• G. Paganelli, G. Ercole, A. Brahma, Y.G. Guezennec, and G. Rizzoni, General supervisory control policy for the energy optimization of charge-sustaining hybrid electric vehicles, JSAE Rev. 22 (2001), pp. 511–518. doi: 10.1016/S0389-4304(01)00138-2
   Google Scholar
• F. Payri, C. Guardiola, B. Pla, and D. Blanco-Rodriguez, On a stochastic approach of the ECMS method for energy management in hybrid electric vehicles, IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM’12, October, Rueil-Malmaison, France, 2012.
   Google Scholar
• G. Rizzoni, L. Guzzella, and B.M. Baumann, Unified modeling of hybrid electric vehicle drivetrains, IEEE/ASME Trans. Mechatronics 4 (1999), pp. 246–257. doi: 10.1109/3516.789683
   Web of Science ®Google Scholar
• A. Sciarreta and L. Guzzella, Control of hybrid electric vehicles, IEEE Control Syst. Mag. 27 (2007), pp. 60–70. doi: 10.1109/MCS.2007.338280
   Web of Science ®Google Scholar
• L. Serrao, S. Onori, and G. Rizzoni, ECMS as realization of Pontryagin's minimum principle for HEV control, 2009 American Control Conference, June, Saint Louis, MO, 2009, pp. 3964–3969.
   Google Scholar
• L. Serrao, S. Onori, and G. Rizzoni, A comparative analysis of energy management strategies for hybrid electric vehicles, J. Dyn. Syst. Meas. Control 133 (2011), pp. 1–9. doi: 10.1115/1.4003267
   Web of Science ®Google Scholar
• S. Stockar, V. Marano, M. Canova, G. Rizzoni, and L. Guzzella, Energy-optimal control of plug-in hybrid electric vehicles for real-world driving cycles, IEEE Trans. Veh. Technol. 60 (2011), pp. 2949–2962. doi: 10.1109/TVT.2011.2158565
   Web of Science ®Google Scholar
• O. Sundström, D. Ambühl, and L. Guzzella, On implementation of dynamic programming for optimal control problems with final state constraints, Oil Gas Sci. Technol. Rev. IFP 65 (2010), pp. 91–102. doi: 10.2516/ogst/2009020
   Web of Science ®Google Scholar
• O. Sundström and L. Guzzella, A generic dynamic programming Matlab function, 18th IEEE International Conference on Control Applications Part of 2009 IEEE Multi-conference on Systems and Control, July, Saint Petersburg, 2009, pp. 1625–1630.
   Google Scholar
• R. Wang and S.M. Lukic, Review of driving conditions prediction and driving style recognition based control algorithms for hybrid electric vehicles, Vehicle Power and Propulsion Conference (VPPC), 2011 IEEE, September 6–9, Raleigh, NC, 2011, pp. 1–7.
   Google Scholar