@article{novak_energy-efficient_nodate,
	title = {Energy-{Efficient} {Model} {Predictive} {Train} {Traction} {Control} {With} {Incorporated} {Traction} {System} {Efficiency}},
	issn = {1524-9050},
	doi = {10.1109/TITS.2020.3046416},
	abstract = {The control system for energy-efficient train operation with the inclusion of a detailed train motion model and train traction system energy efficiency is presented in the paper. A piecewise affine train model is constructed with the parameters obtained for the electromotive train of an industrial manufacturer. The model encompasses intrinsic features of the train system such as linearized resistance force, a set of traction and braking force physical limitations and passengers comfort constraints. The resulting quadratic optimization problem is solved parametrically through dynamic programming giving the off-line precomputed optimal control law that is a function of train speed and traversed path. The on-line computed traction force profile is then tuned with respect to the traction system energy efficiency. The developed control system is evaluated on a detailed real case study scenario put together with a railway operator and the train manufacturer. The presented results show the possibility of significant energy consumption reductions achieved by energy-efficient train control.},
	language = {English},
	journal = {IEEE TRANSACTIONS ON IN℡LIGENT TRANSPORTATION SYSTEMS},
	author = {Novak, Hrvoje and Lesic, Vinko and Vasak, Mario},
	note = {Place: 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Type: Article; Early Access},
	keywords = {Adhesives, Energy-efficient train traction control, Force, Optimization, Predictive models, Rail transportation, Rails, Resistance, explicit model predictive control, mixed-integer quadratic programming, piecewise affine train model, traction system energy efficiency},
}

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The resulting quadratic optimization problem is solved parametrically through dynamic programming giving the off-line precomputed optimal control law that is a function of train speed and traversed path. The on-line computed traction force profile is then tuned with respect to the traction system energy efficiency. The developed control system is evaluated on a detailed real case study scenario put together with a railway operator and the train manufacturer. 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A piecewise affine train model is constructed with the parameters obtained for the electromotive train of an industrial manufacturer. The model encompasses intrinsic features of the train system such as linearized resistance force, a set of traction and braking force physical limitations and passengers comfort constraints. The resulting quadratic optimization problem is solved parametrically through dynamic programming giving the off-line precomputed optimal control law that is a function of train speed and traversed path. The on-line computed traction force profile is then tuned with respect to the traction system energy efficiency. The developed control system is evaluated on a detailed real case study scenario put together with a railway operator and the train manufacturer. 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