Development of an Efficient Thermal Electric Skipping Strategy for the Management of a Series/Parallel Hybrid Powertrain

Vincenzo De Bellis, Enrica Malfi and Jean-Marc Zaccardi
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Vincenzo De Bellis: Dipartimento Di Ingegneria Industriale, Università Degli Studi Di Napoli Federico II, 80125 Napoli, Italy
Enrica Malfi: Dipartimento Di Ingegneria Industriale, Università Degli Studi Di Napoli Federico II, 80125 Napoli, Italy
Jean-Marc Zaccardi: IFP Energies Nouvelles, Institut Carnot IFPEN Transports Energie, Rond-Point De L’échangeur de Solaize, BP 3, 69360 Solaize, France

Energies, 2021, vol. 14, issue 4, 1-24

Abstract: In recent years, the development of hybrid powertrain allowed to substantially reduce the CO 2 and pollutant emissions of vehicles. The optimal management of such power units represents a challenging task since more degrees of freedom are available compared to a conventional pure-thermal engine powertrain. The a priori knowledge of the driving mission allows identifying the actual optimal control strategy at the expense of a quite relevant computational effort. This is realized by the off-line optimization strategies, such as Pontryagin minimum principle—PMP—or dynamic programming. On the other hand, for an on-vehicle application, the driving mission is unknown, and a certain performance degradation must be expected, depending on the degree of simplification and the computational burden of the adopted control strategy. This work is focused on the development of a simplified control strategy, labeled as efficient thermal electric skipping strategy—ETESS, which presents performance similar to off-line strategies, but with a much-reduced computational effort. This is based on the alternative vehicle driving by either thermal engine or electric unit (no power-split between the power units). The ETESS is tested in a “backward-facing” vehicle simulator referring to a segment C car, fitted with a hybrid series-parallel powertrain. The reliability of the method is verified along different driving cycles, sizing, and efficiency of the power unit components and assessed with conventional control strategies. The outcomes put into evidence that ETESS gives fuel consumption close to PMP strategy, with the advantage of a drastically reduced computational time. The ETESS is extended to an online implementation by introducing an adaptative factor, resulting in performance similar to the well-assessed equivalent consumption minimization strategy, preserving the computational effort.

Keywords: hybrid powertrain; optimization strategy; computational efficiency; energy management; fuel economy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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