Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Capancioni, Alessandro (2022) Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Automotive per una mobilità intelligente, 34 Ciclo. DOI 10.48676/unibo/amsdottorato/10044.
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Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

Tipologia del documento
Tesi di dottorato
Capancioni, Alessandro
Dottorato di ricerca
Settore disciplinare
Settore concorsuale
Parole chiave
hybrid electric vehicles (HEVs) Software-in-the-Loop (SiL) Hardware-in-the-Loop (HiL) vehicle-to-everything (V2X) zero-emission zone (ZEZ) predictive functions energy management equivalent consumption minimization strategy (ECMS) dynamic programming (DP)
Data di discussione
30 Marzo 2022

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