%0 Conference Proceedings %T A two-layer predictive control for hybrid electric vehicles energy management %+ Technocentre Renault [Guyancourt] %+ Laboratoire des signaux et systèmes (L2S) %+ Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME) %A Stroe, Nicoleta %A Olaru, Sorin %A Colin, Guillaume %A Ben-Cherif, Karim %A Chamaillard, Yann %< avec comité de lecture %Z ECM %B IFAC 2017 - 20th World Congress of the International Federation of Automatic Control %C Toulouse, France %3 Preprints of the 20th World Congress, The International Federation of Automatic Control, Toulouse, France, July 9-14, 2017 %P 10475-10481 %8 2017-07-09 %D 2017 %K hybrid electric vehicle %K energy management %K predictive control %Z Engineering Sciences [physics]/AutomaticConference papers %X In this paper, a two-layer predictive energy management strategy for hybrid electric vehicles without an external recharge is introduced. The low-level layer exploits telemetry data over a short-term horizon in a model predictive control structure that provides the engine torque, but also the stop-start decision. The upper layer uses a tuning mechanism with a longer horizon to calculate the MPC weighting factor that ensures a balance between the fuel and battery consumption. An analysis of this upper-level tuning prediction horizon dependence on the drive cycle characteristics is performed. The robustness with respect to state-of-charge and engine torque estimation is also proven by a sensitivity analysis. %G English %2 https://univ-orleans.hal.science/hal-01566029/document %2 https://univ-orleans.hal.science/hal-01566029/file/IFACWC2017_Stroe_el_al_MPC_HEV.pdf %L hal-01566029 %U https://univ-orleans.hal.science/hal-01566029 %~ CNRS %~ UNIV-ORLEANS %~ UNIV-PSUD %~ SUP_LSS %~ SUP_SYSTEMES %~ CENTRALESUPELEC %~ TDS-MACS %~ UNIV-PARIS-SACLAY %~ UNIV-PSUD-SACLAY %~ CENTRALESUPELEC-SACLAY %~ PRISME-CVL %~ INSA-GROUPE %~ INSA-CVL %~ GS-ENGINEERING %~ GS-COMPUTER-SCIENCE