A two-layer predictive control for hybrid electric vehicles energy management

Nicoleta Stroe (1, 2, 3) , Sorin Olaru (2) , Guillaume Colin (3) , Karim Ben-Cherif (1) , Yann Chamaillard (3)

1 Technocentre Renault [Guyancourt]
2 L2S - Laboratoire des signaux et systèmes
3 PRISME - Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique

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.

Keywords: hybrid electric vehicle; energy management; predictive control

Domains: Engineering Sciences [physics]; Automatic

Nicoleta Stroe, Sorin Olaru, Guillaume Colin, Karim Ben-Cherif, Yann Chamaillard. A two-layer predictive control for hybrid electric vehicles energy management. IFAC 2017 - 20th World Congress of the International Federation of Automatic Control, The International Federation of Automatic Control, Jul 2017, Toulouse, France. pp.10475-10481. ⟨hal-01566029⟩