Title: Model predictive control of a hybrid electric powertrain with combined battery and ultracapacitor energy storage system
Authors: Hoseinali Borhan; Ardalan Vahidi
Addresses: Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA ' Department of Mechanical Engineering, Clemson University, Clemson, SC 29634, USA
Abstract: Due to the high energy density characteristic of the batteries with respect to the ultracapacitors and high power density characteristic of the ultracapacitors with respect to the batteries, combining these electrical energy storage devices is believed to provide an effective energy storage system for the Hybrid Electric Vehicle (HEV) applications. A real-time energy management strategy which supervises the split of the driver demand power between the engine, the battery and the ultracapacitor of the HEV is required. This paper presents an optimisation-based energy management strategy for the optimal control of the propulsion system of an HEV with combined battery and ultracapacitor storage system; an optimal control problem with a quadratic cost function is defined and linear time-varying Model Predictive Control (MPC) framework is employed to solve it in real-time. The simulation results of a high-fidelity model of an HEV with power-split powertrain show that the proposed strategy can effectively distribute power between the different components of the HEV while the powertrain constraints are enforced and the charge and discharge rate of the battery is noticeably reduced.
Keywords: hybrid electric powertrains; energy management strategy; hybrid energy storage; ultracapacitors; supercapacitors; model predictive control; MPC; batteries; hbrid eElectric vehicles; HEVs; optimal control.
International Journal of Powertrains, 2012 Vol.1 No.4, pp.351 - 376
Accepted: 07 May 2012
Published online: 05 Dec 2014 *