Title :
Nonlinear MPC-based power management strategy for plug-in parallel hybrid electrical vehicles
Author :
Zhang Jiangyan ; Shen Tielong ; Sawada, Tsuyoshi ; Kubo, Momoji
Author_Institution :
Coll. of Electromech. & Inf. Eng., Dalian Nat. Univ., Dalian, China
Abstract :
For hybrid electric vehicles (HEVs), fuel economy which is a significant performance index strongly depends on the power management strategy. In this paper, a new nonlinear MPC strategy is proposed to improve the fuel economy of a plug-in parallel hybrid electric vehicle (HEV). With the preview of the traffic and the battery state of charge (SoC) as well as all the physical constraints of the system, the power management control problem is formulated as a nonlinear optimization problem. A Continuous/GMRES method-based nonlinear MPC strategy is used to determine the power split ratios. Simulations over a real driving cycle is conducted on a HEV simulator built in the GT-Suite environment to evaluate the nonlinear MPC algorithm for real-time application.
Keywords :
battery powered vehicles; energy management systems; fuel economy; hybrid electric vehicles; nonlinear control systems; nonlinear programming; power control; predictive control; road traffic control; transport control; GT-suite environment; HEV; SoC; battery state of charge; continuous-GMRES method; fuel economy; model predictive control; nonlinear MPC-based power management strategy; nonlinear optimization problem; plug-in parallel hybrid electrical vehicle; power management control problem; power split ratio; Engines; Fuels; Gears; Hybrid electric vehicles; System-on-chip; Torque; Nonlinear MPC; Parallel HEV; Plug-in HEV; Power Management Strategy; Real-time Optimization;
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
DOI :
10.1109/ChiCC.2014.6896635