Paper Info
Title
Nonlinear MPC-based power-assist scheme of internal combustion engines in plug-in hybrid electric vehicles
Abstract
Power optimal control of plug-in hybrid electric vehicles (PHEVs) is a considerable issue due to the promising technology of PHEVs comparing with the other hybrid electric vehicles (HEVs). A case study that focuses on the power-assist operation by the internal combustion engine in the plug-in hybrid electric vehicle (PHEV) system is investigated. A formulation for the fuel economy optimal control problem is presented. A new nonlinear MPC method that uses the Continuous/GMRES algorithm is proposed to solve the optimal control problem. Besides the constraint condition of the dynamics of the battery state of charge (SoC), as far as the driving pattern of the driver is concerned, the vehicle velocity dynamics is also taken as the constraint condition of the predictive-based optimal control problem. The developed control scheme is implemented on a power-split hybrid electric vehicle (HEV) simulator constructed based on the JSAE-SICE benchmark problem. Using a driving scenario and a real-world driving cycle, simulation studies are conducted to evaluate the nonlinear MPC algorithm.
Year
DOI
Venue
2014
10.1109/ECC.2014.6862343
ECC
Keywords
Field
DocType
fuel economy,hybrid electric vehicles,internal combustion engines,nonlinear control systems,optimal control,power control,predictive control,vehicle dynamics,jsae-sice benchmark problem,phev system,soc,battery state of charge,constraint condition,continuous-gmres algorithm,fuel economy optimal control problem,model predictive-based optimal control problem,nonlinear mpc-based power-assist scheme,plug-in hybrid electric vehicle system,power optimal control,power-split hybrid electric vehicle simulator,real-world driving cycle,vehicle velocity dynamics,engines,generators,gears,torque
Automotive engineering,Combustion,Internal combustion engine,Nonlinear system,Optimal control,Generalized minimal residual method,Electric vehicle,Control theory,Hybrid power,Engineering,Driving cycle
Conference
Citations 
PageRank 
References 
1
0.48
8
Authors
2
Name
Order
Citations
PageRank
Jiangyan Zhang1277.02
Tielong Shen224340.52