This study presents a novel decentralised hierarchical global energy management control strategy for a group of connected four‐wheel‐drive hybrid electric vehicles (HEVs) in urban road conditions. In the higher level controller, signal phase and timing information and the optimal cruising velocity are combined to generate the target velocities for the HEVs. A model predictive control framework that focuses on the tracking of the target velocity and the associated desired control variable for every individual vehicle is proposed for the prediction of the optimal velocity that compromises fuel economy, mobility and safety. In the lower level controller, a dynamic programming problem is formulated that utilises the predicted velocity for the global energy management optimisation of every individual HEV. Simulation results validate the advantages of the proposed higher and lower level controllers.
Global optimal energy management control strategies for connected four‐wheel‐drive hybrid electric vehicles
IET Intelligent Transport Systems ; 11 , 5 ; 264-272
2017-06-01
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
energy management systems , optimal control , timing information , global optimal energy management control strategy , fuel economy , optimal cruising velocity , decentralised hierarchical global energy management control strategy , hybrid electric vehicles , urban road conditions , predictive control , level controller , target velocity generation , dynamic programming problem , global energy management optimisation , wheels , connected four‐wheel‐drive hybrid electric vehicles , level control , dynamic programming , HEVs , model predictive control framework
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