access icon free Global optimal energy management control strategies for connected four-wheel-drive hybrid electric vehicles

© The Institution of Engineering and Technology
Received 25/07/2016, Accepted 28/02/2017, Revised 22/01/2017, Published 03/03/2017

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.

Inspec keywords: dynamic programming; optimal control; fuel economy; energy management systems; predictive control; hybrid electric vehicles; level control; wheels

Other keywords: optimal cruising velocity; level controller; dynamic programming problem; HEVs; fuel economy; decentralised hierarchical global energy management control strategy; model predictive control framework; global optimal energy management control strategy; connected four-wheel-drive hybrid electric vehicles; global energy management optimisation; target velocity generation; urban road conditions; timing information

Subjects: Transportation system control; Optimisation techniques; Optimisation techniques; Optimal control; Control of electric power systems; Transportation; Level, flow and volume control

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