Title: Stochastic model predictive power management strategy for series hydraulic hybrid vehicle

Authors: Daiwei Feng; Dagui Huang

Addresses: School of Mechatronics Engineering, University of Electronics Science and Technology of China, Chengdu, 611731, China. ' School of Mechatronics Engineering, University of Electronics Science and Technology of China, Chengdu, 611731, China

Abstract: With the expectation that series configuration would maximise the fuel economy as engine is decoupled from the wheels, a forward-facing, series hydraulic hybrid vehicle (SHHV) powertrain model for medium size trucks is developed in this paper, and is employed to investigate the application of stochastic model predictive control (SMPC) methodology for developing power management strategy. For properly managing all the control variables that arise from the significant freedoms introduced by the SHHV powertrain, two-level hierarchical control architecture is proposed. Simulation results over the urban driving cycle are presented to demonstrate the effectiveness of SMPC compared with other deterministic approaches and the potential of the selected hybrid system to substantially improve vehicle fuel economy.

Keywords: series hydraulic hybrid vehicles; vehicle modelling; hierarchical control; stochastic model predictive control; SMPC; fuel economy; power management strategy; powertrain models; medium size trucks; simulation; urban driving cycle.

DOI: 10.1504/IJMA.2012.046588

International Journal of Mechatronics and Automation, 2012 Vol.2 No.1, pp.51 - 63

Received: 22 Aug 2011
Accepted: 25 Feb 2012
Published online: 27 Nov 2014 *

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