Title: Engine-in-the-loop study of the stochastic dynamic programming optimal control design for a hybrid electric HMMWV

Authors: Jinming Liu, Jonathan Hagena, Huei Peng, Zoran S. Filipi

Addresses: Mechanical Engineering Department, Automotive Research Centre, The University of Michigan, 1231 Beal Avenue, Ann Arbor, MI 48109-2133, USA. ' Mechanical Engineering Department, Automotive Research Centre, The University of Michigan, 1231 Beal Avenue, Ann Arbor, MI 48109-2133, USA. ' Mechanical Engineering Department, Automotive Research Centre, The University of Michigan, 1231 Beal Avenue, Ann Arbor, MI 48109-2133, USA. ' Mechanical Engineering Department, Automotive Research Centre, The University of Michigan, 1231 Beal Avenue, Ann Arbor, MI 48109-2133, USA

Abstract: This paper presents a Stochastic Dynamic Programming (SDP) methodology for automatic generation of an implementable hybrid control strategy, and addresses engine soot emissions during controller development by using an advanced Engine-In-the-Loop (EIL) setup. Coupling the real engine with the virtual driveline/vehicle enables application of fast analysers to characterise the impact of transients on engine emissions. The benefits of using the EIL for establishing driveability and soot emissions constraints, and subsequent application of the constraints for refining the SDP strategy is demonstrated through a study of a virtual parallel-hybrid system for the High-Mobility Multipurpose Wheeled Vehicle with a V8 6L engine.

Keywords: hybrid electric vehicles; HEVs; supervisory control; stochastic dynamic programming; EIL; engine-in-the-loop; visual signature; hybrid vehicles; hybrid control; engine emissions; soot emissions; driveability constraints; virtual parallel-hybrid systems; control design; optimal design; mobility; multipurpose wheeled vehicles.

DOI: 10.1504/IJHVS.2008.022247

International Journal of Heavy Vehicle Systems, 2008 Vol.15 No.2/3/4, pp.309 - 326

Available online: 24 Dec 2008 *

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