Title: Battery power management in heavy-duty HEVs based on the estimated critical surface charge

Authors: Tae-Kyung Lee; Youngki Kim; Denise M. Rizzo; Zoran S. Filipi

Addresses: Department of Mechanical Engineering, The University of Michigan, 1020 W.E. Automotive Laboratory, 1231 Beal Ave., Ann Arbor, MI 48109-2133, USA ' Department of Mechanical Engineering, The University of Michigan, 1020 W.E. Automotive Laboratory, 1231 Beal Ave., Ann Arbor, MI 48109-2133, USA ' US Army RDECOM TARDEC, 6501 E. 11 Mile Road, Warren, MI 48397-0001, USA ' Department of Mechanical Engineering, The University of Michigan, 2031 W.E. Automotive Laboratory, 1231 Beal Ave., Ann Arbor, MI 48109-2133, USA

Abstract: This paper proposes a battery power management strategy using Critical Surface Charge (CSC) information estimated by Extended Kalman Filter (EKF) in real time. The insight from CSC characterisation is used to propose a novel approach for supervisory control design of a series Hybrid Electric Vehicle (HEV). The underlying phenomenon determining the battery allowable power limits is closely connected to the CSC. The estimated CSC is processed with a Finite Impulse Response (FIR) filter to smoothen short-term fluctuations and highlight longer-term trajectories. The battery allowable power limits are adjusted based on the filtered CSC information to prevent undesirable battery operations.

Keywords: lithium-ion batteries; battery power management; CSC; critical surface charge; lithium-ion concentration; estimation; EKF; extended Kalman filter; HEVs; hybrid electric vehicles; supervisory control; control design; finite impulse response; FIR; battery power limits.

DOI: 10.1504/IJVD.2013.050842

International Journal of Vehicle Design, 2013 Vol.61 No.1/2/3/4, pp.108 - 127

Available online: 05 Dec 2012 *

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