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Model-Based Fault Detection of a Battery System in a Hybrid Electric Vehicle



Author(s)

S. Andrew Gadsden and Saeid R. Habibi

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DOI:10.17265/1934-8975/2013.07.016

Department of Mechanical Engineering, McMaster University, Hamilton L8S 4L7, Ontario, Canada

Recently, a new type of IMM (interacting multiple model) method was introduced based on the relatively new SVSF (smooth variable structure filter), and is referred to as the IMM-SVSF. The SVSF is a type of sliding mode estimator that is formulated in a predictor-corrector fashion. This strategy keeps the estimated state bounded within a region of the true state trajectory, thus creating a stable and robust estimation process. The IMM method may be utilized for fault detection and diagnosis, and is classified as a model-based method. In this paper, for the purposes of fault detection, the IMM-SVSF is applied through simulation on a simple battery system which is modeled from a hybrid electric vehicle.

Battery system, fault detection and diagnosis, interacting multiple model, smooth variable structure filter, Kalman filter.