Estimation and Fault Diagnosis of Lithium-Ion Batteries: A Fractional-Order System Approach

Shulan Kong,Mehrdad Saif,Guozeng Cui

doi:10.1155/2018/8705363

Abstract

This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system. Two simple and common types of observers are designed to address the design of fault diagnosis and estimation for the fractional-order systems. Fractional-order Luenberger observers are employed to generate residuals which are then used to investigate the feasibility of model based fault detection and isolation. Once a fault is detected and isolated, a fractional-order sliding mode observer is constructed to provide an estimate of the isolated fault. The paper presents some theoretical results for designing stable observers and fault estimators. In particular, the notion of stability in the sense of Mittag-Leffler is first introduced to discuss the state estimation error dynamics. Overall, the design of the Luenberger observer as well as the sliding mode observer can accomplish fault detection, fault isolation, and estimation. The effectiveness of the proposed strategy on a three-cell battery string system is demonstrated.

Highlights

This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system
Lithium-ion (Li-ion) batteries are an integral part of electrified vehicles and have found many other areas of applications in consumer products, space, marine, and other applications
The main goal of this paper is to propose a strategy for fault detection, isolation, and estimation via fractional-order differential models

Summary

Introduction

Lithium-ion (Li-ion) batteries are an integral part of electrified vehicles and have found many other areas of applications in consumer products, space, marine, and other applications. They remain a costly and safety critical subsystem in many areas that they are used in. Reliability, safety, and efficient operation of Li-ion batteries in high power applications, such as in electrified vehicles, and challenging problems such as modeling, state estimation, monitoring, diagnostics, and pyrognostics capabilities are critical areas for research [1,2,3,4,5,6,7,8]. For almost two hundred years, fractionalorder models have been used to describe biology systems [10]

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