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Fault Detection and Isolation for Lithium-Ion Battery System Using Structural Analysis and Sequential Residual Generation

[+] Author Affiliations
Zhentong Liu

Beijing Institute of Technology, Beijing, ChinaThe Ohio State University, Columbus, OH

Qadeer Ahmed, Giorgio Rizzoni

The Ohio State University, Columbus, OH

Hongwen He

Beijing Institute of Technology, Beijing, China

Paper No. DSCC2014-6101, pp. V002T36A005; 10 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


This paper presents a systematic methodology based on structural analysis and sequential residual generators to design a Fault Detection and Isolation (FDI) scheme for nonlinear battery systems. The faults to be diagnosed are highlighted using a detailed hazard analysis conducted for battery systems. The developed methodology includes four steps: candidate residual generators generation, residual generators selection, diagnostic test construction and fault isolation. State transformation is employed to make the residuals realizable. The simulation results show that the proposed FDI scheme successfully detects and isolates the faults injected in the battery cell with cooling system at different times. In addition, there are no false or missed detections of the faults.

Copyright © 2014 by ASME



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