NDLI: An electrochemical model-based particle filter approach for Lithium-ion battery estimation

Content Provider	IEEE Xplore Digital Library
Author	Samadi, M.F. Alavi, S.M.M. Saif, M.
Copyright Year	2012
Description	Author affiliation: School of Engineering Science, Simon Fraser University, Burnaby, B. C., V5A 1S6, Canada (Samadi, M.F.) \|\| Department of Electrical and Computer Engineering, Concordia University, Montreal, Q.C., Canada (Alavi, S.M.M.) \|\| Faculty of Engineering, University of Windsor, 401 Sunset Avenue, O.N., N9B3P4, Canada (Saif, M.)
Abstract	Lithium-ion batteries are currently amongst the leading technologies for electrical energy storage. In automotive industry they are recognized as the most promising alternative to gasoline powered engines. State estimation of the state of the battery can provide useful information regarding the state of charge (SOC) and state of health (SOH) of the battery which play a crucial role in optimal and safe utilization of the battery. Although the electrochemical dynamics of the battery are described by nonlinear system of PDAEs, most works in the area of condition monitoring of the battery resort to empirical or equivalent electrical circuit models. These models don't provide any physical insight into the battery and lack insight into physical limitations of the battery. This work presents a particle filter algorithm for state estimation and condition monitoring of the Li-ion battery. This filter can effectively deal with the nonlinear and complex nature of the PDAEs describing the dynamics of the battery. It provides accurate estimation of the average as well as spatial distribution of concentration in the battery. The simulation results demonstrate the effectiveness of the proposed estimation algorithm.
Starting Page	3074
Ending Page	3079
File Size	197303
Page Count	6
File Format	PDF
ISBN	9781467320658
ISSN	07431546
e-ISBN	9781467320665
e-ISBN	9781467320641
DOI	10.1109/CDC.2012.6426009
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Batteries Mathematical model Equations Estimation Heuristic algorithms Particle filters Electrodes
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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