Journal
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
Volume 2, Issue 4, Pages 417-431Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TTE.2016.2571778
Keywords
Battery state estimation; electrochemical-based model; extended Kalman filter (EKF); lithium-ion battery modeling; single-particle model (SPM)
Funding
- Canada Excellence Research Chairs Program
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Modeling of lithium-ion cells is a key task in the development of a battery management system to achieve battery pack safety and reliable operation. Electrochemical-based approaches enable modeling of internal electrochemical processes within the lithium-ion cell. Several reduced-order electrochemical-based modeling approaches amenable for online battery state estimation are reviewed in this paper. In particular, aging effects such as the solid-electrolyte interface layer growth is modeled. The single-particle-model (SPM) method is extended using the following novelties: 1) numerical solution of the diffusion equation in the solid phase; 2) sensitivity on the numerical solution accuracy considering the number of shell partitions; 3) a new parameterization method that identifies pertinent parameters; 4) state-of-charge and state-of-health estimation algorithms based on hybrid SPM (HSPM); and 5) validations of SPM- and HSPM-based estimation algorithms using drive cycle data.
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