Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6681838 | Applied Energy | 2017 | 12 Pages |
Abstract
Lithium-ion batteries are commonly employed in various applications owing to high energy density and long service life. Lithium-ion battery models are used for analysing batteries and enabling power control in applications. The Doyle-Fuller-Newman (DFN) model is a popular electrochemistry-based lithium-ion battery model which represents solid-state and electrolyte diffusion dynamics and accurately predicts the current/voltage response using a set of nonlinear partial differential equations. However, implementation of the full DFN model requires significant computation time. This paper proposes a computationally efficient implementation of the full DFN battery model, which is convenient for real-time applications. The proposed implementation is based on applying model order reduction to a spatial and temporal discretisation of the governing model equations. For model order reduction, we apply proper orthogonal decomposition and discrete empirical interpolation method, which leads to a set of reduced order nonlinear algebraic equations. These equations are solved using a particular numerical scheme, based on a damped Newton's method. In a simulation study, the computational efficiency of the proposed implementation is shown and the resulting accuracy is presented.
Keywords
Related Topics
Physical Sciences and Engineering
Energy
Energy Engineering and Power Technology
Authors
L. Xia, E. Najafi, Z. Li, H.J. Bergveld, M.C.F. Donkers,