A Computationally Efficient Implementation of an Electrochemistry-Based Model for Lithium-Ion Batteries

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. 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 spatial and temporal discretisation of the governing partial differential equations and a particular numerical method for solving the resulting discretised model equations, which is based on a damped Newton’s method. In a simulation study, the numerical efficiency of the proposed implementation is shown.