Coupling Temperature Distribution with the Single Particle Model

TL;DR

This paper introduces a reduced-order model that couples temperature distribution with the single particle model within the DFN framework, balancing accuracy and computational efficiency for thermal-electrochemical battery simulations.

Contribution

A novel reduced-order model integrating temperature effects into the single particle framework, simplifying electrolyte dynamics with a correction term.

Findings

Model captures temperature effects with reduced complexity

Maintains accuracy comparable to full DFN models

Enables faster simulations for thermal management

Abstract

The DFN (Doyle-Fuller-Newman) model is well know for being accurate and computationally expensive. In situations where temperature gradients are important (eg fast charging) it is desirable to couple the temperature dynamics within a battery into the DFN model. This leads to even greater computational complexity. Inspired by the work of Marquis et al [1] we present the derivation of a reduced-order model based on the DFN model with temperature in the macroscale. The complexity of the reduced-order model is characterised by the local temperature plus one internal electro-chemical dimension and the electrolyte dynamics is accounted for by a simple correction term.