Journal Article


A computationally informed realisation algorithm for lithium-ion batteries implemented with LiiBRA.jl

Abstract

Real-time battery modelling advancements have quickly become required as the adoption of battery electric vehicles (BEVs) has rapidly increased. In this paper an open-source, improved discrete realisation algorithm, implemented in Julia for the creation and simulation of reduced-order, real-time capable physics-based models is presented. This work reduces the Doyle–Fuller–Newman electrochemical model into continuous-form transfer functions and introduces a computationally informed discrete realisation algorithm (CI-DRA) to generate the reduced-order representation. Further improvements in conventional offline model creation are obtained as well as achieving in-vehicle capable model creation for ARM-based computing architectures. Furthermore, a parametric sensitivity analysis of the presented architecture is completed as well as experimental validation of a worldwide harmonised light vehicle test procedure (WLTP) for an LG Chem. M50 21700 parameterisation. A performance comparison to a MATLAB implementation is completed showcasing a mean computational time improvement of 3.51 times for LiiBRA.jl on x86 hardware. Finally, an ARM-based implementation showcases full system model generation within three minutes for potential in-vehicle.

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Authors

Planden, Brady
Lukow, Katie
Henshall, Paul
Collier, Gordana
Morrey, Denise

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: 2022
Date of RADAR deposit: 2023-06-29


Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License


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