  Real-time battery modelling advancements have quickly become a requirement 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 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 models. 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 sensitivity analysis on
the resultant computational time is completed as well as experimental
validation of a worldwide harmonised light vehicle test procedure (WLTP) for a
LG Chem. M50 21700 parameterisation. A performance comparison to the
conventional Matlab implemented discrete realisation algorithm (DRA) is
completed showcasing a mean computational time improvement of 88%. Finally, an
ARM based compilation is investigated for in-vehicle model generation and shows
a modest performance reduction of 43% when compared to the x86 implementation
while still generating accurate models within 5.5 seconds.
