  Advanced battery management is to lithium-ion battery systems as the brain is
to the human body. Its performance rests on the use of battery models that are
both fast and accurate. However, mainstream equivalent circuit models and
electrochemical models have yet to meet this need well, due to struggle with
either predictive accuracy or computational complexity. This problem has
acquired urgency as some emerging battery applications running across broad
current ranges, e.g., electric vertical take-off and landing aircraft, can
hardly find usable models from the literature. Motivated to address the
problem, we develop an innovative model in this study. Called BattX, the model
is an equivalent circuit model but draws comparisons to a single particle model
with electrolyte and thermal dynamics, thus combining their respective merits
to be computationally efficient, accurate, and physically interpretable. The
model design pivots on leveraging multiple circuits to approximate major
electrochemical and physical processes in charging/discharging. Given the
model, we develop a multipronged approach to design experiments and identify
its parameters in groups from experimental data. Experimental validation proves
that the BattX model is capable of accurate voltage prediction for
charging/discharging across low to high C-rates.

Systems and Control;Systems and Control