An Acausal Li-Ion Battery Pack Model for Automotive Applications

Kotub Uddin, Alessandro Picarelli, Christopher Lyness, Nigel Taylor, James Marco
<span title="2014-08-28">2014</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a2yvk5xhdnhpxjnk6yd33uudqq" style="color: black;">Energies</a> </i> &nbsp;
In this work, a novel acausal and reconfigurable battery pack model is presented. The model structure adopted for the battery cell is based on an equivalent circuit representation. The circuit elements are modified to take account of both hysteresis and diffusion limitation. The latter is known to be a nonlinear function of large operating currents or long operating times. It is shown that the integration of a current dependent time constant within the cell model better emulates the solid
more &raquo; ... ional dynamics of lithium intercalation into the active material under large electrical loads. The advantages of an acausal modeling approach, when scaling-up individual cell models into a complete battery system are also presented. Particular consideration is given to emulating the impact of cell to cell variations on pack performance. Using statistical analysis of battery tests, cell model parameter variations are characterized and quantified. The cell and scaled-up pack model are parameterized for a number of commercially available cell formats, energy capacities and chemistries. The new models are validated using transient, real-world, electrical data measured from an electric vehicle (EV) operating within an urban environment.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/en7095675">doi:10.3390/en7095675</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4kvldbfmb5gnnhve3xhm4kwy64">fatcat:4kvldbfmb5gnnhve3xhm4kwy64</a> </span>
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