Determining Battery State of Charge
Accurate prediction of state of charge (SoC) of a cell / battery pack is crucial to the widespread uptake of energy storage / EV’s, as errors in the prediction of SoC in EVs for example can lead to a reduced operating range for the pack.
This is due to ‘range anxiety’, which make the installed pack oversized for the actual usage. In grid support, errors in predicting SoC can lead to unplanned non-availability, and therefore leads to reduced SoC operating range for the system, and hence reduced income.
At the University of Sheffield we have techniques for accurately determining battery SoC based on dynamic models of the cells / packs, with predictor / corrector approaches to ensuring the models parameters are optimised.
The systems are capable of locking onto Battery SoC even in the situation where they are initialised with the incorrect conditions. The systems are applicable to most battery chemistries and can be implemented in battery management hardware, across battery pack size ranges from a few cells to in excess of 20,000 cells.
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