Accurate modeling of electrochemical batteries isof major concern in designing the control system of EnergyStorage Systems (ESS). In particular, a precise estimation ofState of Charge (SOC) and State of Health (SOH) parametersstrongly affects the full exploitation of battery energy potential inreal applications. In this paper a novel real-time estimationmethod is presented representing a good tradeoff between modelaccuracy and algorithm complexity. In the proposed approach,SOC and SOH values are determined by a suitable algorithmthat continuously performs a comparison between the ESSvoltage value, calculated by an adaptive run-time circuital model,and its real value measured at the ESS terminals. The result ofsuch comparison is used to suitably tune two parameters of theESS circuital model, the no-load voltage and resistive voltagedrop, in order to compensate the inaccuracy of the modelresponse due to parameter variations.Initially, to set the parameter of ESS electrical model, theproposed approach requires to carry out short preliminary teststhat can be easily implemented in a low cost control units.Experimental results and comparisons with other estimationmethods highlight the consistency of the proposed algorithm.

Real-time model-based estimation of SOC and SOH for energy storage systems

CACCIATO, MARIO;SCARCELLA, Giuseppe;SCELBA, GIACOMO
2015-01-01

Abstract

Accurate modeling of electrochemical batteries isof major concern in designing the control system of EnergyStorage Systems (ESS). In particular, a precise estimation ofState of Charge (SOC) and State of Health (SOH) parametersstrongly affects the full exploitation of battery energy potential inreal applications. In this paper a novel real-time estimationmethod is presented representing a good tradeoff between modelaccuracy and algorithm complexity. In the proposed approach,SOC and SOH values are determined by a suitable algorithmthat continuously performs a comparison between the ESSvoltage value, calculated by an adaptive run-time circuital model,and its real value measured at the ESS terminals. The result ofsuch comparison is used to suitably tune two parameters of theESS circuital model, the no-load voltage and resistive voltagedrop, in order to compensate the inaccuracy of the modelresponse due to parameter variations.Initially, to set the parameter of ESS electrical model, theproposed approach requires to carry out short preliminary teststhat can be easily implemented in a low cost control units.Experimental results and comparisons with other estimationmethods highlight the consistency of the proposed algorithm.
2015
978-147998586-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/98879
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