A white-box equivalent neural network circuit model for SoC estimation of electrochemical cells
Smart grids, microgrids, and pure electric powertrains are the key technologies for achieving the expected goals concerning the restraint of CO₂ emissions and global warming. In this context, an effective use of electrochemical energy storage systems (ESSs) is mandatory. In particular, accurate state of charge (SoC) estimations are helpful for improving the ESS performances. To this aim, developing accurate models of electrochemical cells is necessary for implementing effective SoC estimators. Therefore, a novel neural network modeling technique is proposed in this paper.