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State-of-the-art lithium-ion cell chemistries with pronounced open-circuit voltage hysteresis (OCV), characterised by asymmetry and directional dependence, present a challenge for estimating the state of charge (SOC). Without understanding the hysteresis behaviour, OCV measurement points that lie within the hysteresis window cannot be used for SOC correction. After obtaining the data efficiency of the trajectory correction hysteresis (TCH) model with the introduction of the transfer fit (TF) method, this work applies the TF TCH for OCV-based SOC correction. The TF method plays a key role as it enables the cell-specific adaptation of an existing TCH model - ageing update is achieved with solely 12 (SOC/OCV) measurement points. With the precise hysteresis model, the developed framework successfully corrects the faulty SOC history, which could originate from a vehicle data logger. Given that two OCV measurement points are available that arbitrarily lie within the SOC history, the SOC correction is achieved by minimising the voltage deviation between the measurement points and the TCH model’s simulation. Identifying the two SOC parameters shift and scale enables subsequent SOC estimation until an additional OCV measurement is available for a further update. The functionality of the presented SOC correction framework is demonstrated using two validation profiles. • Application of trajectory correction hysteresis (TCH) model in a SOC estimation framework. • Efficient ageing update of TCH model based on 12 instead of 1000 SOC/OCV data due to transfer fit (TF) method. • Correction framework enables considering real-world SOC uncertainties in the modelling of hysteresis behaviour. • Offline SOC correction based on two arbitrary OCV measurements identifies SOC drift and offset parameter. • Drift and offset parameter allow continuous SOC estimation. • Proven for NMC cell with Si/C anode and up to 150 mV OCV hysteresis range.
Schmitt et al. (Sat,) studied this question.