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This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate (LiFePO 4 ) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.

This paper presents the design of a control system suitable for EV DC bus voltage sag compensation based on the voltage PI controller and load current feedforward compensator. The superimposed PI controller and feedforward compensator references are distributed between the inner battery and ultracapacitor current-controlled DC/DC converters so that the ultracapacitor takes on the highly-dynamic (transient) current demands, while the battery covers for steady-state loads. In order to avoid deep discharges of the ultracapacitor, the DC bus control system is also equipped with auxiliary state-of-charge (SoC) controller. The functionality of the superimposed DC bus voltage control system and inner current and SoC control loops has been verified by means of simulations and experimentally on a downscaled battery/ultracapacitor experimental (HIL) setup.

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