A robust extended Kalman filter (EKF) is proposed as a method for estimation of the state of charge (SOC) of lithium-ion batteries used in hybrid electric vehicles (HEVs). An equivalent circuit model of the battery, including its electromotive force (EMF) hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analyzed, and an optimized gain coefficient is determined to restrain battery terminal voltage from fluctuating. Experimental and simulation results are presented. SOC estimates using the standard EKF are compared with the proposed robust EKF algorithm to demonstrate the accuracy and precision of the latter for SOC estimation.

Dc‐link capacitor sizing is a critical aspect of inverter design. This study investigates capacitor sizing for three‐level neutral‐point‐clamped and cascaded H‐bridge inverters, based on an analysis of dc‐link capacitor current. Methods used to derive expressions for the root‐mean‐square (rms) value and harmonic spectrum of the capacitor current in two‐level inverters, are extended to the three‐level inverters. A new numerical approach is also proposed for calculating the capacitor rms current and voltage ripple. MATLAB code is given for the proposed approach, which can be easily adapted to different modulation strategies and applied to higher‐level inverters. Capacitor sizing parameters derived according to this approach are presented for a number of common modulation strategies and are used to compare the requirements of the examined three‐level topologies. Results are validated by simulations using MATLAB‐Simulink.

Fast capacity estimation is a key enabling technique for second-life of lithium-ion batteries due to the hard work involved in determining the capacity of a large number of used electric vehicle (EV) batteries. This paper tries to make three contributions to the existing literature through a robust and advanced algorithm: (1) a three layer back propagation artificial neural network (BP ANN) model is developed to estimate the battery capacity. The model employs internal resistance expressing the battery’s kinetics as the model input, which can realize fast capacity estimation; (2) an estimation error model is established to investigate the relationship between the robustness coefficient and regression coefficient. It is revealed that commonly used ANN capacity estimation algorithm is flawed in providing robustness of parameter measurement uncertainties; (3) the law of large numbers is used as the basis for a proposed robust estimation approach, which optimally balances the relationship between estimation accuracy and disturbance rejection. An optimal range of the threshold for robustness coefficient is also discussed and proposed. Experimental results demonstrate the efficacy and the robustness of the BP ANN model together with the proposed identification approach, which can provide an important basis for large scale applications of second-life of batteries.

A transformer-less Buck-Boost direct current–direct current (DC–DC) converter in use for the fast charge of electric vehicles, based on powerful high-voltage isolated gate bipolar transistor (IGBT) modules is analyzed, designed and experimentally verified. The main advantages of this topology are: simple structure on the converter’s power stage; a wide range of the output voltage, capable of supporting contemporary vehicles’ on-board battery packs; efficiency; and power density accepted to be high enough for such a class of hard-switched converters. A precise estimation of the loss, dissipated in the converter’s basic modes of operation Buck, Boost, and Buck-Boost is presented. The analysis shows an approach of loss minimization, based on switching frequency reduction during the Buck-Boost operation mode. Such a technique guarantees stable thermal characteristics during the entire operation, i.e., battery charge cycle. As the Buck-Boost mode takes place when Buck and Boost modes cannot support the output voltage, operating as a combination of them, it can be considered as critically dependent on the characteristics of the semiconductors. With this, the necessary duty cycle and voltage range, determined with respect to the input-output voltages and power losses, require an additional study to be conducted. Additionally, the tolerance of the applied switching frequencies for the most versatile silicon-based powerful IGBT modules is analyzed and experimentally verified. Finally, several important characteristics, such as transients during switch-on and switch-off, IGBTs’ voltage tails, critical duty cycles, etc., are depicted experimentally with oscillograms, obtained by an experimental model.