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This study presents a coupled-inductor single-stage boost inverter for grid-connected photovoltaic (PV) system, which can realise boosting when the PV array voltage is lower than the grid voltage, converting dc voltage into ac voltage, feeding current to the grid with high-power factor and maximum power point tracking (MPPT) together. By introducing an impedance network including coupled inductor in front of the three-phase inverter bridge, and adjusting the previously forbidden shoot-through zero state, the converter can step up input voltage to a higher voltage level. System reliability is also improved by using shoot-through zero state as a normal operation mode. Cost can be reduced by single-stage operation and also by using economical MPPT method only via grid current. Theoretical analysis, simulation and experimental results are presented to verify its good performance.

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The coupled-inductor single-stage boost inverter (CI-SSBI) has been proposed and applied to photovoltaic (PV) power system. As previously presented, the CI-SSBI has the feature of stepping up input voltage to a higher voltage level by properly designing the turns ratio of coupled inductor and regulating the shoot-through duty cycle. The CI-SSBI based grid-connected PV system integrates some characteristics together in one stage, including boost inversion, feeding current into the grid with high power factor, and maximum power point tracking. Moreover, system reliability can be improved by using the shoot-through zero states as a normal operation mode. This study focuses on the power loss analysis of main elements, and control analysis of both bus voltage loop and inner current loop of the proposed PV system. Simulation and experimental results are presented to verify the analysis and show the real system performance.

This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.

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