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Kalman Filter-Based Super-Twisting Sliding Mode Control of Shunt Active Power Filter for Electric Vehicle Charging Station Applications. / Çelik, Doğan; Ahmed, Hafiz; Meral, Mehmet Emin.
Yn: IEEE Transactions on Power Delivery, 13.09.2022.

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Çelik D, Ahmed H, Meral ME. Kalman Filter-Based Super-Twisting Sliding Mode Control of Shunt Active Power Filter for Electric Vehicle Charging Station Applications. IEEE Transactions on Power Delivery. 2022 Medi 13. doi: https://doi.org/10.1109/TPWRD.2022.3206267

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TY - JOUR

T1 - Kalman Filter-Based Super-Twisting Sliding Mode Control of Shunt Active Power Filter for Electric Vehicle Charging Station Applications

AU - Çelik, Doğan

AU - Ahmed, Hafiz

AU - Meral, Mehmet Emin

PY - 2022/9/13

Y1 - 2022/9/13

N2 - Electric vehicle (EV) charging stations draw nonlinear currents, which makes the distribution network unbalanced, distorted, and results in power quality (PQ) issues. These PQ issues are mitigated in this work through high-performance control of the shunt active power filter (SAPF). In the proposed method, a linear Kalman filter (LKF) has been applied to grid voltage and load current signals for harmonic and disturbance robust estimation purpose. Unlike the conventionally used orthogonal vector model, in this work, phase angle vector model together with a simple to tune phase-locked loop (PLL) has been considered for the LKF implementation. DC-link voltage regulation and charging of the DC-link capacitor has been obtained by proposing a Luenberger observer-based super twisting sliding mode control (ST-SMC), which has fast dynamic response and lower voltage ripples compared to similar other existing control methods. This results in significant reduction in size, cost and loss together with lifetime enhancement of the DC-link capacitor. Rigorous sensitivity analysis is conducted to analyze the robustness of the developed method. The proposed control technique achieves fast response time and satisfy the harmonic requirements as specified in the IEEE Std. 519 under various grid and load disturbances. Comparative quasi-real time validation results are presented by using digital signal processor (DSP) based processor-in-the-loop (PIL) with another recently proposed control strategy to verify the performance enhancement by the developed method.

AB - Electric vehicle (EV) charging stations draw nonlinear currents, which makes the distribution network unbalanced, distorted, and results in power quality (PQ) issues. These PQ issues are mitigated in this work through high-performance control of the shunt active power filter (SAPF). In the proposed method, a linear Kalman filter (LKF) has been applied to grid voltage and load current signals for harmonic and disturbance robust estimation purpose. Unlike the conventionally used orthogonal vector model, in this work, phase angle vector model together with a simple to tune phase-locked loop (PLL) has been considered for the LKF implementation. DC-link voltage regulation and charging of the DC-link capacitor has been obtained by proposing a Luenberger observer-based super twisting sliding mode control (ST-SMC), which has fast dynamic response and lower voltage ripples compared to similar other existing control methods. This results in significant reduction in size, cost and loss together with lifetime enhancement of the DC-link capacitor. Rigorous sensitivity analysis is conducted to analyze the robustness of the developed method. The proposed control technique achieves fast response time and satisfy the harmonic requirements as specified in the IEEE Std. 519 under various grid and load disturbances. Comparative quasi-real time validation results are presented by using digital signal processor (DSP) based processor-in-the-loop (PIL) with another recently proposed control strategy to verify the performance enhancement by the developed method.

U2 - https://doi.org/10.1109/TPWRD.2022.3206267

DO - https://doi.org/10.1109/TPWRD.2022.3206267

M3 - Article

JO - IEEE Transactions on Power Delivery

JF - IEEE Transactions on Power Delivery

SN - 1937-4208

ER -