Moving average filter-based model predictive control for electric vehicles bidirectional chargers

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Conference Proceeding
2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017, 2017
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© 2017 IEEE. The paper proposes a moving average filter (MAF)-based model predictive control (MPC) for the electric vehicles (EVs) bidirectional chargers. Grid virtual flux is used to estimate the grid voltage through a low pass filter (LPF). An MAF, which acts as an ideal LPF, can eliminate the effect of unbalanced/distorted grid voltage and unknown characteristic harmonics. Both the two-cascaded LPF-based and the proposed MAF-based MPC strategies can achieve bi-directional power flow for EV batteries. Compared with the system results obtained from the two-cascaded LPF based MPC algorithm, the proposed control method can improve the system performance by reducing the current total harmonic distortion under a balance/unbalance grid voltage. The reactive power performance can be improved when the active power reference varies.
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