Hybrid Predictive Control With Linear Power Distribution of Single-Stage Multiport Inverters for Hybrid Electric Vehicles

Model predictive control (MPC) is a promising candidate for single-stage multiport inverters (SSMPI) control due to its capability to handle multiple control objectives of power distribution and stator current control under time-varying dc link. However, conventional MPC, which obtains the optimal control input by evaluating all the discrete switching states, experiences excessive port power ripples and a complex weighting factor tuning process. To this end, this article proposes a hybrid predictive control (HPC) with linear power distribution for the SSMPI to reduce power ripples of dc ports and eliminate weighting factors. In the proposed HPC, the stator current regulation of the motor is realized through tracking error minimization by considering the SSMPI as a single-source inverter, where the iteration time of the MPC can be sharply reduced. Besides, the power distribution of the dc sources is achieved by precisely splitting the predicted optimal voltage vector in the subinverters of SSMPI, and the dc port power distribution ripples can be significantly reduced through linear comparison of the predicted boundary powers. Moreover, the complex weighting factor tuning process is also eliminated due to the decoupled control structure in HPC. Extensive experimental results are presented to validate the advantages of the proposed HPC.