Model predictive current control (MPCC) schemes have been considered as a promising control technique for voltage source inverters (VSIs). However, the computational burden reduction, harmonic currents elimination and common-mode voltage (CMV) mitigation are special issues when MPCC schemes are applied to five-phase VSIs. Moreover, it is time-consuming to tune weighting factors for the multiple control objectives. To address these problems, this paper proposes two computational efficient MPCC schemes based on virtual voltage vectors (V3s), named as MPCC-V3-RCMV1 and MPCC-V3-RCMV2. The former one achieves lower harmonics while the latter one achieves lower switching frequency. The V3s are defined with basic voltage vectors that generate small CMV, hence inherent CMV reduction can be achieved. The proposed MPCC schemes simplify the controller by redefining cost function and control set, which reduces the computational effort significantly. Besides, the proposed MPCCs can improve the quality of current waveforms. Simulations and experiments are carried out to verify effectiveness of the proposed control schemes.

The application of model predictive current control (MPCC) on the open-winding permanent magnet synchronous machine (PMSM) drive system confronts the challenge of complexity due to the enumeration process and the multiobjective cost function evaluation. In this article, a new low-complexity MPCC is proposed to eliminate the online enumeration process and the cost function evaluation. In the proposed scheme, the reference voltage vector components are calculated based on the deadbeat principles. Then, the optimal voltage vector that matches the reference vector is selected from the control set based on predefined optimization criteria. These criteria are defined offline by solving the conventional current control cost function in the 3-D ( $\alpha $ – $\beta $ – $z$ ), utilizing new 3-D analysis. The proposed control scheme is compared with the conventional finite control set (FCS)-MPCC and the existing 3-D-MPCC schemes using MATLAB simulation and hardware-in-the-loop (HIL) results. Compared with conventional FCS-MPCC and 3-D-MPCC schemes, the proposed control scheme presents the same salient features, such as fast dynamic response, low output current/torque ripple, and zero-sequence current suppression. The computational complexity of the proposed control scheme is much lower than the conventional FCS-MPCC.

Finite control set model predictive control (FCS-MPC) has been widely studied and applied in power converters and machine drives. It takes advantage of the nonlinear finite switching states of the power converters, and a discrete model is used to predict the behavior of the system. The main advantages of FCS-MPC lie in easy inclusion of nonlinear constraints, simple structure and intuitive concept. However, FCS-MPC applied in multiphase machine drives will face with the challenge of heavy computation cost. In this article, a computationally efficient FCS-MPC method is proposed for multiphase drives. The concept of virtual voltage vector is introduced to eliminate low-order harmonic currents in open-loop mode, resulting in simplified prediction model and cost function. To further simplify the enumerative optimization process, the redundant vectors are eliminated, and only five evaluations are required. By this way, the computation complexity is considerably reduced and is approximately irrespective of phase number. Thus, it can be easily generalized to multiphase drives. Moreover, the merit of simple structure is kept, which is the most important characteristic of FCS-MPC. The proposed method is compared with the existing FCS-MPC methods to illustrate its effectiveness. The experimental results have verified that the proposed method can reduce computation complexity, achieve superior steady-state and dynamic performance.

Modulating the traction converters produces current harmonics at the switching frequencies and their multiples. These harmonics should be minimized to meet the network specifications. The LC ‐trapped filters, tuned to these frequencies, can easily meet this requirement, but the existing applicable trap filters have not been studied with the traditional traction system topologies. Thus, this paper presents a trapped LCL filter with an LC resonator on the converter side, called a fully integrated T‐LCL filter, for the traction power supply system. The model and analysis reported in this research demonstrate that the presented filter has several advantages, which can be summarized by: reducing the size by winding many coils through magnetic integration, attenuating the switching frequency and its multiple harmonics that reduce the current total harmonic distortion, assuring durability against the filter parameters differences, and preserving system stability under transient conditions. The proposed filter can become a promising trap filter based on these advantages. Simulation models of an ac/dc single‐phase traction rectifier with the proposed filter were created and tested in MATLAB/Simulink, verifying its superiority. Finally, the filter is validated by performing hardware‐in‐the‐loop experiments.

Finite control set (FCS) model predictive control (MPC) has been widely emerged for the double-subspace control problem of five-phase permanent magnet synchronous motor (PMSM) drives thanks to the principles of the virtual voltage vectors (V ³ s), which improve the steady-state performance with low computational burden. However, the V ³ s are designed offline to include one-subspace components, which is not considered as an optimized solution. Therefore, this article presents an improved double-vector-based FCS-MPC scheme for five-phase PMSM drives, considering the control objectives of the two subspaces. The proposed scheme remedies the limitations of the conventional V ³ s using online selection of the two vectors combination and duty ratio calculation. To keep low computational burden, ten possible double-vector combinations are examined during every sampling interval for each fundamental α–β sector, which is defined using the deadbeat calculations. Compared with the standard FCS-MPC and the traditional FCS-MPC with V ³ s schemes, the proposed double-vector-based FCS-MPC scheme can achieve improved tracking accuracy and high dc-link voltage utilization. The potentials of the proposed scheme over these existing FCS-MPC schemes are verified by simulation analysis and experimental test on a five-phase PMSM drive prototype.

The study proposes a supply chain contractual coordination model based on the product lifecycle information sharing effort and consumers' price sensitivity to a product with the Blockchain system. This paper examined the following five scenarios: (1) centralized supply chain with Blockchain system-based product lifecycle information sharing investment; (2) Stackelberg leader retailer processed and invested Blockchain system scenario; (3) retailer processed the Blockchain system cost-sharing scenario; (4) retailer processed Blockchain system investment through bargaining the revenue-sharing model; (5) Blockchain system investment under the cost and revenue-sharing contract. The study used the game theory reverse induction method to compare the Nash equilibrium solutions under different decision-making scenarios and discussed the chain member’s constraint condition of Blockchain system investment. We simulated and analysed the products’ lifecycle information sharing effort cost factor, the influence of price sensitivity coefficient, and expected profits of the supplier and retailer. The study results show that the product lifecycle information sharing effort under the Blockchain system increases the profit of the whole chain and decreases with the increase of customer’s price sensitivity coefficient.