Distributed Predictive Control of the Two-Stage Power Converter From the Battery to the Motor Considering the DC-Voltage Prediction

Abstract

In recent years, there has been a notable rise in deploying multiple power converters within integrated systems. Among the most crucial of these systems are electric vehicles, which utilize dc–dc converters and inverters. Interleaved boost converters are desirable for these applications because of their favorable characteristics, including low current ripple, high efficiency, and flexibility. The configuration chosen in this article is a motor drive inverter for permanent magnet synchronous motors powered by a three-phase interleaved boost converter. Implementing control methods independently for multiple interconnected converters can lead to decreased accuracy, increased response time, lack of proper control, and system uncertainty. On the other hand, integrated control of complex systems is not feasible because of computational time limits. This article proposes a distributed finite-control-set model predictive control method to solve the problems caused by the lack of dependence on the controllers. Furthermore, the proposed technique alleviates the computational burden associated with the unified control methods, aiming to enhance feasibility and minimize complexity. Considering the switching states in the prediction equation, the proposed method eliminates both the dc-link voltage and current sensors from the system. Compared to independent control methods, the results showed that the proposed method improved the transient and steady-state performance and reduced the ripple of essential variables such as torque, current, and voltage. In addition, the peak battery current is decreased.