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| An Improved Model Predictive Control of Four-Level Active Neutral Point Clamped Inverter with Balanced Capacitor Voltage |
| Xiang Chaoqun1, Du Jingrun1, Zhang Xinan2, Xi Zhen1, Ding Hao1 |
1. School of Traffic and Transportation Engineering Central South University Changsha 410075 China;
2. Department of Electrical and Electronic Engineering School of Engineering The University of Western Australia Crawley WA6009 Australia |
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Abstract Multi-level inverters can generate high-quality stepped AC voltage with advantages such as low harmonic content, switch state redundancy, and small common mode voltage, which is suitable for various power applications. Compared to cascaded H-bridge multi-level inverters, the active neutral point clamped (ANPC) inverter uses few power semiconductors without multiple independent DC sources and is cost-effective for low to medium-voltage applications. Furthermore, compared to diode-based passive, neutral point clamped (NPC) inverters, the ANPC inverter can better distribute power losses among power semiconductors, resulting in higher reliability.
To effectively control a four-level ANPC (4L-ANPC) inverter and avoid using complex modulation strategies, this paper proposes an improved finite set model predictive current control (FS-MPCC) algorithm that adopts a two-step voltage vector selection mechanism to achieve excellent control performance and ensure capacitor voltage balance. Firstly, the improved FS-MPCC evaluates the six large voltage vectors (LVVs) at the outer layer of the four-level voltage vector hexagon. The LVV that minimizes the cost function containing only current errors is selected as the optimal LVV. The LVV does not affect the neutral point (NP) capacitor voltage and cannot suppress neutral point voltage (NPV) fluctuations. In addition, the spatial position of the optimal LVV may not be closest to the reference voltage vector. Directly applying the optimal LVV can cause increased harmonic currents and reduced control system stability. Therefore, in the second stage, the optimal LVV obtained in the first stage is used as the central voltage vector, and all voltage vectors within a 60° range are optimized. The second-stage voltage vectors (13 voltage vectors) include medium voltage vectors (MVVs) and small voltage vectors (SVVs) that can affect the neutral point potential. Each candidate voltage vector is substituted into a cost function with current and capacitor voltage errors for rolling optimization. The final target voltage vector is obtained to suppress current errors and NPV fluctuations. In total, 19 optimizations are performed between the two stages, reducing the iterative calculation amount by 45 compared to traditional FS-MPCC strategies.
Simulation is conducted in Matlab/Simulink, and experimental validation is carried out on a dSPACE-based hardware platform. The results demonstrate that the proposed method maintains capacitor voltage balance while keeping NPV values within allowable limits under different modulation indexes and fundamental frequencies. Compared to traditional methods, the proposed method can quickly respond without decreasing steady-state and dynamic control performance under sudden changes in reference current, fundamental frequency, or system parameters. In addition, dSPACE configuration file tests show that the proposed method reduces system execution time and computational burden while maintaining high computational efficiency.
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Received: 27 July 2023
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2024, Vol. 39 
