Neutral-point (NP) voltage imbalance is an inherent problem of three-level neutral-point clamped (NPC) converter. To solve this problem, an improved virtual space vector pulse width modulation (VSVPWM) is proposed in this paper. A new repartitioning of the space vector sectors is proposed for three-level NPC converter by considering the amplitude variations of small vectors under NP voltage imbalance. The factor k of the NP voltage imbalance is introduced. The small vector favorable to the NP voltage balance is selected based on the factor k and phase current direction to achieve precise control and balancing of NP voltage. The proposed method can effectively maintain NP voltage balance and eliminate the low frequency oscillation of the NP voltage over the whole modulation index range. The improved VSVPWM also has advantages of good dynamic performance. The method has been tested and verified by simulations and experiments.

This article proposes a novel online integral reinforcement learning (IRL) based data-driven control algorithm for interleaved dc/dc boost converter. The proposed algorithm is independent of system model due to the usage of a three-layer neural network (NN). Furthermore, its controller gains are autonomously adjusted online through the value function based NN weights updating mechanism, which simplifies the controller gain tuning process. Compared to the conventional model-dependent control approaches, it provides superior control performance. Additionally, the proposed method contributes to significantly reduce the computational burden of classical IRL algorithm by removing the disturbance updating process. Experimental results are presented to verify the efficacy of the proposed algorithm.

This paper proposes a novel deep deterministic policy gradient (DDPG) assisted integral reinforcement learning (IRL) based control algorithm for the three-phase DC/AC inverter feeding a resistive-inductive (RL) load. The proposed controller autonomously updates its control gains online without the need to know the system model. Excellent steady-state and dynamic system responses are achieved by the proposed control algorithm with reasonably low computational complexity. Moreover, the important initial stabilizing control problem is solved through offline training that uses the DDPG technique. Details of the DDPG based training procedures are presented. Experimental results are presented to verify the efficacy of the proposed IRL based control method.

The safety and reliability of inverters play a significant role in stable power electronic system operations. Considering a railway vehicle air-conditioning inverter as a case study, this paper presents a generic open-circuit fault diagnosis method that can be applied to various inverter and control schemes. First, a detailed model of three-phase output currents under both normal and fault status is derived, and then the concept of space trajectory is introduced based on the three-phase output currents. The open-circuit faults of the inverter lead to output phase current distortion. Therefore, different types of faults have different space trajectories, and the corresponding shape of the space trajectory is considered to be a fault feature. Then, the fault is located by the direction vector and center-of-mass coordinate. The effectiveness and reliability of the diagnosis method are verified and analyzed using a hardware-in-the-loop test platform.

This paper proposes a novel Extended Sliding-Mode Predictive Control (ESM-PC) strategy for three-phase three-level voltage source inverters (3P-3L VSIs). Initially, the control domain is established using sliding-mode theory, dynamically reducing the search space. Subsequently, a unique parallel optimization strategy is presented in the two-phase stationary coordinate system, with an analysis of the monotonicity of the cost functions and the constraints within the search space. Compared to traditional model predictive control (MPC), this approach results in a calculation time reduction of at least 51.3%. To mitigate output ripple, a novel design method for virtual voltage vectors (VVVs) is proposed based on α and β components, demonstrating notable scalability. At the same time, to maintain neutral point (NP) voltage balance, two output modes are devised for the VVVs using redundant small voltage vectors, eliminating weighting factors. Additionally, the excessive voltage jumps are mitigated and the method operates at a constant switching frequency. Experimental results robustly validate the algorithm's superior performance.

Open-circuit (OC) faults of inverter switch, clamping diode and load are easily misdiagnosed by most of the existing methods due to the extremely similar fault features. In this regard, a diagnostic method based on line voltage over-modulation and amplitude features is proposed in this paper to accurately locate coupling faults of three-level neutral-point-clamped (3L-NPC) inverter and load. Only two line voltages are used as diagnosis variables, and additional sensor is not required. The proposed diagnosis method consists of two parts: fault detection and fault classification. The fault detective algorithm only requires a small amount of computation and is suitable for uninterrupted execution. The classification algorithm starts immediately when the fault is detected, and the over-modulated voltage features are used to locate the fault. The proposed method can usually complete the diagnosis in 1/4 of fundamental period. The proposed method is also robust to different modulations, carrier frequencies and load variations. Experiments demonstrate that the proposed method can distinguish the OC faults of semiconductors (including switches and clamping diodes) and load effectively.