In this paper, an open-circuit (OC) fault diagnosis algorithm for power switch in the motor drive inverter system is proposed, which uses signal normalization preprocessing to deal with the current fluctuation caused by the load change. For the proposed fault diagnosis algorithm, firstly, the three-phase currents are sampled by the sliding window, which can improve the timeliness of diagnosis. Then, the sampled data is preprocessed by the variable modulus length normalization to eliminate the influence of the load change. Especially in the transient state, the information of the data feature is retained and the impact of load change is removed. Moreover, the frequency domain feature of the data is extracted by the DFT. Finally, the dimension of the features is reduced by the PCA method and its contribution graph is used to locate the fault IGBT. Moreover, the method can overcome the misjudgment of IGBT failure caused by transient currents when the load changes in the drive system. The simulation and experiment results show its effectiveness and timeliness in the OC fault diagnosis of the inverter.

This article presents a open-circuit fault diagnosis method for a sensorless vector control system based on the voltage–current hybrid model flux observer. The error voltage, which is obtained after a PI module, is used as a diagnostic factor. This PI module is designed to correct the deviation between the voltage model flux observer and the current model flux observer. The error voltage is not affected by load and speed variation. First, the activation function is used to separate fault information and normal information, and the feature function is defined to describe the signal feature in healthy and faulty conditions. Second, a second-order moving mean filtering method is proposed to reduce the storage of the error voltage data and increase the timeliness of diagnosis. Finally, the fault is diagnosed and located through logical calculations. Compared with conventional methods, this method features the timeliness of fault diagnosis in a closed-loop system and robustness with respect to speed and load changes. It reduces the storage and operation burden such that it can be easily implanted into the control algorithm as a subroutine. Simulations and experiments show the accuracy and superiority of the proposed fault diagnosis method for voltage source inverter fed sensorless vector controlled drives.

In order to improve the speed regulation performance of induction motors, a multi-modulation times space vector pulse width modulation (MMT-SVPWM) is proposed for the three-level neutral point clamped (NPC) converter. This method can eliminate the dead time effect (DTE), which is caused by the addition of the dead time (DT) in the SVPWM. This paper firstly analyzes the deviation of the output voltage which is caused by the DTE in the SVPWM, and then proposed the MMT-SVPWM. The generation of driving signals in this method is different from the ideal SVPWM. According to the directions of three-phase currents, the driving signals of a pair of complementary power switches are obtained by comparing a pair of multiple modulation times with the triangular carrier. Thus, this method directly eliminate the DTE, which is different from the SVPWM with DT (DT-SVPWM). The output voltage vector is the same as that of the ideal SVPWM, and there is no zero-current clamping effect. Finally, the simulation and experimental results show that the proposed method effectively eliminates the DTE and improves the output currents of the three-level NPC converter.

Unbalanced loads are general in uninterruptible power supply (UPS), standalone power generation applications and the failure mode of three-phase inverters. Three-phase four-leg inverters are a well-known solution to handle neutral currents caused by unbalanced loads. In four-leg inverters, three-dimensional space vector modulation (3DSVM) is widely used. However, the 3DSVM of four-leg current source inverter (CSI) has not been systematically studied so far. To fill this gap, this paper proposes a 3DSVM for CSI. The definition of the current vector, the identification of the position of reference vector and the sequence of switches are introduced. Under unbalance loads, the symmetrical load voltage can be realized, which complies with IEEE Std. 1159-2019. The output current can comply with IEEE Std. 519-2014. The proposed 3DSVM has the potential to extend the advanced modulation strategies that have been implemented/ proposed on three-leg CSI.

Green hydrogen is one of the most promising choices among hydrogen production methods due to its zero-emission, environmentally friendly, and sustainable characteristics. Choosing an appropriate model for green hydrogen production via photovoltaic electrolysis is critical to improving its efficiency and reliability. However, existing studies lack a comprehensive review and comparison of photovoltaic electrolysis for green hydrogen production. This gap makes it challenging for researchers to select suitable models for photovoltaic electrolysis in their investigations. To address this challenge, this article provides a comprehensive review and comparison of existing modeling research on photovoltaic hydrogen production systems. It classifies and analyzes photovoltaic panels, converters, and electrolyzers in photovoltaic electrolysis hydrogen production, summarizing general modeling approaches and criteria for selecting appropriate electrolyzer models for different applications. The article also highlights shortcomings in existing research and proposes directions for future investigations.

This paper proposes a power switch open-circuit (OC) fault diagnosis method for a motor drive inverter system. This method utilizes adjacent trend lines to extract fault features from the current vector trajectory, enabling rapid fault diagnosis and localization. Firstly, the current vector trajectory is obtained by applying the Clark transformation to the three-phase currents, and trend line slopes are calculated using equidistant current signal nodes. Subsequently, the method determines fault by calculating changes in adjacent trend line slopes and quickly locates the faulty power switch by considering the average slope of adjacent trend lines and the beta-axis current direction in the alpha–beta coordinate system. Accurate OC fault localization can be achieved with just a few trend line data points calculated in each current cycle, reducing the extra hardware and computational burden. This method is not only suitable for load variations but also applicable to the diagnosis of both single-switch and multiple-switch faults. Finally, simulation and experimental results validate the effectiveness and robustness of the method.