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1. Fast Detection of Open Circuit Device Faults and Fault Tolerant Operation of Stacked Multilevel Converters

   https://doi.org/10.1109/APEC.2019.8721923  

   Hekmati, Parham; Brown, Ian P.; Shen, Z. John (March 2019, 2019 IEEE Applied Power Electronics Conference and Exposition (APEC))

   This paper proposes a simple and fast technique for power device open circuit (OC) fault detection in stacked multicell converters (SMCs). A mitigation technique allowing for fault-tolerant operation using a simple front-end routing circuit is also proposed for SMCs. The fault detection concept only needs to sense the voltage and direction of current at the output terminal of the SMC to detect and localize an OC switch fault to a particular rail of the SMC. The proposed technique compares the measured and expected voltage levels considering the commanded switch states and the direction of the terminal current flow. Once an OC fault is detected and localized, the front-end routing circuit will be activated to reconfigure the SMC converter to a simple flying capacitor multilevel converter (FCMC) to maintain the output power flow with a reduced number of voltage levels. A window detector circuit is proposed to track the output voltage level and current direction with high bandwidth. Simulations were performed to validate the fault detection method and router performance. The functionality of windows detector is investigated with a hardware prototype 7 level 300 V SMC. 

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2. A Fault-Tolerant Hybrid Cascaded H-Bridge Topology

   https://doi.org/10.1109/ECCE.2019.8912836  

   Mhiesan, Haider; Mantooth, Alan; Siwakoti, Yam P. (September 2019, 2019 IEEE Energy Conversion Congress and Exposition (ECCE))

   null (Ed.)

   This paper presents the fault-tolerant operation for a cascaded H-bridge (CHB) inverter. The added features ensure reliable and robust operation in the event of a fault. The proposed strategy uses an additional cross-coupled CHB (X-CHB) unit in companion with the existing CHB to support the output voltage and ensure continuity of operation in case of an open/short circuit fault. The operation of the proposed X-CHB inverter is described in detail. Simulation and experimental verification of the proposed concept is demonstrated using a seven-level CHB. Both simulation and experimental results validate the fault-tolerant operation of the CHB for a battery energy storage system (BESS) in case of switch faults such as open/short-circuit switch faults or dc-source or battery failure. 

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3. Prognostic Health Monitoring of DC Microgrid with Fault Detection and Localization using Machine Learning Techniques

   https://doi.org/10.1109/ECCE53617.2023.10362739  

   Bohara, Bharat; Krishnamoorthy, Harish S. (October 2023, IEEE)

   DC microgrids incorporate several converters for distributed energy resources connected to different passive and active loads. The complex interactions between the converters and components and their potential failures can significantly affect the grids' resilience and health; hence, they must be continually assessed and monitored. This paper presents a machine learning-assisted prognostic health monitoring (PHM) and diagnosis approach, enabling progressive interactions between the converters at multiple nodes to dynamically examine the grid's (or micro-grid's) health in real time. By measuring the resulting impedance at the power converters' terminals at various grid nodes, a neural network-based classifier helps detect the grid's health condition and identify the potential fault-prone zones, along with the type and location of the fault type in the grid topology. For a faulty grid, a Naive Bayes and a support vector machine (SVM)-based classifiers are used to locate and identify the faulty type, respectively. A separate neural network-based regression model predicts the source power delivered and the loads at different terminals in a healthy grid network. The proposed concepts are supported by detailed analysis and simulation results in a simple four-terminal DC microgrid topology and a standard IEEE 5 Bus system. 

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4. Solar energy management as an Internet of Things (IoT) application

   https://doi.org/10.1109/IISA.2017.8316460  

   Spanias, Andreas S. (August 2017, 2017 IEEE 8th International Conference on Information, Intelligence, Systems & Applications (IISA))

   Photovoltaic (PV) array analytics and control have become necessary for remote solar farms and for intelligent fault detection and power optimization. The management of a PV array requires auxiliary electronics that are attached to each solar panel. A collaborative industry-university-government project was established to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management. First generation smart monitoring devices (SMDs) were built in Japan. At the same time, Arizona State University initiated research in algorithms and software to monitor and control individual solar panels. Second generation SMDs were developed later and included sensors for monitoring voltage, current, temperature, and irradiance at each individual panel. The latest SMDs include a radio and relays which allow modifying solar array connection topologies. With each panel equipped with such a sophisticated SMD, solar panels in a PV array behave essentially as nodes in an Internet of Things (IoT) type of topology. This solar energy IoT system is currently programmable and can: a) provide mobile analytics, b) enable solar farm control, c) detect and remedy faults, d) optimize power under different shading conditions, and e) reduce inverter transients. A series of federal and industry grants sponsored research on statistical signal analysis, communications, and optimization of this system. A Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently 

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5. A Comprehensive Analysis of Charge-Pump-Based Multi-Stage Multi-Output DC-DC Converters

   https://doi.org/10.1109/ISCAS51556.2021.9401129  

   Danesh, Ahmad Reza; Heydari, Payam (May 2021, IEEE International Symposium on Circuits and Systems)

   null (Ed.)

   This paper presents an analytical model for calculating the output voltage and the power efficiency of multi-stage multi-output (MSMO) DC-DC converters (DDC) that use charge pump cells for boosting the voltage. Various cases such as multi-output current consumption and its effects on the output voltage and the power efficiency are studied. Based on the model, a tapered design approach is proposed that can bolster the power efficiency and lower the output voltage drop of MSMO DDCs. Moreover, a charge-pump-based DDC is introduced and designed to verify the proposed model. Simulation results using a standard high-voltage 180-nm CMOS technology affirms the accuracy of the presented model. 

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