This paper proposes a model reference adjustable system observer for the sensorless control of doubly fed induction machines. The formulation is based on the direct calculation of the torque and flux rotor current components in the stator-flux-oriented coordinates by using the stator currents and voltages and the norm of the rotor current space vector. The tuning of the observer is discussed, and a theoretical sensitivity and stability analysis is performed in order to investigate the behavior of the observer under mismatched parameters. The paper is completed by the experimental validation of the observer performances.

Hybrid energy storage systems that combine lithium-ion batteries and supercapacitors are considered as an attractive solution to overcome the drawbacks of battery-only energy storage systems, such as high cost, low power density, and short cycle life, which hinder the popularity of electric vehicles. A properly sized hybrid energy storage system and an implementable real-time power management system are of great importance to achieve satisfactory driving mileage and batterycyclelife.However,dimensioningandpowermanagement problems are quite complicated and challenging in practice. To address these challenges, this work proposes a Bi-level multi-objective design and control framework with the nondominated sorting genetic algorithm-II and fuzzy logic control as key components, to obtain an optimal sized hybrid energy storage system and the corresponding optimal real-time power management system based on fuzzy logic control simultaneously. In particular, a vectorized fuzzy inference system is devised, which allows large-scale fuzzy logic controllers to run in parallel, thereby improving optimization efficiency. Pareto optimal results of different hybrid energy storage systems incorporating both optimal design and control parameters are obtained efficiently thanks to the vectorization. An example solution chosen from the Pareto front shows that the proposed method can achieve a competitive number of covered laps while improving the battery cycle life significantly.

This paper presents a model predictive control (MPC) algorithm for a three-level neutral point clamped converter connected to the grid via an LCL filter. The proposed long horizon MPC method, formulated as a multi-criterion quadratic program (QP), simultaneously controls the grid and converter current as well as the filter capacitor voltage, while meeting the relevant grid standards. To achieve the latter, a carrier-based pulse width modulation (CB-PWM) stage is employed. Finally, soft constraints are included to ensure operation of the system within its safe operating limits, particularly with regards to a potential overcurrent or overvoltage trip during transient operation. The presented simulation results based on a medium-voltage system as well as experimental studies based on a scaled-down prototype verify the effectiveness of the proposed method.

This paper introduces a framework to perform operational modal analysis (OMA) for structural health monitoring (SHM) by presenting the development and validation of a low-power, solar-powered wireless sensor network (WSN) tailored for bridge structures. The system integrates accelerometers and temperature sensors for dynamic structural assessment, all interconnected through the energy-efficient message queuing telemetry transport (MQTT) messaging protocol. Moreover, it delves into the details of sensor selection, calibration, and the design considerations necessary to address the unique challenges associated with bridge structures. Special attention is given to the solar-powered aspect, allowing for extended deployment periods without the need for frequent maintenance or battery replacements. To validate the proposed system, a comprehensive field deployment was conducted on an actual bridge structure. The collected data were transmitted through MQTT messages and analyzed by means of OMA. Comparative studies with traditional wired systems underscore the advantages of the solar-powered wireless solution in terms of sustainability, scalability, and ease of deployment. Results from the validation phase demonstrate the system’s capability to provide accurate and real-time data needed to assess the health state of the monitored asset. This paper concludes with insights into the practical implications of adopting such a solar-powered WSN, emphasizing its potential to revolutionize bridge health monitoring by offering a cost-effective and energy-efficient solution for long-term infrastructure resilience.

This paper deals with a performance analysis of sensorless drives based on doubly fed induction machines. A simplified model of the whole system equipped with a generic model reference adaptive system (MRAS) observer is introduced, by taking also into account a mismatch in the parameters. Three MRAS known in literature are analyzed in detail and meaningful analytic relations between the mismatched parameters and the error in the estimated rotor position during a steady-state operation are deduced. Then, a stability analysis is performed and the stability regions of each drive are found. Finally, the theoretical results are experimentally validated.