A novel magneto-optical current sensor (MOCS) with two sensing arms is proposed to improve the temperature stability. One of the arms, with a highly stable permanent magnet attached and orthogonal to the other one, is designed to provide a reference that follows the temperature characteristics of the sensing material. By a normalization operation between two arms, the temperature drift is compensated adaptively and a sensing output proportional to the measured current can be reached. A dual-input and dual-output structure is specially designed for the reference sensing arm to demodulate the DC Faraday rotation angle. This scheme compensates simultaneously two main temperature influence factors, the Verdet constant and linear birefringence. Validation tests were carried out and are discussed.

The neutral point clamped (NPC) three-level grid-tied converter is the key equipment connecting renewable energy and power grids. The current sensor fault caused by harsh environment may lead to the split of renewable energy. The existing sensor fault-tolerant methods will reduce the modulation ratio index of the converter system. To ensure continuous operation of the converter system and improve the modulation index, a model predictive control method based on reconstructed current is proposed in this paper. According to the relationship between fault phase current and a voltage vector, the original voltage vector is combined and classified. To maintain the stable operation of the converter and improve the utilization rate of DC voltage, two kinds of fault phase current are reconstructed with DC current, normal phase current and predicted current, respectively. Based on reconstructed three-phase current, a current predictive control model is designed, and a model predictive control method is proposed. The proposed method selects the optimal voltage vector with the cost function and reduces time delay with the current reconstruction sector. The simulation and experimental results showthat the proposed strategy can keep the NPC converter running stably with one AC sensor, and the modulation index is increased from 57.7% to 100%.

The paper presents the analysis of the magnetic sensor’s applicability to the energy harvesting operations. The general scheme and technical advancement of the energy extraction from the electric vehicle (such as a tram or a train) is presented. The proposed methodology of applying the magnetic sensor to the energy harvesting is provided. The experimental scheme for the sensor characteristics and measurement results is discussed. Conclusions and future prospects regarding the practical implementation of the energy harvesting system are provided.

Modern induction motor (IM) drives with a higher degree of safety should be equipped with fault-tolerant control (FTC) solutions. Current sensor (CS) failures constitute a serious problem in systems using vector control strategies for IMs because these methods require state variable reconstruction, which is usually based on the IM mathematical model and stator current measurement. This article presents an analysis of the operation of the direct torque control (DTC) for IM drive with stator current reconstruction after CSs damage. These reconstructed currents are used for the stator flux and electromagnetic torque estimation in the DTC with space-vector-modulation (SVM) drive. In this research complete damage to both stator CSs is assumed, and the stator current vector components in the postfault mode are reconstructed based on the DC link voltage of the voltage source inverter (VSI) and angular rotor speed measurements using the so-called virtual current sensor (VCS), based on the IM mathematical model. Numerous simulation and experimental tests results illustrate the behavior of the drive system in different operating conditions. The correctness of the stator current reconstruction is also analyzed taking into account motor parameter uncertainties, especially stator and rotor resistances, which usually are the main parameters that determine the proper operation of the stator flux and torque estimation in the DTC control structure.