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Timely and accurate fault diagnosis for a lithium-ion battery pack is critical to ensure its safety. However, the early fault of a battery pack is difficult to detect because of its unobvious fault effect and nonlinear time-varying characteristics. In this paper, a fault diagnosis method based on relative entropy and state of charge (SOC) estimation is proposed to detect fault in lithium-ion batteries. First, the relative entropies of the voltage, temperature and SOC of battery cells are calculated by using a sliding window, and the cumulative sum (CUSUM) test is adopted to achieve fault diagnosis and isolation. Second, the SOC estimation of the short-circuit cell is obtained, and the short-circuit resistance is estimated for a quantitative analysis of the short-circuit fault. Furthermore, the effectiveness of our method is validated by multiple fault tests in a thermally coupled electrochemical battery model. The results show that the proposed method can accurately detect different types of faults and evaluate the short-circuit fault degree by resistance estimation. The voltage/temperature sensor fault is detected at 71 s/58 s after faults have occurred, and a short-circuit fault is diagnosed at 111 s after the fault. In addition, the standard error deviation of short-circuit resistance estimation is less than 0.12 Ω/0.33 Ω for a 5 Ω/10 Ω short-circuit resistor.

Reliable detection of the rotor winding faults in the doubly fed induction generator (DFIG) is crucial for the resilience of the variable speed energy systems. High-resistance connection (HRC) and inter-turn short circuit (ITSC) faults cause current distortions that are remarkably similar, and the rapid rotor side dynamics and the DFIG multimode operation ability also make fault diagnosis more difficult. This paper proposes a three-layer diagnostic framework named ZSC-CASI-CADI which leverages three-phase rotor currents in conjunction with rotor zero-sequence current (ZSC) for comprehensive rotor winding fault diagnosis. Fault detection is realized through ZSC magnitude and the Cosine Angle Spread Indicator (CASI) enables the strong discrimination between HRC and ITSC faults using the dispersion of rotor current phasors from the ZSC reference. Fault localization is achieved using the Current Angle Difference Indicator (CADI), which determines the faulty rotor phase through the angular deviations in rotor currents from the ZSC. The methodology is verified with extensive simulation results to demonstrate the accurate, real-time fault detection, discrimination, and localization of DFIG rotor winding faults under different load and rotor speed conditions including sub-synchronous and super-synchronous modes. The results show that the proposed framework provides a light and effective solution for rotor winding fault monitoring of the DFIG systems.

Measurement errors in voltage and current sensors may result in overcharge and overdischarge of the battery, thereby reducing battery reliability. However, this relationship has not been well characterized in existing studies. To address this issue, a reliability evaluation method of battery energy storage system (BESS) considering sensor deviations is proposed. First, the error distribution of the battery state estimation is derived within the extended Kalman filter framework. In addition, the battery aging state, thermal stability, and internal resistance are investigated to characterize the evolution of battery reliability based on the degradation mechanism. On this basis, the battery reliability is modeled by integrating these three aspects. Finally, the reliability model of BESS is developed utilizing the universal generating function technique. Case studies demonstrate a correlation between sensor error and battery reliability. A 1% error of the sensor can accelerate the battery reliability decrease by 6 times. In some cases, an internal short circuit may lead to a complete loss of battery reliability. By reducing the sensor error from 1% to 0.5%, the reliability of BESS can be improved by up to 24.6% after 1000 cycles. These conclusions are significant for predicting the life cycle performance and guiding the design of BESS monitoring systems.

The method for estimating the immunity of an AC/DC converter built in a commercial LED lamp to a 1.2/50 µs (8/20 µs) surge has been presented in this paper. A lamp with a direct drive LED inverter was selected to present the methodology for determining the coefficient of immunity of the test object to a standardized type of surge. The choice of this configuration was important for the testing process and presentation of the methodology to estimate the immunity coefficient of the tested system. In this work, the methodology for determining the deterministic immunity factor of the model inverter to a normalized type of disturbance was presented. Considerations were carried out for a 1.2/50 µs (8/20 µs) surge in accordance with the recommendations of the EN 61000-4-5:2014 standard. This conventional surge is used in laboratory practice to test the immunity of electronic and electrical systems and devices to disturbances that can be generated in the power grid during switching processes, short circuits, and direct and indirect lightning. In the first stage of testing on test benches, the intensity of damage to the integral components of a model inverter was examined with increasing levels of disturbance. Statistical measures characterizing their impact resistance were determined for each of the elements tested. Knowing their values, the value of this coefficient was finally determined for the lamp selected for testing, and the mechanism of its damage was analyzed.

This study deals with the CdS/CdTe solar cells under low illumination intensity, with cell #1 for the shunt resistance exceeding 100,000 Ω·cm2 and cell #2 for the shunt resistance above 1000 Ω·cm2. The diode parameter variations with the decline of the irradiance intensity are illustrated by dividing 0–100 mW/cm−2 into a number of small intensity ranges for J–V measurements and assuming the diode parameters to be constant within each range, the diode parameters of each range including the series resistance, the shunt resistance, the reverse saturation current density and the ideality factor are then extracted by employing an analytical approach. The mechanism of the cell performance deviations are also investigated by basic theories, reports and experiments. For cell #1 with higher Rsh corresponding to less traps, Rsh shows a upward tendency as the irradiance declines, n and J0 exhibit a rise with the irradiance and keep nearly unchanged at the low irradiance values mainly due to recombination and carrier contributions, Rs shows a slight increase when the irradiance intensity goes down because of the resistance of CdTe absorption layer. For cell #2 with lower Rsh corresponding to more traps, with the decrease of the illumination intensity, Rsh increases sharply only for captured carrier reduction, Rs goes steadily up similarly, n and J0 exhibit a decline with the irradiance due to recombination shift. It should be pointed out that Rs varies much smoother than the traditional approximation of a reciprocal of differential at short circuit, and the distribution of Rsh is diverse, and an average Rsh of for each intensity range can reflect the variation trend.

The purpose of this paper is the inter-turn short circuit fault Modeling and detection for the sensorless input-output linearization control of the permanent magnet synchronous motor (PMSM) based on the Extended Kalman Filter observer (EKF). The fault detection procedures are based through the estimation of the stator resistance variation by the Extended Kalman Filter observer and the Fast Fourier Transformer (FFT) for the stationary state, and the Discrete Wavelet Transform (DWT) analysis of the electrical characteristics of the PMSM, for the non-stationary state. However, the FFT spectral analysis and the DWT is a useful solution to ensure that the variation of the stator resistance estimation is caused by the inter-turn short circuit fault. The effectiveness of the sensorless control and the fault detection techniques are presented in a simulation in MATLAB/Simulink environment.