This paper proposes a method based on chaotic spread spectrum sequence for synchronous online diagnosis of intermittent faults for complex and cable networks, such as the aircraft power system. The novelties of the proposed method include: 1) Since chaotic spread spectrum signals are sensitive to initial values, the number of chaotic sequences are not limited and the proposed method is not limited by the number of cables under monitoring; 2) With the self-correlation characteristic and cross-correlation characteristic of chaotic sequence, the proposed method can be extended to online diagnosis of multiple cable intermittent faults; and 3) The signal source impedance amplification method is proposed for intermittent arc faults of multiple cables, which improves the reflection coefficient and increases the accuracy of on-line detection and location of intermittent arc faults. A series of simulations and experiments on multiple cables with different intermittent fault modes are conducted to verify the effectiveness of the proposed approaches.

The physical properties in amorphous regions are important for the insulation aging assessment of polytetrafluoroethylene (PTFE) cable insulation materials. In order to study the effect of boron nitride (BN) nanoparticles on the physical properties of PTFE materials under moisture, temperature, and electric fields conditions at the molecular level, the amorphous region models of PTFE, BN/PTFE, water/PTFE, and water/BN/PTFE were respectively constructed by molecular dynamics (MD) simulation. The mechanical properties including Young’s modulus, Poisson’s ratio, bulk modulus, and shear modulus, along with glass transition temperature, thermal conductivity, relative dielectric constant, and breakdown strength of the four models have been simulated and calculated. The results show that the mechanical properties and the glass transition temperature of PTFE are reduced by the injection of water molecules, whereas the same, along with the thermal conductivity, are improved by incorporating BN nanoparticles. Moreover, thermal conductivity is further improved by the surface grafting of BN nanoparticles. With the increase of temperature, the mechanical properties and the breakdown strength of PTFE decrease gradually, whereas the thermal conductivity increases linearly. The injection of water molecules increases the water content in the PTFE materials, which causes a gradual increase in its relative dielectric constant. This work has shown that this effect is significantly reduced by incorporation of BN nanoparticles. The variation of physical properties for PTFE and its composites under the action of moisture, temperature, and electric fields is of great significance to the study of wet, thermal, and electrical aging tests as well as the life prediction of PTFE cable insulation materials.

This paper develops and applies an inductive directional coupling technology based on spread spectrum time domain reflectometry (SSTDR) for non-intrusive power cable fault diagnosis. Different from existing capacitive coupling approaches with large signal attenuation, an inductive coupling approach with a capacitive trapper is proposed to restrict the detection signal from transmitting to power source and to eliminate the effect of the power source impedance mismatch. Moreover, a novel structure with two parallel couplers is developed to enhance the effect of capacitive trapper with small capacitance. The development, design, analysis, and implementation of the proposed approach are discussed in details. A series of simulations and experiments on cables with different fault modes are conducted, along with comparison with existing capacitive coupling, to verify and demonstrate the effectiveness of the proposed method.

Six-phase double-star armature windings of a synchronous generator are essentially equivalent to 12-phase symmetrical windings displaced in turn by 30deg. This paper proposes and implements a new permanent-magnet brushless dc (BLDC) generator using 12-phase half-wave rectifier. Characteristic of output voltage is analyzed according to the star graph of slot potential, and the design constraints of armature windings are provided. Simulation models of 12-phase synchronous generator with half-wave rectifier and double-star synchronous generator with bridge rectifier are established separately. Field-circuit-coupled analysis is accomplished, and conducted modes of rectified diodes and output characteristic are obtained. It is shown that the current stress of diodes in 12-phase rectification system is less than half of that in double-star rectification system, and the output voltage fluctuation between the two different rectification systems is similar. Experimental results on prototype machine, which agree well with the simulation analysis, also verify the feature of the proposed BLDC generator system.

Series arc faults (SAFs) are a primary cause of fire incidents in photovoltaic systems. Accurately and rapidly detecting SAF under the interference of power electronic devices remains a significant challenge. This article proposes an SAF detection method based on the time-frequency Markov permutation transition field (TFMPTF). First, variational mode decomposition is used to decompose the current signal into modes containing different frequency components to prevent interference between the information of different frequency bands. Then, the modes are transformed into two-dimensional matrices using TFMPTF. Innovatively, the concept of time-frequency permutation patterns state transition analysis in TFMPTF is proposed, from which the distinct structural information of the current signal can be effectively depicted. Afterward, singular value decomposition is employed to extract fault features from matrices. Finally, fault features are processed using a kernel extreme learning machine to obtain detection results. Offline experimental results show that the average detection accuracy of the proposed method is 98.97%, and the advancedness and adaptability of the proposed method are verified by comparing it with different methods. The proposed method and comparison methods are implemented in a microprogrammed control unit (MCU) for online experiments, further confirming that the detection speed and detection accuracy of the proposed method are reliable.

The transportation sector is undergoing electrification to gain advantages such as lighter weight, improved reliability, and enhanced efficiency. As contributors to the safety of embedded critical functions in electrified systems, better sizing of electric machines in vehicles is required to reduce the cost, volume, and weight. Although the designs of machines are widely investigated, existing studies are mostly complicated and application-specific. To satisfy the multi-level design requirements of power systems, this study aims to develop an efficient modeling method of electric machines with a background of aircraft applications. A variable-speed variable-frequency (VSVF) electrically excited synchronous generator is selected as a case study to illustrate the modular multi-physics modeling process, in which weight and power loss are the major optimization goals. In addition, multi-disciplinary design optimization (MDO) methods are introduced to facilitate the optimal variable selection and simplified model establishment, which can be used for the system-level overall design. Several cases with industrial data are analyzed to demonstrate the effectiveness and superior performance of the modeling method. The results show that the proposed practices provide designers with accurate, fast, and systematic means to develop models for the efficient design of aircraft power systems.