Dry-type transformers are widely used in modern power systems because of their safety and reliability, and their insulation performance directly affects operational stability and service life. Existing studies mainly focus on electric-field breakdown of insulation structures, while dielectric loss caused by insulation gap variations has received less attention. This study develops a two-dimensional axisymmetric finite-element model of the main insulation of a 10 kV dry-type transformer. It investigates how the LV-HV gap and the Fe-LV gap affect electric-field distribution. The active/reactive power method is used to extract volume loss density and terminal complex current, calculate the equivalent dielectric loss factor of the main insulation, and analyze the effect of the LV-HV gap on dielectric loss. Within the simulated conditions, the LV-HV gap strongly affects field intensity and dielectric loss: reducing it from 21 mm to 13 mm at power frequency increases the equivalent dielectric loss by about 52.5%, whereas the Fe-LV gap has a negligible effect. For the three LV-HV gaps examined (13, 17, and 21 mm) at power frequency, an empirical power-law correlation is fitted. Since it is based on only three data points, it should be treated as a local interpolation rather than a validated quantitative law and should not be extrapolated. The study examines the chain “insulation gap–electric-field distribution–dielectric loss” in terms of peak field, field distribution, and energy integration. It also highlights the role of field uniformity in dielectric loss regulation. These results provide theoretical and simulation support for multi-objective optimization of dry-type transformers, balancing electrical strength, volume, and operational loss. All results are from 2D finite-element simulations at 10 kV and have not been experimentally validated; the conclusions are therefore provisional and limited to the studied conditions.
The security of modern electronic systems is increasingly grounded in the physical properties of hardware, rather than on purely algorithmic assumptions. In this context, passive circuit elements with memory, commonly referred to as mem-elements, have emerged as promising candidates for implementing hardware-based security primitives. Among them, memristors, as the most experimentally mature devices, have demonstrated significant potential in Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) by exploiting their intrinsic variability, nonlinearity, and history-dependent behavior. By contrast, memcapacitors and meminductors, which extend memory effects to energy-storing electrical and magnetic domains, remain largely unexplored in security applications, despite their richer dynamical structure and greater theoretical potential for entropy generation and resistance to inference. This mini-review provides a structured overview of the state of the art of mem-elements in hardware security, highlighting the differences in dynamical behavior and security-relevant properties across memristors, memcapacitors, and meminductors. The review identifies key limitations of current approaches based on static or low-dimensional variability, discusses the implications of machine-learning-based modelling attacks, and outlines open research challenges associated with the limited availability of memcapacitive and meminductive devices. Finally, it explores the potential of coupled memcapacitor–meminductor systems as a fundamentally new platform for entropy-driven and dynamically evolving security primitives, opening promising directions for next-generation hardware security.
Mechanical vibration is a common operating condition of power transformers and may interact with electrical stress, thereby influencing partial discharge (PD) behavior in oil–paper insulation. To investigate this influence, an electro-mechanical coupled experimental platform was developed. Two typical PD defects, namely, needle–plate and floating electrode defects, were studied under various vibration frequencies and acceleration levels. The experimental results indicate that mechanical vibration affects PD characteristics in a defect-dependent manner. For floating defects, vibration significantly reduces the partial discharge inception voltage (PDIV) and average discharge magnitude, while markedly increasing the discharge repetition rate. Under certain conditions, the repetition rate increases by more than one order of magnitude, indicating intensified discharge activity. In contrast, the needle–plate defect exhibits lower sensitivity to vibration. Moderate vibration tends to suppress PD development and slightly increase PDIV, whereas higher vibration levels may promote discharge occurrence. Further analysis suggests that these differences arise from distinct dominant mechanisms. The PD behavior of floating defects is mainly attributed to vibration-induced electric field distortion caused by periodic electrode displacement, while that of needle–plate defects is jointly influenced by electric field variation and bubble dynamics in the oil gap. These findings provide experimental insight into the diagnosis of electro-mechanical coupled faults in power transformers.
DC/DC converters are widely employed in dc distribution systems and motor-drive power supplies to provide voltage conversion, dc-bus regulation, and power-flow control between distributed sources, energy-storage units, and power-electronic loads. When downstream tightly regulated converters behave as constant power loads (CPLs), their negative incremental impedance can reduce dc-bus damping and enlarge voltage overshoot. To improve the large-signal stability and transient performance of an interleaved Boost converter, this paper proposes a composite control strategy combining a virtual dc machine (VDCM) voltage loop and a passivity-based control (PBC) current loop. An averaged model of the two-phase interleaved Boost converter in continuous conduction mode is first derived, and an Euler-Lagrange representation with a CPL is formulated. Then, an inner-loop PBC law is designed from the error-energy function and damping injection, which ensures convergence of the inductor-current tracking error. Furthermore, a VDCM outer loop is introduced to emulate the external characteristic of a dc machine with virtual inertia and damping, and its output is converted into the total inductor-current reference. The effectiveness of the proposed method is evaluated through comparisons with PI + PI and PI + PBC control. Finally, a prototype of an interleaved Boost converter based on GaN devices with a rated power of 3 kW and a power density of 9 kW/L is designed and built. Experimental results from the prototype further validate the accuracy of the simulation results and the excellent steady-state performance of the proposed composite control strategy across the full load range.
For conventional freezer trucks, engines are required to run during both driving and parking to power the freezer units. It causes emissions and noise. A solar-powered freezer truck is developed in this article to eliminate emissions and considerably reduce noise. Multiple energy inputs and energy systems are proposed to offer flexible energy control for energy management. The multiple energy inputs include solar energy, the onboard battery energy, the off-board plug-in AC energy, and the external battery energy from another electric vehicle for testing the connected vehicle function. Furthermore, an optimal energy management strategy is proposed to ensure reliable operation of the freezer unit, maximize the photovoltaic (PV) output power, maintain the high-efficiency operation of the energy system, and extend the service lifetime of the onboard battery. The energy design formulation is presented in this article. The development of the solar-powered freezer truck was verified by the experimental results of the prototype. Therefore, this article is significantly valuable for the application of solar-powered refrigeration/freezer trucks and ways to extend energy usage using connected vehicle technology.
