With the growing adoption of both residential and commercial electric vehicles (EV) and the rapid deployment of EV charging stations, it is of paramount importance to assess the potential overloading impact of intensive EV charging on the operation and planning of power distribution systems. Targeting at the west Kentucky rural area, this research leverages the Distribution Resource Integration and Value Estimation (DRIVE) and HotSpotter software tools to investigate the potential impact of EV charging on the operation of regional distribution systems and the lifetime degradation of power transformers. The research outcome helps identify possible distribution system overload risks and mitigation solutions to meet future intensive EV charging necessity under assumed EV adoption scenarios. Possible overloading in the distribution systems and undervoltage violations are examined. In addition, the overload impact of EV charging is investigated by conducting a multi-physics reliability analysis of a distribution transformer.

An electrical power system for low earth orbit satellites that can be reused for a variety of mission requirements with minimal redesign is proposed. The goals of the proposed power system are achieved by modularizing the subsystems of a small spacecraft and designing them to allow any number of each module to be connected simultaneously. The modularized subsystems include solar energy generation and energy storage. The overall objectives will be accomplished without compromising efficiency or power system stability. The purpose of this paper is to describe the proposed power system and detail the experimental results. The generalized system can be used as a one-size-fits-all solution that only requires basic power systems knowledge to configure and operate.

This paper presents the optimization study targeting a specific drive cycle for a MAGNUS-type axial-flux permanent magnet vernier machine (AFPMVM). The proposed MAGNUS machine has a novel design with a dual-stator configuration, where only one stator is wound, with a high-polarity spoke permanent magnet (PM) rotor. The machine topology has a 3D flux path, which necessitates the analysis of a large finite element (FE) model. However, due to the computational complexity and time required for such a large FE model, a new approach was developed. This approach involves a computationally efficient finite element analysis (CE-FEA) model combined with a single-point drive cycle analysis and the differential evolution (DE) optimization algorithm. The targets of the optimization algorithm are derived by modeling the load operating cycle through a systematic k-means clustering method, identifying specific operating points representing high-energy zones within the drive cycle. The optimized design achieves a wide range of constant power operation, which is desirable for electric vehicle (EV) in-wheel traction. Experimental and numerical results demonstrate a higher torque density in the MAGNUS machine compared to commercially available electric vehicle traction motors. Additionally, the paper explores various flux-weakening methods for the MAGNUS machine, highlighting their respective benefits.

Outer-rotor switched reluctance machines (SRMs) have drawn much attention as promising candidates for in-wheel direct-drive motors of future electric vehicles. This paper presents a systematic performance comparison of three outer-rotor SRM topologies for in-wheel traction applications in terms of the specific torque, electromagnetic efficiency, torque ripple, radial force and mechanical aspects. A generalized design optimization framework for SRMs is proposed to enable the fast evaluation of large numbers of designs generated from the differential evolution (DE) by incorporating an analytical current profile estimation into the transient finite element analysis (FEA). The relationship between the saliency ratio and converter volt-ampere (VA) rating is also discussed. The calculations are then benchmarked with the experimental results from an existing prototype. The effectiveness of the performance prediction method and the proposed optimization approach is validated.

Capacitive deionization (CDI) operated under inverted mode involves electronic charging and discharge steps with corresponding ion concentration and desalting coupled with simultaneous energy storage. In this work, an energy recovery system derived from a Ćuk dc–dc converter is explored to transfer the energy stored from one inverted capacitive deionization (i-CDI) cell during the electronic discharge step to another during the charge step, decreasing the overall energy requirement for capacitive water desalination. The i-CDI cell, a subset of CDI architecture operated in an inverted mode, is improved by incorporating ion-selective membranes to allow inverted membrane capacitive deionization (i-MCDI), leading to enhanced charge storage achieved with reduced energy input. For example, in comparison to i-CDI that requires ∼12 J g⁻¹ of energy input, the i-MCDI cell requires only 8 J g⁻¹. By incorporating the recovery system, the energy penalty can be reduced to only require ∼8 and 4 J g⁻¹ for i-CDI and i-MCDI cells, respectively. Improvement in energy recovery was shown to be achieved by reducing charge leakage, with the i-MCDI cell showing up to 3 times the leakage resistance of the i-CDI cell.

Brushless excitation systems are widely used for synchronous machines. As a critical part of the system, rotating rectifiers have a significant impact on the system behavior. This paper presents a numerical average-value model (AVM) for rotating rectifiers in brushless excitation systems, where the essential numerical functions are extracted from the detailed simulations and vary depending on the loading conditions. Open-circuit voltages of the brushless exciter armature are used to calculate the dynamic impedance that represents the loading condition. The model is validated by comparison with an experimentally validated detailed model of the brushless excitation system in three distinct cases. It has been demonstrated that the proposed AVM can provide accurate simulations in both transient and steady states with fewer time steps and less runtime compared with detailed models of such systems and that the proposed AVM can be combined with AVM models of other rectifiers in the system to reduce the overall computational cost.