Transformations between abc, stationary dq0 (αβ0) and rotating dq0 reference-frames are used extensively in the analysis and control of three-phase technologies such as machines and inverters. Previous work on deriving the matrices describing these transformations follows one of two approaches. The first approach derives Clarke's matrix by modifying symmetrical components. Park's matrix can be subsequently found from a rotation matrix. The second approach derives Park's matrix using trigonometric projection by interpreting the transformation as a rotation in the plane of the cross-section of a machine. Then, Clarke's matrix can be found trivially using a reference angle of zero in Park's matrix. This paper presents a third approach to deriving the Clarke and Park transformation matrices: a geometric interpretation. The approach exploits properties of the linear transformation using the Cartesian representation. We introduce the locus diagram of a three-phase quantity and show how these diagrams have applications in power quality. We show that, unlike a phasor diagram, a single locus diagram can fully represent a three-phase system with harmonics.

With ever-increasing concern of fossil fuel storage and environmental pollution, transportation electrification has recently attracted extensive attention. In conventional propulsion systems, the engine is connected to the wheel through a clutch, reduction gearbox, and mechanical differential. The mechanical transmission inevitably results in power loss, noise, vibration, and additional maintenance. With elimination of the gearbox and transmission component, the direct-drive technique exhibits significant advantages of higher systematic efficiency, more flexible wheel control, and better passenger comfort. This paper aims to provide an overview of automobile direct-drive techniques and recent electrical machine developments for direct-drive propulsion systems. Benefits and limitations of various direct-drive machines are summarized and compared with typical industrial products. Finally, the opportunities, challenges, and future development trends are discussed in related to the research “hot spots”.

Electric propulsion of ships has experienced steady expansion for several decades. Since the early 20th century, icebreakers have employed the flexibility and easy control of direct current (dc) motors to provide for ship operations that split ice with back and forth motion of the ship. More recently, cruise ships have employed diesel-electric propulsion systems to take advantage of the flexibility of diesel, as opposed to steam engines, and because the electric plant can also be used for hotel loads. Research vessels, ferries, tankers, and special purpose vessels have also taken advantage of increased flexibility and fuel efficiency with electric propulsion. Today, the U.S. Navy is building an “all electric” destroyer to be named “Zumwalt,” which employs two induction motors for propulsion. There are several different classes of motors that might be considered for use in ship propulsion, ranging from dc (commutator) motors through conventional induction and synchronous motors to permanent magnet synchronous machines, doubly fed machines and superconducting alternating current (ac) and acyclic homopolar machines. This review paper describes features of some of the major classes of motor that might be used in ship propulsion.

This paper introduces an adaptive voltage and frequency control method for inverter-based distributed generations (DGs) in a multi-microgrid (MMG) structure using distributed cooperative control and adaptive neural networks (ANN). First, model-based controllers are designed using the Lyapunov theory and dynamics of the inverter-based DGs. ANNs are then utilized to approximate these dynamics, resulting in an intelligent controller, which does not require a priori information about DG parameters. Also, the proposed controllers do not require the use of voltage and current proportional-integral controllers normally found in the literature. The effectiveness of the proposed controllers are verified through simulations under different scenarios on an MMG test system. Using Lyapunov analysis, it is proved that the tracking error and the neural network weights are uniformly ultimately bounded, which results in achieving superior dynamic voltage and frequency regulation.

Representing a major technology toward the proliferation of sustainable energy resources, droop controlled microgrids have attracted numerous modeling approaches with a view to improving their operation and applicability. Acknowledging the low inertia of distributed generators and the network characteristics at the distribution level, this paper proposes a reduced order model for inter-inverter oscillations in autonomous droop controlled microgrids. At first, a simplified equivalent network on the basis of Kron reduction is suggested as an effective topology for the study of inter-inverter oscillating currents. The focus shifts toward low-frequency modes following the detailed small signal model and its simplification according to the singular perturbation theory with multiple time scales. Assuming accurate and instantaneous tracking of the voltage by the inner controllers on their local reference frame, the quasi steady state study results in a simple closed-loop model. This model is successfully benchmarked against the detailed model and other germane models over the full range of operational damping ratios.

Axial flux induction motors have attracted attention in electric vehicles due to their advantages over conventional motors, including higher efficiency, compact structure, high utilization of materials, and good ventilation and cooling. This paper provides a fast design method for two-stator-one-rotor axial flux induction motor of electric vehicle applications. The proposed method consisting of an accurate motor analytical model and a design variables optimization method based on genetic algorithm. Unlike traditional design of axial flux induction motor with single objective, multi-objective is considered in this work. Based on the proposed method, the performance of axial flux induction motor can be simulated and optimized in much shorter time compared with finite element analysis in ANSYS Maxwell. The comparison results from ANSYS Maxwell can prove the effectiveness and accuracy of the proposed method, and the performance of the final designed motor can meet all the design requirements.