Microgrids are networked control systems with multiple distributed generators (DGs). Microgrids are associated with many problems, such as communication delays, high sampling rates, and frequent controller updates, which make it challenging to realize coordination control among the DGs. Therefore, finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems. The DG in the microgrid system serves as an agent node in the control network, and a distributed secondary controller is designed using finite-time consensus algorithm, such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance. The event-triggered function was designed based on the state information of the agents. The controller exchanges the state information at the trigger instants. System stability is analyzed using the Lyapunov stability theory, and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process. A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.

Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet (PM) topologies. Consequently, a comprehensive, accurate, and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations. A unique three-dimensional (3D) lumped parameter thermal network (LPTN) is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator (OR-HPMFSG) for direct-drive applications. First, the losses of the OR-HPMFSG are calculated using 3D finite element analysis (FEA). Subsequently, all machine components considering the thermal contact resistance, anisotropic thermal conductivity of materials, and various heat flow paths are comprehensively modeled based on the thermal resistances. In the proposed 3-D LPTN, internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components. Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN. A comparison of the results at various operating points between the developed 3-D LPTN, experimental test, and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.

This study investigates the negative influence of an eccentric permanent-magnet (PM) design on high-frequency electromagnetic vibration in fractional-slot concentrated-winding (FSCW) PM machines. First, an analytical expression for the sideband current harmonics was derived using the double Fourier series expansion method. Then, the characteristics of the flux-density harmonics are studied from the perspective of the space-time distribution and initial phase relationship. The influence of the eccentric PM design on high-frequency electromagnetic and concentrated forces was studied based on the electromagnetic force modulation effect. Consequently, an eccentric PM design is not conducive to reducing the 2p th -order high-frequency electromagnetic forces. Finally, two FSCW PM machines with conventional and eccentric PM designs are manufactured and tested to verify the theoretical analysis. The results show that the eccentric PM design worsens high-frequency vibrations.

Energy-storage technologies based on lithium-ion batteries are advancing rapidly. However, the occurrence of thermal runaway in batteries under extreme operating conditions poses serious safety concerns and potentially leads to severe accidents. To address the detection and early warning of battery thermal runaway faults, this study conducted a comprehensive review of recent advances in lithium battery fault monitoring and early warning in energy-storage systems from various physical perspectives. The focus was electrical, thermal, acoustic, and mechanical aspects, which provide effective insights for energy-storage system safety enhancement.

The electromagnetic vibration noise in axial flux motors was meticulously examined. In this study, 24-slot/10-pole and 12-slot/10-pole axial flux motors were chosen as the subjects of research. The spatial characteristics of the axial electromagnetic force were derived analytically and confirmed via two-dimensional Fourier decomposition. The finite-element method was used to simulate the low-order axial modes of both motors. Furthermore, a modal experiment on the stator of a 24-slot/10-pole axial flux motor was conducted to validate the simulation's accuracy. By integrating the electromagnetic and structural models, a comprehensive multi-physical field model was developed to calculate the vibration noise of the axial flux motor. The precision of this model was subsequently corroborated with noise experiments. The findings from this study aim to offer insights into identifying the sources of vibration noise in axial flux motors.

This study aimed to improve the vibration and torque of an integral-slot surface-mounted permanent magnet (SPM) machine by optimizing the shape of the harmonically injected permanent magnet (PM). First, the effect of the third harmonic injected into the sinusoidal PM shape on the electromagnetic performance of a 36-slot/12-pole SPM machine was investigated, including the torque performance and vibration response. It was found that the Sin+3rd harmonic-shaped PM had a contrary effect on the torque and vibration performance of the integral-slot machine, which improved the torque capability but worsened the vibration performance. Second, the response surface model and Barebones multi-objective particle swarm optimization algorithm based on a trade-off between the average torque and vibration were implemented to determine the optimal harmonic injection. Subsequently, the performances of the optimal Sin+3rd-shaped and eccentric PM machines were compared, showing the excellent torque and vibration performance of the adopted method. Finally, a prototype was manufactured and tested to verify the results of the theoretical analysis.

The hybrid structure of a power-module package is summarized and classified. Basic and extended planar wire-bond designs are analyzed and compared with regular wire-bond modules and planar modules, respectively. The automatic layout method can improve the electrical and thermal performance of hybrid structures. A state-of-the-art hybrid structure is introduced, and suggestions for alleviating the current and temperature imbalances for future designs are provided.

Designing high-gain observers (HGOs) for the state estimation of an electric vehicle's electrohydraulic brake (EHB) system is challenging. This type of observer is applicable to model nonlinearities and constant feature gains. However, they are very sensitive to measurement noise, which is unavoidable in EHB. The first novelty of this study is that it compensates for the measurement noise using a filtered high-gain observer (FHGO) to ensure EHB state estimation. The proposed FHGO provides an estimate of the master cylinder pressure, motor current, and rotor speed from measurements of the rotor position. The second novelty is the design of an extremum-seeking (ES) optimization loop to adjust the FHGO gains online. The performance of the developed FHGO with ES-based online gain optimization was highlighted in the presence of model uncertainties and output measurement noise using a Matlab/Simulink simulation. The superiority of the FHGO (even with a fixed gain) over a standard high gain observer (SHGO) was also demonstrated.

A wind energy conversion system (WECS) based on a permanent magnet synchronous generator (PMSG) is an effective solution for renewable energy generation in modern power systems. The main advantages of PMSG include high performance at high and low speeds, minimal control effort owing to lower rotor inertia, self-excitation, high reliability, and simplicity of structure compared with induction generators. However, the intermittent nature of wind energy implies that maximum efficiency is not obtained from this system. Accordingly, maximum power point tracking (MPPT) in wind turbine systems has been proposed to address this problem. Traditional MPPT strategies suffer from severe output power fluctuations, low efficiency, and significant ripples in turbine rotation speed. This paper presents a novel MPPT control strategy based on fuzzy logic control (FLC) and model predictive control (MPC) to extract the maximum power from a PMSG-WECS and control the machine-side and grid-side converters. The simulation results obtained from Matlab/Simulink confirm the superiority of the control model in eliminating the output power fluctuations of the wind generators and accurately tracking the maximum power point. A comparative study between conventional MPPT and control methods is also conducted.