Comparative Study of Consequent-Pole Switched-Flux Machines with Different U-Shaped PM Structures

This paper presents a comparative study of two consequent-pole switched-flux permanent magnet (CP-SFPM) machines with different U-shaped PM arrangements. In order to address the flux barrier effect in a sandwiched SFPM machine, two different alternate U-shaped PM designs are introduced to improve the torque capability, forming two CP-SFPM machine topologies. In order to reveal the influence of different magnet designs on the torque production, a simplified PM magneto-motive force (MMF)-permeance model is employed to identify the effective working harmonics in the two CP-SFPM machines. The torque contributions of the main working harmonics are subsequently quantified by a hybrid finite-element (FE)/analytical method. Multi-objective genetic algorithm (GA) optimization is then employed to optimize the design parameters of the proposed CP-SFPM machines. In addition, the electromagnetic characteristics of the CP-SFPM machines with two U-shaped PM arrangements are investigated and compared by the FE method. Finally, a 6/13-pole CP-SFPM machine with an optimally selected U-shaped PM structure is manufactured and tested to validate the FE analyses

Multi-Objective Optimization of a Permanent Magnet Actuator for High Voltage Vacuum Circuit Breaker Based on Adaptive Surrogate Modeling Technique

A novel mono-stable permanent magnet actuator (PMA) for high voltage vacuum circuit breaker (VCB) and its optimal design method are proposed in this paper. The proposed PMA is featured with a structure of separated magnetic circuits, which makes the holding part and closing driving part work independently without interference. The application of an auxiliary breaking coil decreases the response time in the initial phase of opening operation, and an external disc spring is adopted to accelerate the opening movement, which makes the PMA meet the fast-breaking requirement of high voltage VCB. As calculating the characteristics of the PMA accurately through numerical simulation is a time-consuming process, a multi-objective optimization (MOO) algorithm based on surrogate modeling technique and adaptive samples adding strategy are proposed to reduce the workload of numerical simulations during optimization. Firstly, initial surrogate models are constructed and evaluated, and then iteratively updated to improve their global approximating abilities. Secondly, according to the approximate MOO results obtained by the global surrogate models, additional samples are added to constantly update the surrogate models to gradually improve the models’ local accuracies in optimal solution regions and finally guide the algorithm to the true Pareto front. The efficiency and accuracy of the proposed algorithm are verified by test functions. By applying the optimization strategy to the design of the proposed PMA, a set of satisfying Pareto optimal solutions, which improve the overall performance of the PMA obviously, can be derived at a reasonable computation cost

Investigation of the over-load unintentional remagnetization effect in series hybrid magnet variable flux memory machine

Variable flux memory machines (VFMMs) have become a research hotspot due to their adjustable air-gap flux with the employment of low coercive force (LCF) permanent magnets (PMs). Series hybrid magnet VFMMs (SHM-VFMMs) utilizing series-magnetic-circuit high coercive force (HCF) and LCF PMs are extensively investigated due to their excellent unintentional demagnetization (UD) withstand capability. Nevertheless, the existing researches still focus on the UD of LCF PMs under heavy load operation, and the remagnetization issue remains unreported. Therefore, in this paper, the over-load unintentional remagnetization (UR) effect of the a dual-layer-SHM-VFMM (DLSHM-VFMM) is first revealed, and its mechanism is investigated and analyzed in depth based on finite element (FE) analyses. A DLSHM-VFMM prototype is manufactured and tested to verify the effectiveness of the theoretical analyses