Investigation and Analysis of Novel Skewing in a 140 kW Traction Motor of Railway Cars That Accommodate Limited Inverter Switching Frequency and Totally Enclosed Cooling System

This study facilitated the improvement of no-load back electromotive force (back-EMF) wave form, total harmonic distortion (THD) of back-EMF, and torque ripple using a novel skew angle formula, considering the specific order of a no-load THD. In real usage environments, it is taken into consideration for the fully enclosed cooling system and limited inverter switching frequency of urban railway car traction motors. Since the most railway car traction motors use high-withstand voltage rectangular wires in slot-open structure, a no-load back EMF waveform includes large space slot harmonics, which should be smaller as possible. For 6-step control, the no-load back EMF waveform is important because switching for motor control is performed once after the rotor position is determined. To improve the no-load back EMF waveform and THD, two-dimensional and three-dimensional finite element analysis (FEA) were performed using a novel skew angle formula considering specific harmonic order reduction, while the fundamental amplitude was minimally reduced. A prototype with the novel skew was fabricated and verified. In addition, it was designed by calculating a low current density for a fully enclosed cooling system. A temperature saturation experiment was also performed, and successfully verified. Therefore, we suggest that the no-load back EMF characteristics and torque ripple are improved by applying the novel skew angle instead of a traditional skew angle.

*Published in the IEEE Magnetics Society Section within IEEE Access.

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Green Elevator Scheduling Based on IoT Communications

In this paper, we propose an energy-saving elevator scheduling algorithm to reduce the car moving steps to achieve motor energy saving and green wireless communications. The proposed algorithm consisting of six procedures can attain fewer Internet of Things (IoT) message exchanges (i.e. communication transmissions) between the Scheduler subsystem and the Car subsystem via the core function AssignCar(r). The function AssignCar(r) is capable of assigning a request to the nearest car through car search globally. From the emulation results for four cars, this work shows that the proposed algorithm outperforms the previous work named as aggressive car scheduling with initial car distribution (ACSICD) algorithm with energy consumption reductions by 49.43%, 47.68%, 37.89%, and 47.65% for up-peak, inter-floor, downpeak, and all-day request patterns, respectively.

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