高性能电动机中的温度传感器虚拟化

Andrea Zanellini, Stefano Pellegrini, Mariano Nerone, Igor Valic, Matteo Zauli, L. Marchi, N. Matteazzi, M. Violi, R. Rovatti
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引用次数: 0

摘要

越来越多的工业应用需要紧凑型电机以最高效率提供高扭矩和功率。如果设计得当,永磁同步电机(pmms)能够满足这一需求。要完全解锁这些功能,了解和精确控制电机的热状态是基本的。事实上,高温可能是至关重要的,因为它们可能导致绝缘熔化或磁体退磁。由于旋转,转子内部温度的直接测量是一个昂贵和复杂的选择,我们在这里估计它从更容易获得的数量。特别是,我们将通过在实际电机上的实验来证明,通过将外部温度和电机电气状态的读数输入到适当训练的神经结构中,可以获得误差在几个度以内的估计。
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Temperature Sensors Virtualization in High Performance Electric Motors
An increasing number of industrial applications require compact motors delivering high torque and power with maximum efficiency. If properly designed, Permanent Magnet Synchronous Motor (PMSMs) are capable to satisfy this needs. To fully unlock such capabilities, knowing and controlling precisely the thermal state of the motor is fundamental. In fact, high temperatures can be critical as they may cause insulation melting or magnets demagnetization. Due to the rotation, the direct measurement of rotor’s inner temperatures is an expensive and complex option, and we here estimate it from more accessible quantities. In particular we will show by experiments on an actual motor that estimations within few degrees of error can be obtained by feeding readings of external temperatures and of the motor electrical status into suitably trained neural architectures.
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