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Minimization of Commutation Torque Ripple in Brushless DC Motors with Optimized Input Voltage Control

机译:利用优化输入电压控制的无刷直流电机中换向扭矩波动的最小化

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This paper presents the method of reducing torque ripple of brushless DC (BLDC) motor. The commutation torque ripple is reduced by control of the DC link voltage during the commutation time. The magnitude of voltage and commutation time is estimated by a neural network and optimized with a new optimization method named particle swarm optimization (PSO) algorithm analysis. The goal of optimization is to minimize the error between the command torque and real torque and doesn't need knowledge of the conduction interval of the three phases. It adaptively adjusts the DC link voltage in commutation duration so that commutation torque ripple is effectively reduced. In this paper, the performance of the proposed brushless DC (BLDC) control is compared with that of conventional BLDC drives without input voltage control.
机译:本文介绍了减少无刷直流(BLDC)电机的扭矩脉动的方法。通过在换向时间期间控制DC链路电压来减小换向转矩纹波。电压和换向时间的大小由神经网络估计,并用新的优化方法优化名为粒子群优化(PSO)算法分析。优化的目标是最小化命令扭矩和真实扭矩之间的误差,并且不需要三相的传导间隔知识。它适自适应地调节换向持续时间的直流链路电压,以便有效地降低换向转矩脉动。在本文中,将所提出的无刷直流(BLDC)控制的性能与传统BLDC驱动器的性能进行比较,而无需输入电压控制。

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