控制理论(社会学)
感应电动机
涡流
病媒控制
扭矩
稳态(化学)
直接转矩控制
磁通量
焊剂(冶金)
控制器(灌溉)
转子(电动)
电压
计算机科学
工程类
物理
磁场
材料科学
控制(管理)
化学
农学
电气工程
物理化学
热力学
人工智能
生物
机械工程
冶金
量子力学
作者
Zengcai Qu,Mikaela Ranta,Marko Hinkkanen,Jorma Luomi
标识
DOI:10.1109/tia.2012.2190818
摘要
This paper applies a dynamic space-vector model to loss-minimizing control in induction motor drives. The induction motor model, which takes hysteresis losses and eddy-current losses as well as the magnetic saturation into account, improves the flux estimation and rotor-flux-oriented control. Based on the corresponding steady-state loss function, a method is proposed for solving the loss-minimizing flux reference at each sampling period. A flux controller augmented with a voltage feedback algorithm is applied for improving the dynamic operation and field weakening. Both the steady-state and dynamic performance of the proposed method is investigated using laboratory experiments with a 2.2-kW induction motor drive. The method improves the accuracy of the loss minimization and torque production, it does not require excessive computational resources, and it shows fast convergence to the optimum flux level.
科研通智能强力驱动
Strongly Powered by AbleSci AI