首页> 外文会议>Annual American Control Conference >Stator Resistance Estimation Using Adaptive Estimation via a Bank of Kalman Filters
【24h】

Stator Resistance Estimation Using Adaptive Estimation via a Bank of Kalman Filters

机译:借助一组卡尔曼滤波器的自适应估计进行定子电阻估计

获取原文

摘要

Accurate and efficient control of electric motors is dependent on knowledge of motor parameters such as the resistance and the inductance of the winding. However, these parameters are often unavailable to the control designer because they are dependent on the motor design and may change due to environmental effects such as temperature. An accurate real-time method to determine the values of these unknown parameters can improve motor performance over the entire operating range. In this work, a parameter estimation technique based on a bank of Kalman filters is used to adaptively estimate the motor winding resistance. Simulation results for a 3.5 horsepower interior permanent magnet (IPM) synchronous motor operating at rated torque demonstrate that this technique may be used for real-time estimation of motor parameters.
机译:电动机的准确和有效控制取决于电动机参数的知识,例如绕组的电阻和电感。但是,这些参数通常对于控制设计人员来说是不可用的,因为它们取决于电动机的设计,并且可能会由于环境影响(例如温度)而发生变化。一种确定这些未知参数值的准确实时方法可以改善整个工作范围内的电动机性能。在这项工作中,基于一排卡尔曼滤波器的参数估计技术用于自适应估计电动机绕组电阻。在额定扭矩下运行的3.5马力内部永磁体(IPM)同步电动机的仿真结果表明,该技术可用于实时估计电动机参数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号