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Speed-sensorless torque control of induction motors for hybrid electric vehicles.

机译:混合动力汽车感应电动机的无速度传感器转矩控制。

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摘要

Hybrid Electric Vehicles (HEVs) are exciting new additions to the car markets since they combine the best features of conventional and electric cars to improve environmental performance and reduce fuel consumption. HEVs get their driving power from both an internal combustion engine and an electric motor. Many researches have demonstrated the induction motor is one of the right electric motor candidates for the most HEVs due to its low cost, robustness and low maintenance.; The objective of this research work is to develop a new speed-sensorless control method for induction motors to optimize torque response and improve robustness in order to meet the requirement of HEV applications. The proposed new control method is based on Sliding-Mode Control (SMC) combined with Space Vector Modulation (SVM) technique. The SMC contributes to the robustness of induction motor drives, and the SVM improves the torque, flux, and current steady-state performance by reducing the ripple. The Lyapunov direct method is used to ensure the reaching and sustaining of sliding-mode and stability of the control system. A sliding-mode observer is proposed to estimate the rotor flux and speed. Computer simulation results show that the proposed control scheme owns very good dynamic characteristics, high accuracy in torque tracking to various reference signals and strong robustness to external load disturbances.
机译:混合动力电动汽车(HEV)是汽车市场上令人兴奋的新成员,因为它们结合了常规和电动汽车的最佳功能,以改善环保性能并减少燃油消耗。混合动力汽车的动力来自内燃机和电动机。许多研究表明,感应电动机由于其低成本,耐用性和低维护成本而成为大多数混合动力汽车的最佳选择之一。这项研究工作的目的是为感应电动机开发一种新的无速度传感器控制方法,以优化扭矩响应并提高鲁棒性,从而满足HEV应用的要求。所提出的新控制方法是基于滑模控制(SMC)结合空间矢量调制(SVM)技术的。 SMC有助于感应电动机驱动器的坚固性,而SVM通过减少纹波来改善转矩,磁通和电流稳态性能。 Lyapunov直接方法用于确保达到并维持滑模以及控制系统的稳定性。提出了一种滑模观测器来估计转子磁链和速度。计算机仿真结果表明,所提出的控制方案具有很好的动态特性,对各种参考信号的转矩跟踪精度高,对外部负载干扰具有很强的鲁棒性。

著录项

  • 作者

    Fu, Tianjun.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Engineering Mechanical.; Engineering Automotive.
  • 学位 M.A.S.
  • 年度 2005
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;自动化技术及设备;
  • 关键词

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