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Sensorless Speed Control of Induction Motor Driven Electric Vehicle Using Model Reference Adaptive Controller

机译:使用模型参考自适应控制器的感应电动机驱动电动车辆无传感器速度控制

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This paper proposes a new sensorless speed control technique for induction motor (IM) driven electric vehicle (EV) using a model reference adaptive controller (MRAC) with a basic energy optimization technique known as golden section method. The proposed MRAC for the vector controlled IM drive utilizes instantaneous and steady state values of a fictitious resistance (R) in the reference and adaptive models respectively. The proposed scheme is immune to the variation in stator resistance (Rs). Moreover, the unique formation of the MRAC with the instantaneous and steady-state reactive power completely eliminates the requirement of any flux estimation in the process of speed estimation. Thus, the method is insensitive to integrator-related problems like drift and saturation enabling the estimation at or around zero speed quite accurately. The proposed drive's performance with the R-MRAC is validated for various speed ranges and patterns in Matlab/Simulink. Sensitivity of various motor parameters and stability studies are carried out using eigenvalues loci plots by first order eigenvalue sensitivity analysis.
机译:本文提出了一种新的传感器速度控制技术,用于使用模型参考自适应控制器(MRAC)的感应电动机(IM)驱动的电动车(EV),具有称为Golden Section方法的基本能量优化技术。用于矢量控制IM驱动器的所提出的MRAC分别利用参考和自适应模型中的虚拟电阻(R)的瞬时和稳态值。该方案对定子抗性(Rs)的变异免疫。此外,MRAC与瞬时和稳态无功功率的独特形成完全消除了速度估计过程中的任何助焊剂估计的要求。因此,该方法对集成器相关的问题不敏感,如漂移和饱和度,例如零速度的估计非常精确。建议的驱动器与R-MRAC的性能验证了Matlab / Simulink中的各种速度范围和模式。通过首次订购的特征值敏感性分析,使用特征值基因座进行各种电动机参数和稳定性研究的敏感性。

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