基于超扭转算法的滑模观测器在轮式电机驱动系统PWM电压源逆变器开路故障诊断中的应用

Maliheh Hashemi, M. Stolz, D. Watzenig
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引用次数: 1

摘要

为了提高轮毂电机的可靠性,避免电机、传感器和电机驱动器的故障是至关重要的。然而,在永磁同步电机(pmsm)和采用脉宽调制(PWM)的电压源逆变器(VSI)上形成的轮内电机结构容易受到功率转换器组件故障(如功率开关)的影响。此外,开关设备故障以开路或短路的形式出现。开路故障使各相电压不平衡。本文提出了一种基于超扭转算法的滑模观测器检测逆变器开路故障引起的相电压不平衡的新方法。该观测器与扩展卡尔曼滤波(EKF)相结合,产生了一个鲁棒观测器,可用于工业应用中不可避免的噪声测量条件。此外,仿真观测器采用了基于模型的故障检测算法,使得故障隔离比使用信号处理方法更容易、更可靠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Super-Twisting Algorithm-based Sliding Mode Observer for Open-Circuit Fault Diagnosis in PWM Voltage Source Inverter in an In-Wheel Motor Drive System
To enhance the reliability of in-wheel motors, it is crucial to avoid failures in the motors, sensors and the motor drives. However, in-wheel motor structures formed on permanent magnet synchronous motors (PMSMs) and voltage source inverter (VSI) using pulse-width modulation (PWM) are fragile to power-converter component faults such as power switches. Furthermore, switching device faults accrue in the form of open circuits or short circuits. An open circuit fault imposes phase voltage imbalances to each phase voltage. This paper presents a new approach to detect the imbalanced phase voltage due to the open-circuit fault in the inverters employing a super-twisting algorithm-based sliding mode observer. The combination of proposed observer with the Extended Kalman filter (EKF) results in a robust observer which can be used under the noisy measurement conditions that are unavoidable in industrial applications. In addition, the simulated observer applies a model-based fault detection algorithm, enabling the fault to be isolated more easily and reliably than when using signal processing methods.
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