建议的故障检测算法与优化的混合速度控制

Mariem Ahmed Baba, Mohamed Naoui, A. Abbou, Mohamed Cherkaoui
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引用次数: 0

摘要

无刷直流(BLDC)电机因其高效率和坚固耐用的特性,成为工业应用(尤其是汽车行业)的常见选择。为了检测电机转子的位置,可以使用霍尔效应传感器,但如果这些传感器发生故障,可能会导致系统无法运行。因此,一些研究提出了容错控制 (FTC),以确保在传感器发生故障时仍能继续运行。本文提出了一种利用组合函数检测无刷直流电机霍尔效应传感器故障的创新方法。本文提出了一种利用组合函数检测无刷直流电机霍尔效应传感器故障的创新方法。对于所研究的无刷直流电机的速度控制,采用了混合自适应神经模糊推理控制(ANFIS)。此外,由于采用了定义明确的故障检测算法,所采用的 FTC 信号重建技术得到了改进,从而在其中一个传感器出现故障时仍能实现电机启动。为测试所用方法的有效性,对每个传感器故障情况都给出了仿真结果。
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Proposed Fault Detection Algorithm with Optimized Hybrid Speed Control
The Brushless DC (BLDC) motor is a common choice for industrial applications, particularly in the automotive sector, owing to its high efficiency and robust capabilities. To detect the position of the motor rotor, hall-effect sensors can be used, but these sensors may prevent the system from operating if they fail. Consequently, fault-tolerant control (FTC) has been proposed in several studies to ensure continuity of operation in the event of sensor failure. This paper proposes an innovative method of fault detection in the hall effect sensor for a BLDC motor using combinatorial functions. This paper proposes an innovative method of hall-effect sensor fault detection for a BLDC motor using combinatorial functions. For the speed control of the BLDC under study, a hybrid adaptive neuro-fuzzy inference control (ANFIS) is implemented. In addition, the FTC signal reconstruction technique adopted has been improved to achieve motor start-up despite a fault in one of the sensors, thanks to well-defined fault detection algorithms. Simulation results are presented for each sensor failure case to test the effectiveness of the method used.
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来源期刊
WSEAS Transactions on Systems and Control
WSEAS Transactions on Systems and Control Mathematics-Control and Optimization
CiteScore
1.80
自引率
0.00%
发文量
49
期刊介绍: WSEAS Transactions on Systems and Control publishes original research papers relating to systems theory and automatic control. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of these particular areas. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with systems theory, dynamical systems, linear and non-linear control, intelligent control, robotics and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.
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