ADRC and IFOC Control of a Sensorless Induction Motor Driven by a Multilevel Converter Using SVM Approach and PV Generators

4区 工程技术 Q1 Mathematics Mathematical Problems in Engineering Pub Date : 2024-04-15 DOI:10.1155/2024/6183332
Abdellah Oukassi, Oumaymah Elamri, Zakaria Boulghasoul
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Abstract

This paper offers a system for an electric vehicle. It consists of digitally controlling an induction motor without using a speed sensor. The machine is powered by a five-level cascading H-bridge inverter. The SVM control principle is used to manage the status of the five-level inverter; this removes harmonics. The H-bridge inverter converter is powered by photovoltaic sources via a serial converter, using the maximum power point tracker control principle. This structure can also reduce shading losses. In the absence of a mechanical sensor, a dynamic model of the asynchronous machine is utilized with the state variables defined in the stator reference frame. The state vector consists of the components of the rotor flux and stator current. The article provides a comparison of two methods widely used on an induction motor drive. The adaptive model-reference system method and Luenberger observer are evaluated using an active control strategy to reject disturbances to minimize the impact of disturbances. The operating principles of each method are described, and the mathematical models of training systems are developed. Both methods provide a promise for high-speed estimate applications in simulation environments. The simulation results obtained show the correct operation of both observers. Perfect decoupling between the velocity and flow control loops is observed, taking into account any disturbances that may affect the system.
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使用 SVM 方法和光伏发电机对多电平转换器驱动的无传感器感应电机进行 ADRC 和 IFOC 控制
本文提供了一种电动汽车系统。该系统包括在不使用速度传感器的情况下对感应电机进行数字控制。机器由五级级联 H 桥逆变器供电。SVM 控制原理用于管理五级逆变器的状态,从而消除谐波。H 桥逆变器采用最大功率点跟踪器控制原理,通过串行转换器为光伏源供电。这种结构还可以减少遮光损失。在没有机械传感器的情况下,利用异步机的动态模型,在定子参考帧中定义状态变量。状态向量由转子磁通和定子电流的分量组成。文章对感应电机驱动中广泛使用的两种方法进行了比较。通过使用主动控制策略来拒绝干扰,从而将干扰的影响降至最低,对自适应模型参考系统方法和卢恩贝格尔观测器进行了评估。介绍了每种方法的工作原理,并建立了训练系统的数学模型。这两种方法为模拟环境中的高速估计应用提供了希望。仿真结果表明,两种观测器都能正确运行。考虑到可能影响系统的任何干扰,速度和流量控制环路之间实现了完美的解耦。
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来源期刊
Mathematical Problems in Engineering
Mathematical Problems in Engineering 工程技术-工程:综合
CiteScore
4.00
自引率
0.00%
发文量
2853
审稿时长
4.2 months
期刊介绍: Mathematical Problems in Engineering is a broad-based journal which publishes articles of interest in all engineering disciplines. Mathematical Problems in Engineering publishes results of rigorous engineering research carried out using mathematical tools. Contributions containing formulations or results related to applications are also encouraged. The primary aim of Mathematical Problems in Engineering is rapid publication and dissemination of important mathematical work which has relevance to engineering. All areas of engineering are within the scope of the journal. In particular, aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, industrial engineering and manufacturing systems, and mechanical engineering are of interest. Mathematical work of interest includes, but is not limited to, ordinary and partial differential equations, stochastic processes, calculus of variations, and nonlinear analysis.
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