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Induction machine parameter range constraints in genetic algorithm based efficiency estimation techniques

机译:基于遗传算法的遗传算法效率估计技术的归纳机参数范围约束

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Estimation of induction machine equivalent circuit parameters which are commonly used in efficiency estimation and control methods can be effectively achieved by utilizing genetic algorithms (GA). One of the difficulties of using GAs for efficiency estimation is the determination of variable (parameter) constraints (ranges). A wide range of variables can cause unstable outcome. Hence, it is essential to determine an acceptable range for each variable prior to a GA run to produce stable and repeatable results. In this paper, relationships based on nameplate information and a large database of tested induction motors provided by Hydro-Que?bec are proposed to determine acceptable induction motor parameter ranges. The effectiveness and accuracy of the proposed method is validated by testing 4 induction machines of different power ratings.
机译:通过利用遗传算法(GA),可以有效地实现效率估计和控制方法中常用的感应机器等效电路参数。使用气体效率估计的困难之一是测定变量(参数)约束(范围)。广泛的变量可能导致不稳定的结果。因此,必须在GA运行之前确定每个变量的可接受范围,以产生稳定和可重复的结果。本文基于铭牌信息的关系和水力 - 阙提供的测试感应电动机的大型数据库,建议确定可接受的感应电动机参数范围。通过测试不同功率额定值的4个感应机器来验证所提出的方法的有效性和准确性。

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