In this paper, we present a new optimization method to estimate the parameters and torques of an induction motor (IM). The proposed method is known as the Vortex Search Algorithm (VSA), whose performance is based on the behavior of the vortices created by stirred fluids. This algorithm was compared with other four optimization methods reported in the specialized literature (grasshopper optimization algorithm, particle swarm optimization, salp swarm algorithm and sine cosine algorithm), and its solution quality, precision, and robustness were validated using two test motors. During the tests, we analyzed the minimum error between the estimated values and the values provided by the manufacturer, as well as the global error of each method and their required processing time. The results show that the VSA is an excellent alternative to estimate the parameters of an IM, as it exhibited the best performance when compared to the other optimization methods.

在本文中，我们提出了一种新的优化方法来估计感应电机（IM）的参数和扭矩。所提出的方法称为涡流搜索算法（VSA），其性能基于搅拌流体产生的涡流行为。该算法与专业文献中报道的其他四种优化方法（蚱蜢优化算法、粒子群优化、樽海鞘算法和正余弦算法）进行了比较，并使用两个测试电机验证了其解的质量、精度和鲁棒性。在测试过程中，我们分析了估计值与制造商提供的值之间的最小误差，以及每种方法的全局误差及其所需的处理时间。结果表明，VSA 是估计 IM 参数的绝佳替代方案，因为与其他优化方法相比，它表现出了最佳性能。