Browsing by Author "Balasubramanian, Aswin"

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Application of surrogate optimization routine with clustering technique for optimal design of an induction motor
(2021-08-17) Balasubramanian, Aswin; Martin, Floran; Billah, Md Masum; Osemwinyen, Osaruyi; Belahcen, Anouar
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This paper proposes a new surrogate optimization routine for optimal design of a direct on line (DOL) squirrel cage induction motor. The geometry of the motor is optimized to maximize its electromagnetic efficiency while respecting the constraints, such as output power and power factor. The routine uses the methodologies of Latin-hypercube sampling, a clustering technique and a Box–Behnken design for improving the accuracy of the surrogate model while efficiently utilizing the computational resources. The global search-based particle swarm optimization (PSO) algorithm is used for optimizing the surrogate model and the pattern search algorithm is used for fine-tuning the surrogate optimal solution. The proposed surrogate optimization routine achieved an optimal design with an electromagnetic efficiency of 93.90%, for a 7.5 kW motor. To benchmark the performance of the surrogate optimization routine, a comparative analysis was carried out with a direct optimization routine that uses a finite element method (FEM)-based machine model as a cost function.
Iron Loss Computation in a Synchronous Machine from a Static Field Solution
(2020-03-16) Billah, Md
Sähkötekniikan korkeakoulu | Master's thesis
Owing to the increasing energy demand, a highly efficient synchronous machine can play a crucial role in energy saving by reducing energy consumption. An optimum machine design requires a good estimation of the power losses, particularly the iron loss due to the complexity involved with the accurate loss prediction. The prediction of iron loss in the synchronous machine has drawn massive attraction due to the extensive use in the power stations and other industrial applications. The conventional time-stepping method for iron loss calculation is computationally highly expensive and can be productive as long as the number of computations remains in a respectable range. However, the situation is different when an excessive number of computations are required, such as for machine optimization, which turns this method into unprofitable. The development of fast and computationally efficient static analysis in case of synchronous machine induce a thought of computing the iron loss using this method which can minimize the computation cost and substitute the time consuming traditional loss computation method. Based on this notion, an effective iron loss computation technique was developed from a single static field simulation which is much faster than the conventional time-stepping method and provide a fair accuracy. A two-dimensional Finite Element Method was used, and the model was integrated with the static FEM analysis program in the in-house software FCSMEK. The model was applied to a 12.5 MW salient pole synchronous machine, and the computational accuracy was validated with the conventional time-stepping simulation.
Lamination Fault Detection in the Stator of an Electrical Machine using Flux Injection Method
(2017-05-22) Balasubramanian, Aswin
Sähkötekniikan korkeakoulu | Master's thesis
In this thesis work, a probe was designed and developed for detecting lamination fault in the stator of an 18.5 kW induction machine, based on flux injection method. Two designs were developed based on the stator dimensions of the 18.5 kW induction machine and they were compared by analyzing those designs analytically in Matlab to implement the most viable design for detecting lamination failure in the machine. The injection probe for analyzing the lamination failure was demonstrated for two separate cases; Initially, lamination failure in a test stack was studied through experimentation by operating the probe at various range of frequencies and flux densities to select an optimal point of operation of the probe and then it was compared with the simulations in FEMM. Later, the experiments and simulations were done on the 18.5 kW induction machine at selected operating point from previous case to study the effect of fault on the probe. The simulations show a promising result for implementing this method for detecting the lamination failure in machine at higher frequencies. However, the results obtained from experiment were affected due to various inaccuracies caused during the construction of the probe. When the flux injection probes are manufactured with industrial standards, the factors causing these inaccuracies can be eliminated making the new flux injection method more reliable for detecting the lamination failure in an electrical machine.
Uncertainty Quantification of Input Parameters in a 2D Finite-Element Model for Broken Rotor Bar in an Induction Machine
(2022-09) Billah, Md Masum; Martin, Floran; Belahcen, Anouar; Balasubramanian, Aswin; Vaimann, Toomas; Sobra, Jan
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In this article, a forward uncertainty propagation method is presented for a 2-D finite-element (FE) model in an induction machine. This method is applied to quantify the uncertainty of input parameters, for example, dimensions and material properties, and demonstrate their variability effect on harmonics related to the broken rotor bar (BRB) faults. To show the most influential input parameters in the case of BRB harmonics, a global sensitivity analysis is performed from the polynomial chaos expansion (PCE) approximation of the FE model. The results of this study indicate that BRB harmonics are highly sensitive to stator inner diameter, rotor outer diameter, rotor bar conductivity, and core materials. Moreover, the combined variability of these sensitive input parameters can attenuate the amplitude of the BRB harmonics 30%-90% compared to the simulation results at nominal values of input parameters and closely match with measurement results.