Abstract
In this paper, a 24 V/12 V, 1 kHz high-frequency transformer is designed optimally using genetic algorithm, with the aim of maximizing the power density and efficiency, while maintaining a reasonably small size and low cost. The advantage of designing a transformer using genetic algorithm is that it proposes to the designer a set of optimal designs instead of a single design solution. Such multiple possible solutions allow the user to choose the best fit for the application. But, the main challenges of high frequency transformer design are the number of design parameters, constraints, objectives, and the difficulty in confirming them to a single design methodology. In the proposed work, form factor, current density coefficient, specific volume coefficient, area constant, and Steinmetz constants are chosen as fixed parameters. The free parameters that are varied and optimized in the work are the window utilization factor Ku and flux density. The constraints that define the boundaries of the possible solutions are the maximum temperature rise and efficiency. Utilizing the optimized design data, a model has been simulated for 24 V/12 V, 1 kHz transformer in order to validate the optimized results. A downscaled prototype model of a 24 V/12 V, 1 kHz transformer has been constructed and the results are studied in this paper.
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Tamil Selvi, S., Nandh Kishore, P.T., Ajith, V., Akshaya, M.K., Karuppiah, N. (2022). Design of a High-Frequency Transformer Using Genetic Algorithm. In: Kumar, A., Zurada, J.M., Gunjan, V.K., Balasubramanian, R. (eds) Computational Intelligence in Machine Learning. Lecture Notes in Electrical Engineering, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-16-8484-5_51
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DOI: https://doi.org/10.1007/978-981-16-8484-5_51
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