Optimization method for drivetrain settings in a calorimeter
Year: 2025
Type: article
Abstract: The optimization of both machine and process efficiency has surged in importance, as it is a key part of the energy transition. This poster addresses the need for enhanced energy efficiency in electromechanical systems by identifying an optimal switching frequency that minimizes total power losses while adhering to the precision constraints of calorimetry. The research aims to determine the optimal switching frequency for a drive system that minimizes power losses in a permanent magnet synchronous motor (PMSM) and drive combination. Measurements are conducted using a precision calorimeter, providing highly accurate power loss data. Obtaining precise measurements using a calorimeter is time-intensive, as each reading requires the system to reach a steady state. To speed up the process, an initial quick sweep of switching frequencies is performed, spanning from low to high frequencies and back, repeated six times to assess power loss variance. The collected data are then used for polynomial fitting, creating a model of power loss as a function of switching frequency. This model supports a specially developed gradient descent algorithm, which tests a reduced number of points and iteratively adjusts the switching frequency by tuning specific parameters to converge on the frequency that minimizes power loss. The experimental results demonstrate the effectiveness of the optimized switching frequency selection. The developed algorithm identifies a switching frequency of 4211 Hz as the optimal frequency, with a minimized total power loss of 1132 W across five tested points. Additionally, experimental tests were conducted with eight points to confirm that the minimum power loss frequency was identified. These tests show that the switching frequency yielding the lowest observed power loss is 3341 Hz, resulting in a total power loss of 1035 W.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930481329
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