Aripriharta, Muhammad Yazid, Nuryani, Muchamad Wahyu Prasetyo, Muhammad Cahyo Bagaskoro, Sasmita Bagus Sang Kesuma, Ika Noer Syamsiana, Pria Eka Reswana, Gwo-Jiun Horng
The development of biomedical devices requires reliable and efficient power management, especially under limited energy sources. This study evaluates the performance of an ultra-low power boost converter using stochastic simulations: Gaussian Analysis, Monte Carlo Simulation, and Worst-Case Analysis. The average output voltage was 4.20 V, with variations from 3.10 V to 4.87 V. Gaussian Analysis showed the highest stability, with the smallest standard deviation of 0.1437 V and the narrowest voltage range (4.80-5.00 ~V), making it the most suitable for precise voltage regulation in biomedical devices. Monte Carlo Simulation revealed moderate stability with wider fluctuations, while Worst-Case Analysis exposed significant deviations under extreme conditions. These results confirm Gaussian Analysis as the best method for ensuring stable voltage, while the other methods help identify variability and risk. Future work includes physical testing, validation with real biological data, and developing adaptive or AI-based controllers to improve voltage stability. © 2025 IEEE.
Universitas Negeri Malang, Department of Electrical Engineering and Informatics, Malang, Indonesia; Institut Teknologi Sepuluh Nopember, Department of Biomedical Engineering, Surabaya, Indonesia; Universitas Sebelas Maret, Department of Physics, Surakarta, Indonesia; State Polytechnic of Malang, Department of Electrical Engineering, Malang, Indonesia; Southern Taiwan University of Science and Technology, Department of Electronics Engineering, Taiwan
