Statistical characteristics of time series temperature in cooling the electric vehicle controller using the bubble generator

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Catrawedarma IGNB
Fiveriati Anggra
Hamid Abdul

Abstract

The present study examines the thermal performance of the cooling system in an electric vehicle controller. This is achieved by injecting bubbles into the water block at various input airflow rates, using quiet-water and circulating-water cooling fluids. The thermal performance of a system is determined by two factors: the maximum temperature at the controller-water block interface and the corresponding thermal resistance. The temperature distribution is analyzed using statistical moments, the Probability Density Function (PDF), and Kolmogorov entropy to determine the irregularity of the temperature signal. The findings indicate that an increase in airflow rate can result in a decrease in maximum temperature and an enhancement in thermal resistance and flatness of the PDF curve. The maximum temperature decreases by 15.5% when the cooling medium is quiet water when compared to bubble injection at an airflow rate of Qa = 1.5 lpm. The bubble-cooling fluid, with an airflow rate of Qa = 1.5 lpm has a relatively uniform entropy across all thermocouple positions. The presence of low Kolmogorov entropy and low PDF flatness indicate a more stable controller response and fewer extreme spikes. In turn, it has an impact on the increasing system reliability and extending the durability of the controller's electronic components.

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How to Cite
IGNB, C., Anggra, F., & Abdul, H. (2026). Statistical characteristics of time series temperature in cooling the electric vehicle controller using the bubble generator. Communications in Science and Technology, 11(1), 42–52. https://doi.org/10.21924/cst.11.1.2026.1858
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