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Genetic algorithm-enhanced linear quadratic control for balancing bicopter system with non-zero set point Apriaskar, Esa; Prastiyanto, Dhidik; Utomo, Aryo Baskoro; Manaf, Akhyar Abdillah; Amelia, Ilya; Ilham, Dimas Alfarizky; Bilqis, Viyola Lokahita; Photong, Chonlatee
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.105-113

Abstract

Bicopter is an unmanned aerial vehicle (UAV) with the advantage of saving energy consumption. However, the unique two rotors design presents a challenge in designing a controller that achieves good stability, fast settling time, and the ability to overcome oscillations simultaneously. This article proposes a new control method for bicopter that uses a genetic algorithm optimization approach in the linear quadratic (LQ-GA) control method. The GA is used to search for the best weighting matrix parameters, Q and R, in the Linear Quadratic (LQ) control scheme. The proposed control method was tested on a balancing bicopter test platform with an input in the form of difference in pulse width modulation (PWM) signals for both rotors and an output in the form of roll angle. The control system was evaluated based on the stability of the transient response and the generated control signal. The results of the tests showed that the proposed LQ-GA control method has better stability, faster settling time, and smaller overshoot than the existing PI and standard LQ control methods. Therefore, the proposed LQ-GA control method is the most suitable for use in a balancing bicopter system with a non-zero setpoint.
Experimental investigation of batteries thermal management system using water cooling and thermoelectric cooling techniques Panmuang, Piyapat; Photong, Chonlatee; Soemphol, Chaiyong
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i1.pp201-212

Abstract

The booming electric vehicle industry seeks fast charging solutions to address the safety risks posed by high-power charging, including thermal runaway and other safety issues. This study investigates the impact of combining liquid with thermoelectric cooling on battery thermal management. A series of experiments were conducted using various thermal batteries, liquid flow rates and batteries temperature thermoelectric. The experimental results compared air cooling (AC), water cooling (WC), and thermoelectric cooling (TEC) with different water flow (WF) rate in system and revealed that TEC with WF at 4.0 l/min was the best cooling system. This system can decrease the temperature by about 41-52% from the maximum temperature at discharge rates of 1.0, 1.5, 2.0, 2.5, and 3.0 °C. However, TEC with WF 1.0 and 2.0 l/min can effectively lower the temperature and reduce energy consumption compared to other cooling systems, while still maintaining the battery temperature within appropriate ranges.
An improved surface solar radiation estimation model using integrated meteorological-air quality data Boottarat, Prakaykaew; Bin Salim, Mohd Azli; Photong, Chonlatee
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp347-356

Abstract

This paper proposes an improved high-precision surface solar radiation estimation model using the integration of the local meteorological data and air quality index based linear regression analysis. The proposed model was evaluated and compared to 8 conventional models and one generated by the commonly used PVsyst simulation software. The actual solar radiation, meteorological data and air quality index collected over 10 years (during 2011-2021) from standard measuring stations located at the northern zone of Thailand were used for developing the models while the collected data year 2022 were used for validating the developed models compared to the conventional models. The statistical error estimations in terms of mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) were used for the precision evaluation. The study found that the proposed models achieved better prediction results and the highest precision for monthly estimating of solar radiation than the other models by having the highest estimation precision of 94.70-97.19% compared to 87.53-96.74% of the conventional models and 90.38-95.96% of the PVsyst program.