Enhancing the efficiency of cabin heaters in emergency shelters after earthquakes through an optimized fuzzy controller

Abstract

In just one and half minutes, more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey's southeast on February 6, 2023; thousands of families who barely escaped struggled to survive in the freezing weather. A warm shelter was the most basic requirement of these families. Container buildings are a rapid and easy solution to this issue. However, there is a need for a more effective and safe heating option than a wood fire for these buildings. In this study, cabin heaters, which allow truck drivers to warm up when they park their vehicles to sleep, are specially optimized for emergency shelters after an earthquake. An optimized fuzzy controller was developed to use in such buildings, which allows an air-fuel ratio in the combustion chamber of the cabin heater to be controlled adaptively based on system dynamics to get lower carbon emissions and fuel consumption. The TRNSYS software was used to establish the transient simulation model of a cabin heater with a capacity of 4 kW for a typical 21 m(2) shelter building in Turkey's cold regions. The developed fuzzy controller carried out the heating process of this shelter from the 15th of November to the 15th of March. Instead of using expert knowledge, the Gray Wolf Optimization (GWO) method was applied to optimize the fuzzy controller parameters developed for the cabin heater. With the optimized fuzzy controller, the fuel consumption at the end of the heating season was reduced by an average of 0.2 L/h, and the cabin heater's efficiency increased by more than 13%. Our simulation results show that the intelligent controller we developed could improve diesel fuel combustion efficiency by up to 85%.