Perancangan Air Cooling System Motor BLDC 2 kW EV Go-Kart Menggunakan Fuzzy Logic

Martiko, Muhammad Roben (2026) Perancangan Air Cooling System Motor BLDC 2 kW EV Go-Kart Menggunakan Fuzzy Logic. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Motor Brushless Direct Current (BLDC) banyak digunakan sebagai penggerak kendaraan listrik karena memiliki efisiensi dan kerapatan daya yang tinggi. Namun, rugi daya yang muncul selama motor beroperasi berubah menjadi panas, sehingga diperlukan sistem pendingin untuk menekan suhu kerja motor. Penelitian ini merancang air cooling system berbasis logika fuzzy untuk motor QS Motor 2 kW pada go-kart listrik. Sistem menggunakan satu kipas DC 12 V yang kecepatannya diatur oleh mikrokontroler ESP32 berdasarkan pembacaan sensor suhu DS18B20 dan sensor arus INA219, dengan fuzzy control Mamdani dua masukan berupa suhu motor dan error suhu yang menghasilkan nilai PWM kipas secara langsung. Pengujian dilakukan tanpa sistem pendingin, dengan kipas konstan 100 %, serta pada mode fuzzy control dengan setpoint 62 °C, 65 °C, dan 68 °C selama 90 menit. Hasil pengujian menunjukkan bahwa sistem pendingin menurunkan suhu keseimbangan motor dari sekitar 72 °C tanpa kipas menjadi sekitar 60 °C pada duty 100 % konstan. Pada mode fuzzy control, suhu akhir pengujian berturut-turut sebesar 62,77 °C, 64,18 °C, dan 65,60 °C dengan duty cycle maksimum 61,6 %, 41,4 %, dan 24,9 %. Perbedaan duty cycle yang nyata pada setiap setpoint menunjukkan sistem memodulasi kecepatan kipas secara adaptif, bukan sekadar menyalakan atau mematikannya. Berdasarkan pengukuran sensor INA219, fuzzy control menghemat energi kipas sebesar 60,6 %, 81,7 %, dan 90,7 % dibandingkan pengoperasian kipas konstan. Hasil ini menunjukkan bahwa fuzzy control mampu memberikan pendinginan yang menyesuaikan kebutuhan termal sekaligus jauh lebih hemat energi.
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Brushless Direct Current (BLDC) motors are widely used as electric-vehicle drivetrains because of their high efficiency and power density. However, the power losses generated during operation turn into heat, so a cooling system is required to limit the motor operating temperature. This study designs a fuzzy-logic-based air cooling system for a 2 kW QS Motor used in an electric go-kart. The system uses a 12 V DC fan whose speed is regulated by an ESP32 microcontroller based on readings from DS18B20 temperature sensors and an INA219 current sensor, with a two-input Mamdani fuzzy controller that takes motor temperature and temperature error and produces the fan PWM value directly. Testing was carried out without cooling, with the fan held constant at 100 %, and in fuzzy control mode with setpoints of 62 °C, 65 °C, and 68 °C over 90 minutes. The results show that the cooling system reduced the motor equilibrium temperature from about 72 °C without a fan to about 60 °C with the constant fan. In fuzzy control mode the final temperatures were 62.77 °C, 64.18 °C, and 65.60 °C, with maximum duty cycles of 61.6 %, 41.4 %, and 24.9 % respectively. The clearly different duty cycle at each setpoint shows that the system modulates fan speed according to the thermal demand rather than simply switching the fan on and off. Based on INA219 measurements, the fuzzy controller saved 60.6 %, 81.7 %, and 90.7 % of fan energy compared with running the fan constantly at 100 %. These results demonstrate that the fuzzy-based cooling system adapts the cooling effort to the thermal demand while consuming substantially less energy.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	motor BLDC, air cooling system, logika fuzzy, energi kipas, suhu motor, BLDC motor, air cooling system, fuzzy logic, fan energy, motor temperature.
Subjects:	Q Science Q Science > QA Mathematics Q Science > QA Mathematics > QA9.64 Fuzzy logic
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Muhammad Roben Martiko
Date Deposited:	11 Aug 2026 09:37
Last Modified:	11 Aug 2026 09:37
URI:	http://repository.its.ac.id/id/eprint/144317

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