DESIGN OF MICROCONTROLLER BASED NEO BLITS AUTOMATIC COOLING SYSTEM WITH FUZZY LOGIC METHOD
Abstract
ABSTRACT
In this final project, a prototype of an automatic cooling system for the Neo Blits car has been designed. The cooling prototype is made with an iron pipe measuring 15 cm in diameter x 30 cm in length with the constituent components of the system, namely the DS18B20 temperature sensor, IBT-2 Motor Driver, Arduino Mega 2560, Peltier and DC 12 V fan. The control method used is the Fuzzy Logic controller. The system works when the working temperature of the electric motor is more than 500C or more than the set point, and as a heat model the temperature of the electric motor that is running is used an air heater (Heater). At first the system works, the sensor will read the temperature value of the electric motor, this temperature value will then be sent to the controller to be processed by the Fuzzy Logic controller algorithm. The output of this Fuzzy Logic controller is the PWM value which is used to adjust the input voltage which will be used to adjust the input voltage for the Peltier and DC fans. The final result is that the working temperature of the electric motor can be maintained at a temperature of 500C according to the set point value. On testing. In the fuzzy logic controlling method, the results of the overall test using the fuzzy logic method in testing at the 500C set point are rise time1 = 75 seconds, overshoot = 0.38%, settling time1 = 25 seconds. In the 51oC set point increase test, the rise time2 = 15 seconds, overshoot = 0.62%, settling time2 = 10 seconds. In a test with a change in the set point at 510C, it is rise time3 = 33 seconds, overshoot = 0.12%, settling time3 = 12 seconds. Testing with a change in the set point at 500C is rise time4 = 57 seconds, overshoot = 0.11%, settling time4 = 34 seconds. The system can maintain the temperature at a given set point value of 50oC from each test which shows that the temperature control system on the prototype of this automatic cooling system is working well.
References
[2] Cahyadi, Suprijadi, S. and Siswanto, A. (2018) ‘Kendali Kecepatan Putaran Motor Kipas Untuk Pendingin Minuman Menggunakan Metode Fuzzy Logic Control Berbasis Mikrokontroller Atmega 328’, Jurnal Ciastech, (September), pp. 591–600.
[3] Nasution, H., Nasution, K. A. and Dahlan, A. A. (2012) ‘Performansi Sistem Pendingin Kendaraan Dengan Variasi Putaran , Temperatur Setting dan Beban Pendingin’, (1999).
[4] Novianto, R. (2016) ‘Pemodelan dan Analisis Kendali Suhu Ruangan dengan Logika Fuzzy Menggunakan MATLAB’.
[5] Suryoputro, R. et al. (2019) ‘Optimasi Smart Peltier Cooler Menggunakan Fuzzy C-Means’, 6(2), pp. 9208–9218.
[6] Tasidjawa, A. F., Saputro, I. P. and Suwanto, T. C. (no date) ‘Penerapan Fuzzy Logic Tsukamoto Untuk Penentuan’, (0431), pp. 42–48.
[7] Tasidjawa, A. F., Saputro, I. P. and Suwanto, T. C. (no date) ‘Penerapan Fuzzy Logic Tsukamoto Untuk Penentuan’, (0431), pp. 42–48.
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