Simulasi Pemograman Pengendali PWM Kecepatan dengan Mikrokontroler Arduino berbasis Sensor Ultrasonik HC-SR04 pada Purwarupa Mobil Listrik - Dwi Aji Saputra; Bana Handaga; Marwan Effendy; Dimas Ardiansyah Halim (Accurate: Journal of Mechanical Engineering and Science, 2020)
The braking process is the basis in the making of the PWM speed control system in order for electric cars to be able to stop automatically and increase the driving safety. The usage of an electric motor as a wheel drive for an electric car allows controlling with a microcontroller. Based on the journal about electric motor control, it is necessary to study the use of PWM as a speed controller. The C language as a coding language can be understood by the Arduino microcontroller with the aim of regulating the speed of the electric motor. The research objective was to use the C language programming as a PWM speed controller with the Arduino microcontroller. The methodology used in this study was to modify a remote control car (RC) made as a prototype electric car. The Arduino microcontroller system was installed and programmed in C language as a PWM speed controller. The main sensor tool used was the ultrasonic distance sensor as the microcontroller input data. Direct current (DC) motors on RC cars were regulated with a pulse width modulation (PWM) signal as the output from the Arduino. LCD and buzzer were used as display devices and indicators of safe distances between prototypes and obstructions. The test results showed that the detection distance of the ultrasonic sensor reached 2 cm to 500 meters. Then the acceleration data obtained by pulse width modulation 64 at 1 meter distance, 127 at 3 meter distance, 191 at 4 meter distance, 225 at 5 meter distance and was made in graphic form. In a speed control system, the usage of the Arduino UNO microcontroller was easy to apply and had complete features. The series of speed control systems could be applied to electric cars with the PWM slow reduction criteria in two stages. The PWM lowering process took 1 second after the sensor detects an obstruction object.