Abstract
There are many research on electric vehicles to reduce environmental pollution due to vehicles that use fossil fuels. The advantages of using a BLDC motor are high efficiency, high torque, reduced noise, long lifetime, and easy maintenance. Using of BLDC motors in electric vehicles is sometimes not optimal due to varying set points and presence of loads. Then a speed motor is needed to be controlled so the motor can work properly. In this research using the Artificial Neural Network (ANN) method. The ANN on this speed controller is practical as a 3-phase inverter input voltage control so the speed of BLDC motor can match the set point. In the simulation in this research, controlled based ANN is applied to electric buses with large torque, from the simulation it can be seen that Controlled based ANN can work well.
| Original language | English |
|---|---|
| Pages (from-to) | 203-210 |
| Number of pages | 8 |
| Journal | Przeglad Elektrotechniczny |
| Volume | 98 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Keywords
- Artificial Neural Network (ANN)
- Brushless DC Motor (BLDC)
- Electric Vehicle
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