Prediction of Voltage Discharge for Electric Tricycle Using Machine Learning Algorithms

The application of Supervised Machine Learning Algorithms for the prediction of Voltage discharge in Electric Tricycles will be explored in this paper. This research investigates the effectiveness of machine learning in predicting the voltage discharge based on the various tricycle operational data. This includes collecting data on discharge voltage, potentially alongside factors like Motor temperature, power, and terrain. Machine learning Algorithms will predict the voltage discharge by training with data. This will ultimately enhance the user experience for electric tricycle riders by providing them with a reliable indication of their remaining range.