Predicting Charge Consumption of Electric Vehicles Using Machine Learning

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G. Balaiah, V. P. Dhanasree, M. Jyothi, K. Varun, Darshan Chowhan


Electric cars have to be the destiny approach of transportation in contemporary society, wherein the enterprise is prospering. A brand-new era is recruited every day, where  electric cars are being driven for some reasons like pollution, growing fuel demand, international warming, and the promotion of environmentally-pleasant modes of transportation. Electric vehicles require charging to operate,therefore they use energy. Power consumption fluctuates depending on the road type, driving style, and distance traveled, but we must also include the user managing the vehicle, which affects the power consumption projection. Predictions based on additional data are more accurate than predictions based just on past charge data. We will make predictions based on current occurrences in the area. We will use algorithms to pre-process the data before training it. Taking into account the charging distance and time, the target variable, and the amount of energy consumed. Features such as acceleration, powertrain, and others will be used to study the behavior. We'll use decision trees and logistic regression and train some more algorithms. We will also implement a voting classifier to the ensemble with machine learning algorithms.

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