An Power-train model based on the Internet of Things for Thingspeak data tracking and EV performance evaluation

Abstract Electric vehicles (EVs) are becoming essential transportation alternatives due to their pollution-free environment. Researchers use EV power train models to study battery monitoring, range estimations, and vehicle performance. The models are simulated using various drive cycles and use an IoT-based model to send vehicle data to the cloud for communication optimization. The Li-ion battery pack is used for the EV battery model. The model assesses the EV's full powertrain and mathematical model, determining efficiency, motor output, and battery parameters based on torque and speed. Motor torque is crucial for a vehicle's power consumption and mobility. Greater mass but higher SOC consumes more energy over the same distance. A higher wind speed results in 6.369 kWh of energy consumption and a balance of 61.52%. The proposed system tracks user operation data for a remaining distance prediction model based on an electric car battery's state of charge. The simulation outcomes summarize the vehicle's distance traveled and the battery state of charge.