Development of a Digital Twin Software Application for Performance Assessment on Electric Vehicles

The application of a digital twin in automotive industry is a virtual replica of vehicle mechanics, electrics and physical behaviour involving internet, artificial intelligence, machine learning, predictive analysis, simulation tools, 5G, and virtual sensors. This research developed an application digital twin software (ADTS) for the performance assessment on linear to circular economic innovation in automotive industry. ADTS measured electric vehicle (EV) performance respect to time, distance, speed, and battery level utilizing computer program to replicate the processes. The attached ADTS measured data from the electric vehicle on testing at different stages of speed levels A and B. C++ computer language was employed to create simulations that predicted how a product and process performance enhance higher degree of control over memory. ADTS predicted the behaviour of the electric cars for an increase in time leading to increase in the speed but battery level depreciation. At low speed, results of EVs tests cemented the findings of battery voltage consumption level in test A higher than test B at high speed. EVs ran at low speed consumed more energy than that of high speed. As the EVs assumes appreciable speed, the momentum increases, and inertia decreases at less power. DTS drives innovation and predicted EVs against failure complex systems.