Digital twin creation of an electric drivetrain

This study shows an approach for assessing the efficiency of a drive train under different load profiles and different environmental conditions using digital twin (DT) technology. Electric drive trains, crucial components in industrial systems, often face deployment in environments with different load conditions than those encountered during the design and testing phases. Therefore, when faced with orders for deployment in different load scenarios, it becomes imperative to evaluate its performance beforehand. To address this, a DT of the drivetrain is developed based on field data and different assets. Utilizing this DT, predictions are made regarding the drivetrain's output and efficiency under the new load profile. Subsequently, experimental validation was conducted to verify the accuracy of the predictions. The results demonstrate the efficiency of the proposed approach in accurately assessing drivetrain performance under different load conditions, facilitating informed decision-making in deployment scenarios. The digital twin (DT) model is constructed by an analytical model using MATLAB/Simulink, complemented by optimization tools in modeFRONTIER.