Digital Twin of Electric Drivetrain: Approach for Virtual Validation of Different Load Profiles

When an electric drivetrain is ordered for deployment under load conditions different from those encountered during its design and testing phases, it is crucial to evaluate its performance beforehand. However, the experimental validation of the efficiency of an electric drivetrain for a new load profile is time-consuming and costly. This article proposes a digital twin approach to estimate the efficiency of an entire drivetrain for a new load profile—one that has not yet been tested on the physical asset. The parameters of the digital twin are determined through a system-level optimization study, utilizing measured data from the load cycles in the time domain. Utilizing this digital twin, the efficiency of the drivetrain is estimated for a new load profile. Subsequently, experimental validation is conducted. The results demonstrate that the proposed approach is accurately assessing drivetrain performance in terms of efficiency for new load profiles, facilitating informed decision-making in deployment scenarios.