Validation of the electromechanical performance (such as voltage & current profiles, torque and speed profiles, efficiency) and reliability (estimated lifetime) of motion systems is often time-consuming and costly. Assuming a motion product has been validated, additional validation tests need to be put in place in the three following scenarios: a) the same product is going to be used for another mission profile, i.e. within another environment and/or with a different load cycle, b) a single component is replaced by one from another supplier or by a new generation component, or c) a new family member is created: a motion product with partially changed functionality and/or with a rescaled power rating or dimensions.
The objective of DT4V is to develop a framework to minimize the validation cost and time of motion products in the above three scenarios either by doing a full virtual validation or potentially supported by a limited set of dedicated HIL measurements (with specific components as device-under-(specific)test)). The considered motion product is a generic drive train consisting of power electronics, an electric motor and a gearbox, both with their bearings.
Within the DT4V concept of operation, the cost reduction will come from leveraging the digital twin of previously validated motion products in the field, capturing additional Real Operational Conditions (ROC) data and physical insights. As such, knowledge is available and leveraged on with respect to how motion products are being used. The DT4V approach includes exploring the concept of digital siblings for virtual validation. Herein, also unmodelled behaviour and low (e.g. thermal) and high (e.g. peak loading) component interactions impacting the performance are taken into account.
Regarding the lifetime, DT4V will apply the physics-of-failure concept. Herein, the validation will take into account specific intra-component quantities – e.g. local temperatures or material loading – that are known to impact lifetime, and then using these quantities in a forward calculation of the expected lifetime based on literature models.
Within the DT4V approach a trust level assessment method is developed, and if needed, suggestions are done to carry out a limited set of additional HIL measurements to improve the trustworthiness of the virtual validation.
For the project, a fleet of drive trains in the lab will generate the “operational data”: six reference drive trains and two scaled versions; and three additional component testing setups for component testing will be developed for more detailed component model generation. Next to this, the methodology will be developed and validated on industrially relevant cases incl. Flanders Make’s co-creation infrastructure (Evoque) and several Small Validation Cases.