In-Vehicle Identification of an Induction Machine Model for Operational Torque Prediction

The importance of electric vehicles to the automotive sector has been growing fast over the last years. These vehicles feature novel electric powertrains, designed and sized using model-based engineering approaches. In this context, they would benefit from knowledge on operational torque loads. However, driveline torque loads are very expensive, and often not feasible, to measure in operational conditions. Therefore, this paper presents a method to obtain a model-based prediction of the motor torque applied on the driveline during on-the-road vehicle operation. As such, it aims to close the loop of model-based system engineering. The method is developed for the case of an induction machine as traction motor. In contrast to classical parameter identification tests requiring a motor test bench, the experimental test campaign for the model parameter identification can be performed on a chassis dynamometer, with the E-powertrain mounted in the vehicle.