Model Based System Testing Approach for Efficient Testing of EPS Systems

Model Based System Testing (MBST) can be defined as the discipline combining physical testing and simulation models with the aim to study, identify, validate and improve the behavior of multiphysical and mechatronic systems. One of its benefits is related to the use of simulation models to improve or accelerate the testing process, using well known procedures, such as optimal sensor and excitation placement, but also more recent methodologies, such as virtual testing or human-in-the-loop interactions. In this context, these MBST methodologies can be used for Electrical power steering (EPS) system testing, to allow for better characterization of the overall system and subsystems, and to better identify and model nonlinearities. This paper presents a testing and simulation combined approach used to optimally define test conditions, such as sensor placement, test boundary conditions, excitation inputs and how they affect parameter identification.