In recent years, the use of high-power inverters has become increasingly prevalent in vehicles applications. With the increasing number of electric vehicle models comes the need for efficient and reliable testing methods to ensure the proper functioning of these inverters. One such method is the use of Hardware-in-the-Loop (HiL) environments, where the inverter is connected to a simulated environment to test its performance under various operating conditions. HiL testing allows for faster and more cost-effective testing than traditional methods and provides a safe environment to evaluate the inverter’s response to different scenarios. Further, in such an environment, it is possible to specifically stimulate those system states in which conflicts between the lines arise regarding the ideal system parametrization. By combining HiL testing with design-of-experiments and modelling methods, the propulsion system can hence be optimized in a holistic manner.
In the past, such approaches have been used in conventional powertrain development such as to validate software functions on existing controller hardware or investigate system interactions on an engine or powertrain testbed. In this paper, we demonstrate the possibilities of inverter testing on a Power-HiL (PHiL) environment. In addition to the resulting analogies and differences for the different kinds of drive systems, the advantages and limitations of this testing method will be discussed. The efficient, robust and NVH-optimized operation of an electric drive is to a great extend determined by the level of current ripple generated by the switching of its inverter. Consequently, the optimization of the switching frequency to minimize this ripple has become a crucial aspect of the development process. In this regard, the present study aims to conduct comparative investigations on both an inverter testbed and an E-motor testbed to evaluate and attribute the sources of the current ripple induced in each component as well as the combined system behavior. By doing so, a comprehensive understanding of the ripple characteristics in different testing environments can be achieved, leading to the effective optimization of the electric drive’s performance.
