Currently, on-board chargers are largely implemented as a two-stage topology consisting of an active front end and a galvanically isolated DC-DC converter. The second stage is used to avoid fault currents that would trigger the residual current device (RCD). This has the disadvantage that the energy flow has to be converted twice using power electronics and in the process power loss occurs in both stages.

The upcoming 6G communication standard offers higher data transfer rates, low latency and optimized energy efficiency and could enable applications such as enable safe autonomous driving, telemedicine and 3D holography. increased path losses and lower environmental scatter at 6G frequencies are Signal transmission over long distances and through obstacles is difficult, which technical challenges, especially in secure real-time transmissions can create.

In their efforts to increase the energy efficiency of their production equipment, companies come up against three implementation hurdles: a lack of transparency regarding energy consumption, the implementation of less effective measures due to the high level of machine complexity and the low motivation of workers to implement the measures in operation. An assistance system that is independent of the equipment can remove these hurdles. The assistance system developed uses machine learning algorithms to analyze the electrical power requirements of the equipment measured by sensors in real time. Based on this, KPIs are calculated, the value of which determines whether a suitable measure is suggested. Workers operate the assistance system via an HMI. This not only displays the measures to be implemented, but also uses gamification elements to incentivize their implementation. The decisive factor here is the eco-score, which summarizes the current energy efficiency of the WZM plant. is summarized.