Cognition-enhanced quality control for hard finishing processes in automotive gear manufacturing

Low noise levels from electric drives in the interior of battery electric vehicles (BEV) represent an important criterion for the quality perception of vehicle passengers. Current research work focuses on minimizing noise emissions caused by manufacturing deviations in the assembled transmission components of highly integrated electric drives. This paper presents a concept for cognition enhanced control for hard finishing processes in gear manufacturing aiming to optimize the Noise Vibration Harshness (NVH) characteristics of electric drives through quality predictions, adaptive parameter adjustments, and the automatic implementation of corrections in gear grinding machines. The concept is developed and validated using a simulation study with an exemplary use case from the commercial vehicle industry.