Optimization of tuned mass damper parameters for axle whine mitigation

Vehicle sound quality is crucial in the modern automotive industry due to its impact on quality perception and customer satisfaction. Rear axle whine, a significant noise, vibration and harshness (NVH) concern, originates from the transmission error of hypoid gears in the rear differential and is amplified when the excitation frequency aligns with driveline structural modes, transmitting tonal noise into the cabin. Tuned mass damper (TMD) is an effective countermeasure to mitigate the axle whine error state. However, defining optimal TMD properties is challenging, as distinct configurations impact the system's dynamic behavior differently. This work proposes an automated process using response surface models (RSMs) in Esteco's modeFRONTIER to evaluate multiple TMD configurations based on differential housing vibration, a key axle whine metric. A finite element model of the drivetrain, with a spring-mass TMD representation, was used to train and validate the RSMs, enabling efficient and accurate predictions of the performance of multiple configurations. The TMD's mass, stiffness, and position along the driveshaft were used as design parameters, while the differential housing displacement was defined as the performance metric. Case studies demonstrate the effectiveness of the automated process in minimizing rear differential vibration, contributing to an efficient NVH design of driveline systems.