Reducing LiDAR Cabin Noise with Damped Elastomers: a Novel Method for Predicting Performance and Durability

Mechanical LiDAR units utilize spinning lasers to scan surrounding areas to enable limited autonomous driving. The motors within the LiDAR modules create noise that can leak into the cabin of a vehicle. Decoupling the module from the body of the vehicle with highly damped elastomers can reduce the acoustic noise in the cabin and improve the driving experience. Damped elastomers work by absorbing the vibrational energy and dispelling it as latent heat, which creates challenges in an unpredictable automotive environment. Throughout the development process with vehicle OEMs and LiDAR ODMs, highly damped elastomers were able to effectively reduce the noise created by the scanning LiDAR modules in a laboratory environment. It was unproven that these elastomers would be as effective in extreme heat, cold, or humid environments. Extensive bench and vehicle tests were conducted, but confidence was low without a model to predict behavior at edge-cases. By creating a unique test method to model the behavior of the elastomers, a predictable pattern of the damping ratio yielded insight into the performance of the elastomer throughout the operating temperature range of the LiDAR module. The test method also provides an objective analysis of elastomer durability when exposed to extreme temperatures and loading conditions for extended periods of time. Confidence in elastomer behavior and life span was restored when no signs of performance degradation were present after 30 simulated years of normal loading conditions at extreme temperatures. The collaborative effort to reduce LiDAR noise in the cabin of the vehicle has yielded practical and theoretical results that can be replicated on other automotive sensors that have spinning motors or make audible noise. With this new model that can predict damping performance and behavior of viscoelastic materials, highly damped elastomers can be confidently used in the automotive space over the predicted lifetime of the vehicle.