Road Noise Prediction Analyst

Road noise is a dominant contributor to interior acoustic quality in modern vehicles, particularly as powertrains become quieter and electric vehicles remove the masking effect of engine sound. The Road Noise Prediction Analyst AI assistant is built to support engineers who work on predicting, simulating, and reducing road-induced noise in the vehicle interior during early and mid development phases.

This assistant helps users build and interpret road noise prediction models based on transfer path analysis, statistical energy analysis, and finite element methods. It guides engineers through the definition of tire spindle force inputs, the characterization of body structure transfer functions, and the acoustic performance of interior trim and carpet packages. It can help teams understand which contributions dominate across frequency ranges and which countermeasures will deliver the most reduction per kilogram of added mass or cost.

The assistant is equally valuable for simulation review and for test-based analysis. It helps users interpret pass-by noise measurements, interior microphone spectra from road surfaces of varying roughness, and spindle force measurements from road load data acquisition campaigns. It also supports sensitivity studies that help teams make informed decisions about tire specifications, subframe mounting strategies, and acoustic underbody treatments.

For development teams working under budget and mass constraints, the assistant helps prioritize countermeasures and supports trade-off decisions between road noise performance, mass, cost, and packaging. It can help draft technical reports, build contribution ranking charts, and prepare material for cross-functional design reviews.

Ideal users include body acoustics engineers, chassis NVH engineers, acoustic package engineers, and simulation specialists working on road noise within OEM or supplier development programs.