Inertial sensor for an autonomous data acquisition of a novel automotive acoustic measurement system

Tire road noise is the major contributor to traffic noise, which has strong consequences for public health and is known as an environmental problem. The measurements in compliance with international standardized methods to measure tire road noise are expensive, sophisticated to use and are not sufficiently mobile. A new method based on a tire cavity sound measurement system has been developed to analyse the sound pressure in the tire cavity of a passenger vehicle. Since the road surface excites the tire carcass, one can draw conclusions from the tire sound pressure on the tire road noise. However, existing prototypes of the tire cavity sound measurement system have a high investment per unit, a low battery life, and need a lot of manual effort. This paper presents a novel tire cavity sound measurement system, which works automatically and the battery is only used significantly during measurements. The automation is based on a MEMS inertial sensor coupled with a micro-controller, which tracks the accelerations of the wheel and activates or sets the measurement system in standby. Due to the presented method it is now possible to comprehensively and automatically acquire data to identify road segments, which have a strong impact on tire road noise. The identification of such road anomalies has a great benefit for civil engineering departments and road infrastructure operators.