In-Vehicle Tire Sound Quality Prediction from Tire Noise Data 2007-01-2253
Tire Sound Quality is an increasingly important factor for customer satisfaction within the replacement tire market. Manufacturers who compete in this market must be capable of predicting a driver's perception of tire noise as early in the design process as possible in order to reduce development time and cost. Typical methods for tire noise evaluation each have limitations that require improvement. Subjective in-vehicle testing is generally an effective method for predicting driver perception, but it is vehicle specific, time consuming, and requires complete sets of tires for testing. Traditional single tire (component level) test methods measure overall tire noise levels, but do not always provide information relevant to a driver's perception of tire noise in a vehicle. Detailed noise path analysis techniques are cost prohibitive due to the amount of time and effort required to characterize each vehicle and the multitude of vehicles that exist. Replacement tires must be designed to work well when fitted to multiple vehicle platforms. Because of this, there exists a need for a robust sound quality based test that can be performed at the component level and used to predict a driver's perception of noise that is relevant for entire classes of vehicles. In order to meet these requirements, replacement market tire manufacturers must implement innovative technologies and improve their processes by employing the following strategies:
Develop better component test procedures
Implement a simplified procedure for measuring vehicle sensitivity functions
Define metrics for in-vehicle tire sound quality that correlate with subjective perception
This paper describes the experimental activities conducted by a major tire manufacturer to achieve these objectives. All three strategies listed above must be integrated together such that the component level test results can be filtered based on the vehicle sensitivity function and then quantified utilizing a sound quality metric. Each test method must be as efficient as possible to reduce testing time and cost. Several known procedures were compared and the methods that best satisfied the given objectives are described within this paper.