COLUMBUS, Ohio -- The sound of a race car as it tears around a track reveals not only engine performance, but the driver’s technique and racing team’s strategy, engineers at Ohio State University have found.
They developed a method of computer analysis that “listens” to the pitches of sound coming from a car and extracts valuable information.
The same technique could be used to gauge the performance of any complicated piece of machinery, such as power plant turbines, said Giorgio Rizzoni, associate professor of mechanical engineering and director of Ohio State’s Center for Automotive Research.
Rizzoni conducted this work with Yann Guezennec, also associate professor of mechanical engineering, and graduate student Matthew Barga. Barga presented these findings Nov. 4 in Columbus at a meeting of the Acoustical Society of America.
“Racing has become an extremely technical field,” saidGuezennec, and racing teams use a wealth of sophisticated equipment to analyze the performance of their own cars and their competitors’.
Deciphering useful information from engine noise isn’t easy, Rizzoni explained. “An engine roars at several different pitches simultaneously, much like the harmonics of a musical instrument. The change in pitch as a car whizzes by complicates matters further,” he said.
“The key is to simplify all the noise down to one thing, such as engine RPM, so we can present information that is not directly available,” said Guezennec.
The engineers developed equations to analyze the change in frequency of car sounds over time. At trackside, they can record the sound of a car and calculate on a computer its instantaneous speed and trajectory.
“From those two pieces of information we can figure out most everything we want to know -- the strategy of the team, the engine capability, how the driver shifts gears,” said Guezennec.
For example, the engineers compared recordings of engine sounds from two cars circling the same track, and could tell from the data the difference in transit time around curves between the two cars.
Another characteristic the Ohio State engineers are able to decode is the gear ratio, or difference between the numbers of teeth on the gears of a car. As part of their strategy, racing teams tinker with gears before a race to optimize performance, and keep the final ratios secret.
Previously, the engineers recorded sounds of Ferrari and McLaren-Mercedes racing vehicles at the 1998 Grand Prix of the Republic of San Marno. Their analysis of the sounds as the two vehicles raced along a straight-away and two curves revealed that McLaren-Mercedes had a transit time as much as 0.5 seconds shorter than the Ferrari.
Rizzoni explained that the Navy uses similar technology to identify underwater sounds and monitor machinery on board ships. “We have advanced that technology to obtain more information efficiently and inexpensively,” he said.
Guezennec offered the example of turbines at power plants. “These are huge, expensive pieces of equipment and you can’t take them apart to see how they are performing -- our technology would enable people to do that in a non-intrusive way.”
While this research centered on sounds recorded outside of cars, Rizzoni said the same technique works on sound recorded inside the cockpit of a vehicle. He and his colleagues have performed similar analyses of sounds they obtained from in-car audio/video footage recorded by racing teams during televised events.
In the future, the engineers will use this and other data to compare the performance of a Formula 1 race car to an Indy-style car from CART, Championship Auto Racing Teams, Inc.
“Those cars have never raced on the same track before,” said Rizzoni, “but we can analyze the performance of both and predict which is the better car -- which would win if the two were actually in a race.”
This research was partially funded by the Center for Automotive Research. Barga’s funding came from his graduate student fellowship.
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