Cavitation Prediction in Automotive Torque Converters

As automotive torque converters decrease in both diameter and axial length, the effects of cavitation in the torque converter becomes increasingly important on noise, efficiency, and performance goals. Therefore, a cavitation prediction technique is developed in this investigation. In a previous investigation it was shown that cavitation is effected by inlet temperature, charge pressure, and K-factor. The prediction technique is devolved to encompass these variables. A dimensional analysis using the power product method is performed with all relevant variables. The nearfield acoustical cavitation detection technique, discussed in the previous investigation, is used to obtain experimental results from a torque converter test lab. The test matrix for the experimental results was constructed to include effects from inlet temperature, charge pressure, and K-factor. The data obtained experimentally is used to curve fit the results found through the power product method. The resulting equation can be used to predict the onset of cavitation within ± 78 RPM. The results of the dimensionless groups found here are compared to previous dimensional groups. It is shown that previous results do not predict the onset of cavitation as well as the method developed here for variations in inlet temperature, charge pressure, and K-factor. The prediction tool can be used to find the onset of cavitation for similar design torque converters by knowing just the K-factor of the converter. This is useful when developing a new converter using computational fluid dynamic models, because the K-factor is typically known.