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Measurement and Modeling of Perceived Gear Shift Quality for Automatic Transmission Vehicles

Journal Article
2014-01-9125
ISSN: 1946-3995, e-ISSN: 1946-4002
Published May 09, 2014 by SAE International in United States
Measurement and Modeling of Perceived Gear Shift Quality for Automatic Transmission Vehicles
Sector:
Citation: Jeon, B. and Kim, S., "Measurement and Modeling of Perceived Gear Shift Quality for Automatic Transmission Vehicles," SAE Int. J. Passeng. Cars - Mech. Syst. 7(1):423-433, 2014, https://doi.org/10.4271/2014-01-9125.
Language: English

Abstract:

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway). After each event, participants were asked to complete the rating of the four descriptive terms as well as a comprehensive rating on the gear-shifting event. Along with this subjective evaluation, changes of mechanical properties during the event also were recorded. This included shift time and delay, acceleration profile, and jerk. Consequently, a series of statistical analysis revealed the relationship between each subdimension on subjective quality and their associated mechanical properties. Models of comprehensive shift quality, based on the ratings of the subdimensions for driving intentions and speeds, were also developed. The study provided a unique framework to assess subjective driving quality related to mechanical control variables in a multidimensional way, which is applicable to improve the quality of a vehicle.