Estimation of the Clutch Characteristic Map for an Automated Wet Friction Clutch Transmission

2016-01-1113

04/05/2016

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
Higher demands on comfort and efficiency require a continuous improvement of the shift process. During the launch and shift process the clutch control is used to get a smooth and efficient behavior. In this short time of acting the shifting behavior can be rated. Many control concepts use a clutch characteristic to calculate the actuator signal based on the clutch torque. Therefore, a high quality of this characteristic is necessary. Because of the dynamic process during clutch engagement the clutch characteristic needs further information to reach a high accuracy for the control algorithm. In this paper an existing clutch torque characteristic is extended to a characteristic map where the clutch torque becomes a function of the current actuator signal of the clutch and the clutch slip. The extension of the torque characteristic describes the slip based dependencies, e.g. the friction coefficient. The model of the characteristic map consists of the multiplication of two separate functions in these two dimensions. The parameters of this model are estimated using different identification algorithms, in this case a non-linear recursive and a non-recursive identification algorithm. Both estimation algorithms result in a characteristic map of the clutch behavior. A further advantage of the presented approach is the normalization during the estimation process of the slip-based function with the cost function. Thus, the original torque characteristic can be used as fallback if the identification of the slip-based part still need reference data to converge or shows an implausible behavior.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-1113
Pages
12
Citation
Arndt, T., Tarasow, A., Bohn, C., Wachsmuth, G. et al., "Estimation of the Clutch Characteristic Map for an Automated Wet Friction Clutch Transmission," SAE Technical Paper 2016-01-1113, 2016, https://doi.org/10.4271/2016-01-1113.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-1113
Content Type
Technical Paper
Language
English