High Pressure RTM Process Modeling for Automotive Composite Product Development

2017-26-0175

01/10/2017

Event
Symposium on International Automotive Technology 2017
Authors Abstract
Content
Composite manufacturing in the automotive industry is striving for short cycle times to be competitive with conventional manufacturing methods, while enabling significant weight reductions. High Pressure Resin Transfer Molding (HP-RTM) is becoming one of the processes of choice for composite applications due to its ability to enable high speed part production. In this regard, researchers need to offer differentiated ultra-fast curing resin systems for carbon fiber composites for automotive structural and nonstructural applications to enable Original Equipment Manufacturers (OEMs) to meet their large volume lightweight targets in concert with present day low-carbon footprint legislations. In order to expand applications for composites in the automotive industry it is necessary to optimize all aspects of the production cycle using predictive modeling.
This paper presents the initiatives taken to develop enhanced predictive modeling capabilities including, resin characterization, and understanding of fabric behavior during HP-RTM process simulations. The study presents experimental test cases for automotive composite application development which includes various aspects related to HP-RTM process conditions. The predictions of the simulations are compared with experimental results, and show very encouraging correlation. We propose that the simulation will enable selection of the correct process parameters such as injection pressure, flow-rate and mold temperature leading to short cycle time and to avoid possible defects such as dry spots, fiber movement, wash out, through thickness flow variation etc.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-26-0175
Pages
8
Citation
Siddiqui, M., Koelman, H., and Shembekar, P., "High Pressure RTM Process Modeling for Automotive Composite Product Development," SAE Technical Paper 2017-26-0175, 2017, https://doi.org/10.4271/2017-26-0175.
Additional Details
Publisher
Published
Jan 10, 2017
Product Code
2017-26-0175
Content Type
Technical Paper
Language
English