Researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL), along with experts from Toyota, Magna, PlastiComp, Autodesk, the University of Illinois, Purdue University and Virginia Tech, have created software tools that successfully predict the fiber orientation and length distribution of complex carbon fiber thermoplastic parts for automotive applications.

Lower cost, lighter weight materials are needed for improved fuel efficiency. By model year 2025, U.S. regulations mandate that the average fuel economy standard meets 54.5 miles per gallon, a 60 percent increase over the 35.5 mpg required now. While stronger and lighter than steel, carbon fiber composites are relatively expensive. For widespread adoption to occur, new, economical composites that meet mechanical and safety requirements — such as long carbon fiber-reinforced thermoplastic resins like polypropylene and nylon — need to be developed.  This approach, according to PNNL, should accelerate the development of more economical carbon fiber materials.

As PNNL explains, current development processes of composite components require carmakers to build molds, mold parts, and test them. It’s a long, arduous process, slowing the advance of new, more cost-effective carbon fiber composites in automobiles. Using the engineering software validated by the PNNL-lead team, manufacturers will be able to “see” what the structural characteristics of proposed carbon fiber composites designs would be like before it’s molded. The tools allow manufacturers and auto part designers to experiment and explore new ideas at a much faster rate.

To predict fiber orientation and fiber length distribution in molded components, the team leveraged Autodesk Moldflow software, based on models originally developed by University of Illinois professor Charles Tucker and coworkers. With guidance from Toyota, PlastiComp, and Magna and materials from PlastiComp, long carbon fiber components were molded and the fibers extracted for measurement by Purdue University and Virginia Tech.

PNNL then compared the predicted properties from the simulation software to the test results of the molded fibers to validate the accuracy of the software and models. PNNL found the software tool successfully predicted fiber length distribution in all cases and fiber orientation in 88 percent of cases.

Additionally, as part of the project, PNNL worked with Magna and Toyota to analyze the performance gains and costs of long carbon fiber components versus standard steel and fiberglass composites. PNNL found the carbon fiber reinforced polymer composite technology studied could reduce the weight of automobile body systems by over 20 percent. However, production costs of carbon fiber components can be 10 times higher than those of steel. The optimization of processes and structures using predictive tools could significantly reduce production costs, paving the way for greater use of carbon fiber in automobiles.