Translating Metallic Automotive Compents to Advanced Materials

Changes in legislation including the introduction of Euro 6, WLTP and the 2040 legislation in the UK that will ban conventional vehicles, means automotive manufacturers require ways to reduce emissions. Change is also being driven by consumers expecting reduced costs with increased miles per gallon. To achieve both requirements manufacturers are looking to hybridisation, electric vehicles and weight reduction.

Weight reduction will support improved range of electric vehicles; reducing range anxiety and improving uptake. Weight reduction is achieved through redesign and change of material, completed in unison to achieve optimum performance. With the introduction of new manufacturing methods for composite materials, which is reducing costs, is allowing manufacturers to achieve component targets while reducing mass. Using composites brings its own challenges;

1. Lack of material knowledge to fully understand new materials in new applications and associated fatigue and failure modes;
2. Lack of design knowledge to reduce risk of early fatigue/failure;
3. Lack of willingness to change from tried and tested metallic materials.

This project looks to tackle the three inhibitors above and open a new world of lightweight composite components in new applications which will benefit vehicle mass, dynamics, emissions and range.

1. To allow AML and CU to work through the design process with a composite SME supplier (SHAPE Machining (SHM)) to better improve design knowledge;
2. Test the components at Cardiff to correlate back to simulation data and show they meet requirements;
3. Monitor components with internal gauging to understand degradation of components through development testing and feed forward information to future design iterations;

In summary this project aims to develop standardised approaches and methodologies for the translation of a metallic component to a composite material through computational analysis, physical testing and advanced video strain analysis.