Knights Racing is a Formula SAE team from the University of Central Florida. Formula SAE is an international competition in which students design and build a race car as well as manufacture the car’s components. During the competition, teams are not only assessed based on vehicle performance but in static events like a business case presentation and engineering design review. This year, our team participated in the Formula SAE Michigan competition located at Michigan International Speedway.
The team used ANSYS Workbench, and with help from ANSYS associates our team expedited the design of several crucial components, particularly the brake rotors, hubs, uprights and pedal box. ANSYS Workbench enabled students to analyze different load cases. For example, we used static structural analysis for the bulk of the brake rotor design. When designing the brake rotors, the interaction between the brake rotor and suspension components was a major priority. ANSYS stood out compared to other simulation programs because it gave us the ability to simulate on a case-by-case basis with invaluable project-specific contact sets. Our team gained valuable insight into the stresses experienced by the entire suspension assembly under an extreme braking cycle. Furthermore, when we analyzed iterations of the brake rotor, we could easily make design changes within the built-in CAD programs, such as ANSYS DesignModeler and ANSYS SpaceClaim.
Since our team was very new to conducting finite element analysis (FEA) using ANSYS simulation, the support ANSYS provided was invaluable. At every step of the way, ANSYS associates provided guidance, which allowed the team to take full advantage of the software. When validating the structural properties of the brake rotors, the team found that the results came within 2 percent of the simulated results. This would not have been possible without the support and tools provided by ANSYS.
As the team comes back together to plan what direction to take with the 2018 vehicle, using ANSYS has been mentioned frequently based on the results of what was a learning year for the team with the software.