Driving Innovation in Collegiate Racing: A Case Study on Michigan Baja Racing and Altair HyperWorks™ Suite

• Robots - Autonomous Guided Vehicles (AGV)
• Sensors - Autonomous Driving Sensors

• Automotive

• Product Research & Development

• Smart Parking
• Vehicle Performance Monitoring

• Testing & Certification

Michigan Baja Racing (MBR), a collegiate race team participating in the North American Baja SAE intercollegiate competition, faced a significant challenge in designing a competitive off-road race car. The team had to create a vehicle that was light and nimble enough for acceleration, maneuverability, and hill climb events, but also durable enough to withstand the suspension and traction (S&T) and endurance race. The design process required innovative solutions to reduce mass while maintaining strength, ensuring the vehicle could travel as fast as possible for as long as possible. Adding to the complexity of the challenge, the team had a tight six-month timeline from rulebook to manufactured vehicle, leaving little room for prototyping and testing and no room for critical design mistakes.

Michigan Baja Racing (MBR) is a collegiate race team that competes in the North American Baja SAE intercollegiate competition. Each year, the team designs, builds, and tests a new single-seater off-road race car from scratch to compete against hundreds of other teams across the United States. The competition consists of a design presentation and other static events, as well as dynamic events including acceleration, maneuverability, hill climb, suspension and traction (S&T), and a four-hour endurance race. The team is tasked with finding innovative solutions to design challenges within a tight six-month timeline.

To overcome these challenges, MBR leveraged the Altair HyperWorks™ suite. Altair HyperMesh™ was used as the default preprocessor, with support from Altair HyperCrash™ to set up crash scenarios, and Altair HyperView™ was used to view the results. Linear static analysis via Altair OptiStruct™ was run on every component as a baseline for stress and stiffness calculations. Loads were collected from strain gauge testing, predicted g-loading, and comparisons with prior year designs. Nonlinear quasi-static analysis from OptiStruct was used in suspension link design to derive reactionary forces from forced displacement. This allowed MBR to predict the forces at the link yields, plastically deforms, fractures, and the failure location. Full vehicle dynamic crash simulation via Altair Radioss™ was run on the computing cluster at the University of Michigan to evaluate the current crashworthiness of the car in a frontal, side-impact, and roll-over situation. Preliminary drag calculations of the roll cage were calculated with Altair AcuSolve™, driving the design towards a more aerodynamic shape rather than a lightweight one.

• The use of the Altair HyperWorks™ suite provided Michigan Baja Racing with a competitive edge in the North American Baja SAE intercollegiate competition. The suite's reliable analysis and technical support allowed the team to rapidly prototype multiple designs and test them virtually, resulting in a lightweight, durable, and nimble vehicle. The vehicle's performance was within 5% of the predictions made using Altair’s software, demonstrating the accuracy and reliability of the suite. The team's vehicle was one of the lightest in the competition and achieved podium finishes in acceleration and hill climb events. Furthermore, the vehicle had little to no failures at competition and there were no major structural failures in the 2019 season, attesting to the durability of the design.

• The HyperWorks suite saved MBR significant design time
• The result was a lightweight product designed in less than a week
• The vehicle's behavior was within 5% of what was predicted with Altair’s software