Crash Testing NASCAR’s Next Gen
Improving crash safety is an ongoing process for NASCAR, not necessarily tied to particular race cars or seasons. The sanctioning body has empowered its safety engineering team, based in Concord, North Carolina, and led by general manager John Patalak, to pursue improvements wherever it identifies a potential safety benefit. Nonetheless, an all-new race car design like the 2022 Next Gen machine for the Cup Series offers an opportunity to consolidate past learnings and introduce new design improvements.
Much of its initial safety development was done remotely by Patalak’s team and chassis designer Dallara. Unlike the outgoing Gen-6 car, the clean sheet Next Gen design deploys a single chassis for all brands, providing new opportunities for passive safety. “A single-source chassis is helpful because we’re not limited to the lowest level of manufacturing or construction technology a team can have,” says Patalak. “An example of this is the bending of round tubes: we are no longer limited to bending at a single point. We now have several bars in the frame that contain continuous rolls. This allows us to make the car stronger without having to add weight.
Digital Design The safety design process began with NASCAR and Dallara working together on CAD-based FEA, iterating different geometries weekly or even daily to optimize deformation just beyond the elastic range. Once the Version 1 CAD prototype chassis assembly was ready, the team commissioned Elemance, based an hour north of Concord and with whom NASCAR had previously worked on modeling the GHBMC human body, to build an Ansys LS-Dyna model from CAD data. The front clip was subjected to near-static load testing After the model was prepared for simulations, NASCAR tapped into its database of historical crashes, examining real-world crash speeds, angles and trajectories to establish boundary conditions for straight frontal impacts, T-bones, rear impacts, roof crush cases and more, which would be used to evaluate and optimize the design. In total, more than 5,000 crash simulations were run.
‘) } // –> ‘) } // –>
Patalak notes that Elemance has also done work designing experiments using LS-Opt, an optimization algorithm that changes material properties, thickness, and geometry iteratively based on set goals. . One example included optimizing the crash impulse for rear impacts while protecting the integrity of the fuel cell. Physical prototype crash tests were mixed in multiple stages throughout the simulation process to validate the model. NASCAR took the rear half of a car to TRC in Ohio and suffered hard wall impacts. He also built two Gen-6 based Next Gen center section mules. These were taken to Ford in Dearborn, Michigan to perform near-static roof crush testing. Above: LS DynaSim was used to model accident scenarios using historical data
By June 2021, the team had gained confidence in the simulation results and it was time to conduct a full right frontal crash test. As has been the case historically, the performance of the area in front of the firewall when subjected to the main direction of the right frontal force (PDOF) became the focus of the full car test. NASCAR’s usual lab at the University of Nebraska-Lincoln was unavailable and an alternate location could not be found in North America due to the demanding 209 mph impact speed and the long test setup time. Above: NASCAR took the rear half of a car to TRC in Ohio and impacted hard walls. Instead, the innovative solution was to autonomously smash a running race car at Talladega Superspeedway in Alabama. “It was the most realistic and easiest solution from a planning perspective, but certainly not from an execution perspective,” admits Patalak, whose team worked with AB Dynamics on testing.
“We started locally at the zMAX Dragway in Concord: a very safe and controlled environment within the walls. Once we were able to get the robots to take off, shift and stop smoothly, we went to Charlotte Motor Speedway where we had more room to shift gears. All of this boosted confidence ahead of Talladega.
Talladega’s configuration consisted of a NASCAR 50th percentile III hybrid male frontal dummy with internal DTS data acquisition. There were dummy sensors, triaxial accelerometers on the chassis as well as external cameras. The team spent two days slowly building the crash test track at Talladega. They first went three-quarters of the way with a last-minute high-speed turn away from the Steel and Foam Energy Reduction Barrier (SAFER) to avoid premature damage to the expensive Next Gen prototype.
“It was a very stressful environment, but they performed for us and we got good car and dummy data, good high-speed video and learned a lot,” Patalak reports. “We did further validation work with our LS-Dyna model in July, August and September, and committed to making some structural modifications to the chassis for crash performance gains. We then repeated the [Talladega] testing in October. “Above: The NASCAR-mandated incident data recorder
The results of earlier human modeling work on driver seating and restraint systems have been carried over into the Next Gen machines. On-board video cameras first introduced in 2018 are also carried over. From 2023, video will be upgraded to a higher frame rate in conjunction with a new Incident Data Recorder (IDR). This comprehensive DAS will have access to CAN data including throttle position, brake pressure, steering angle and engine speed. Data streams through the ECU will be synced and recorded as a crash file along with the video and currently recorded chassis 3-axis acceleration. Additionally, NASCAR is adding its own 20 Hz GPS antenna to cars.
“We already have GPS data through a 5Hz TV telemetry system, but when a car approaches a wall, a lot of things happen in 200ms,” says Patalak. “The higher sampling rate is very important for us from the point of view of the boundary conditions for our simulation work. When trying to figure out the difference between 244 km/h or 260 km/h, these are hard things to answer confidently with 5Hz data.
“The new system also has on-board processing capabilities. We have developed driver injury risk curves for AIS injury levels based on our historical data, taking into account peak acceleration, PDOF, Delta-V (gear change – severity of accident) and the number of events within the accident,” he explains. “The new system will be able to do these calculations in near real time and relay the information to race control. A crash at Daytona could involve 10 or 12 cars, for example, and we have a limited number of response vehicles in accident; the new system is another tool to help us get the right resources to a car as soon as possible.”