Engine Simulation Model for a Formula SAE Race Car: Applied Design, Development, Correlation and Optimization

Abstract: This report is the result of a one year project to provide Monash Motorsports FSAE team with vital predictions regarding how the 2011 450 CC KTM SX-F engine would respond to planned reconstructions and how to optimise different parts of the engine. The phases of operation have been: Learning the software, building the engine, confirming the trustworthiness of the results, rebuilding the engine to predict future results, optimising the simulation and finally providing Monash Motorsport with results and recommendations. The entire engine has been required to be fully defined to be able to run proper simulations. This includes: intake system, engine, exhaust system, physical and environmental properties and also combustion and other sub-models. There were three options to obtain the required data. Either by the engine manufacturer (KTM), manually measuring or using values from example engines included in the simulation software. All three options have been used depending on availability, the time it takes to get hold of topical data and the reliability of the source. By building the engine in the software and simulating the planned changes one step ahead of the team, the simulations have served part of their purpose to work as guidelines to shortening the time of optimisation.

Before approaching the real task the stock engine was created, tested and confirmed to work properly in the simulation. By doing so credibility was added to the simulation which are most important if the simulation predictions was to be accepted as guidelines. The stock engine worked as reference and the dynamometer results was used as benchmark together with results from KTM while building the engine. As a next step the simulation engine was upgraded to the geometry of the final design including components not yet created for the real engine. By doing so the simulation engine could take the role of reference and various simulation tests was performed to map out how each new component affect the engine individually and in conjunction with other related new components. The step of rebuilding the simulation engine to correspond to the future race engine was most crucial to be performed properly hence there was no reference to compare the outcome with but rather being the reference for the real engine.

The results from the final optimisation advocate that a spherical plenum chamber with the volume of 3.89 l should be added to the engine. By doing so a buffer of air is created after the restrictor decreasing the negative impact of the FSAE regulated restrictor. Plenum volume was selected with respect to power/torque, throttle response and packaging. Optimum runner length is 170 mm. This is with respect to the narrow engine speed of 7000 – 11000 rpm the car will be driven during competition. It is also necessary to limit the rpm range of maximum interest since different geometries are optimum within different rpm range. The simulation clearly states that a high discharge coefficient at the diffuser-plenum and plenum-runner ends is to prefer. To do so bell-mouths are beneficial and doe smoothen out the air flow. The components that have been delimitated from this work are thous that will be limited affected by the outcome of the simulations. This includes the air filter, throttle body and different shape of the diffuser including the restrictor. These components have already been carefully investigated and optimised by previous thesis students.
The FSAE regulation had made it extra challenging to optimise the car by allocating points on different criteria hence it is not only being the first car over the finish line that decide if you win or not. Optimum was therefore defined as the best compromise between all the criteria providing points. A total number of approximately 264 simulations were produced in the process which now lays the foundation for Monash Motorsport engine simulation database for future years to come. This report can serve new engine simulation users as a guideline through all steps to a solid foundation of how to design tests, interpret results and optimise an engine.
Ramin Gilani
Sydney, February 1, 2012