Racecar Optimization and Tradeoff Analysis in a Parallel Computing Environment

In this paper, we present an approach to the optimization of a racecar using vehicle dynamics simulation in a parallel-computing environment. The use of vehicle dynamics simulations in the automotive and auto racing industries is widespread. Complex vehicle simulations can include hundreds of parameters and be very computationally expensive to perform. This limits the number of design configurations that can be considered within a reasonable time, preventing thorough exploration of the design space. It also limits the usefulness of these simulations during the course of a race weekend when time is of the essence. In this paper, we present results from work to overcome this problem. Our results focus on determining the Pareto optimal designs for a vehicle model with three design variables running simulated races around corners of different radii.