|Reference: McAllister, C.D., Simpson, T.W., Lewis, K., Hacker, K., “Application of Multidisciplinary Design Optimization To Racecar Design and Analysis”, AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 4-6 September 2002, Atlanta, Georgia.|
|Description: The objective of the problem is to determine the racecar configuration that minimizes lap time around a skidpad of constant radius while satisfying a yaw balance constraint. The force and the aerodynamic components of the design optimization problem provide the multidisciplinary setting. Collaborative optimization is used in this problem which includes a system level optimizer as well. The racecar design provides a rich environment in which to apply the multidisciplinary design optimization techniques. Racecar configuration and analyses involves knowledge of aerodynamics, structural mechanics, tire performance, and vehicle dynamics. This information is attained from disciplinary experts who have different opinions and control over the performance of the vehicle. The range of adjustment on the design variables may be limited during the racing season (e.g., center of gravity location), and sanctioning bodies limit the amount of on-track testing that can be conducted.
The racecar model is based on the classic bicycle model of Milliken and Milliken, which has been expanded to include four individual wheels. Equations of motion are written for lateral acceleration, longitudinal acceleration and yaw acceleration. The tires, which may be different for front and rear, are modeled using tabular tire data including representations of nonlinearities such as load sensitivity and slip angle saturation. Wheel loads are calculated based on static load, aerodynamic downforce, and lateral load transfer. Figure 1 illustrates a simplified sketch of the racecar model. There are three primary design variables: roll stiffness distribution (K’), weight distribution (A’), and aerodynamic downforce distribution (C’). All three design variables are normalized quantities between 0 and 1.
|Analysis: The design variables have upper and lower bounds of 0.3 and 0.6, respectively. There are two subsystems in this problem; one is the Force analysis and Aerodynamic analysis.|