Modeling and Evaluation of FSAE Vehicle Cockpit Ergonomics

This paper seeks to define an analytical approach to ergonomic cockpit design for SAE formula style vehicles. The proposed approach uses a data driven driver model based on RAMSIS ergonomic FEA that considers the discomfort, fatigue, and force availability to evaluate cockpit designs that are generated considering defined constraint inputs, such as driver gender and size. The multifunctional model is applicable to various settings of vehicle design and is tuned toward proving performance in operation tasks, as well as setting the groundwork for a multi-variable optimization to determine the preferred driver controls positions for minimum effort and fatigue. In this initial research, RAMSIS ergonomic software is used to generate fatigue and joint discomfort data related to individual joint angles. Anthropometric data is used to calculate the proportional limb lengths from an individual’s gender and height percentile. The optimization function works by selecting a range of driver percentiles and creating random vehicle control positions within the bounds established. From this, each driver is positioned in the car in a random configuration and inverse kinematics calculations evaluate the driver’s limb and joint angles in the driving position. Using the discomfort and fatigue values in the ergonomic dataset, the penalty function evaluates each driving position. The optimization function works towards a minimum discomfort and fatigue rating using provided convergence criteria. Once the acceptance criteria are met, the optimal cockpit position for the desired range of driver percentiles is reported from the position function. A visualization of the optimum driver position for minimum comfort and fatigue is generated from the results of the algorithm, taking into account the constraints and key cockpit features.