Search Results

Formula Student is a competition held on yearly basis in multiple countries around the world. Students from different universities participate in this competition implementing some of the most sophisticated techniques in design and analysis of Formula Student car performance. In this research a track simulation tool is developed using Python to analyze the effect of different systems on the car performance, and to test the performance of the car on the Autocross track. For simplicity, the car is modeled as point mass in straight roads and corners. Intensive studies were carried out leading to a conclusion that, in some cases, point mass modeling leads to some inaccuracy and in others it provides the solution. Therefore, to achieve simulation accuracy, the point mass model was replaced with four degrees of freedom, or “bicycle”, model counterpart when it couldn’t provide an accurate solution, and the difference between both models results are discussed.

This Application is using Multilayer Perceptron Algorithm to predict the shifting gear timing based on throttle percentage, vehicle velocity, time history and engine speed, in order to enhance the fuel efficiency, shifting time, power loss and driver’s comfort during shifting. The model makes no assumptions about how transmission performance aspects like gears slipping time or the existence of distinct environments like high temperature affects the power train system performance. Instead, the model can learn to model any type of distortion or additive noise in the sensor data; induced in the CAN protocol, through sufficient training data characterization. The network will be implemented on an AMESim model to characterize the operating temperatures and optimize the gearbox design to work with an optimal temperature and advance to this temperature during operation.