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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.

The Braking System is the most crucial part of the racing vehicle. There is no doubt, that if only one minority failure in the braking system took place, this would be more than enough reason to cause the racing team disqualification from the competition. Time is the main and the most important criteria for any racing competition; on the other hand the formula student “FS UK SAE” competition care the most about developing the automotive engineering sense in the students by putting them under strict rules normally taken from the original version “formula 1” to encourage their creativity to reach the optimum performance under these strict rules. One of the most important rules is “No Braking by wire”, and the obvious consequences are more stopping distance and time. Braking distance is a critical facture in achieving racing success in a competitive domain.