Evolutionary Optimization of a Motorcycle Traction Control System Based on Fuzzy Logic


Braking and traction control systems are fundamental vehicle safety equipments. The primary ones stop the wheels from locking, maintaining, when doable, the handling of the vehicle beneath emergency braking. Whereas the second ones management wheel slip when excessive torque is applied on driving wheels. The aim of this study is to develop and implement a replacement control model of a traction management system to be put in on a bike, regulating the slip in traction and improving dynamic behavior of 2-wheeled vehicles. This paper presents a unique traction management algorithm, which makes use of a fuzzy logic control block. Two ways to form the control block are administrated. In the primary one, the parameters that define the fuzzy logic controller are tuned consistent with experience. In the second one, the parameters are obtained by means of an evolutionary algorithm (EA) so as to style an augmented traction controller. It has been proved that the utilization of EA will improve the fuzzy-logic-primarily based control algorithm, getting better results than those made with the management tuned solely by experience.

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