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Fuzzy control algorithm for automotive traction control systems

Adaptive traction control can greatly enhance the mobility of vehicles on varying road surfaces. Traction control includes antilock braking systems (ABS) and antislip regulation systems (ASR). During braking, wheelslip is controlled with ABS, while wheelslip during acceleration is controlled by an ASR. Since the friction between a vehicle's tyre and the road surface is a function of wheelslip, there is an optimum wheelslip value at which the best road holding performance can be achieved. This optimum wheelslip value will however change with differing road surfaces and vehicle speeds. Optimising the wheelslip values has several advantages: both vehicle stopping and acceleration distances can be optimised, vehicle handling during in-turn braking and acceleration is optimised and tyre wear is reduced. Currently there are various ABS and ASR systems available, with the common goal of optimising wheelslip. These systems are however mechanically complex, while the operation of both these systems are usually triggered when some wheelslip value is exceeded. Differing road surfaces can greatly influence the effectiveness of these systems. The central theme of this paper is the development of a fuzzy logic control algorithm for vehicle traction control. Such a fuzzy logic controller must be able to operate effectively on any road surface, while the mechanical system must be simple. The main goal is to improve the performances of existing traction control systems and the feasibility of fuzzy controllers in automobile applications.