Abstract
M.Ing.
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, wheel slip is controlled with ABS, while
wheel slip during acceleration is controlled by an ASR. Since the friction between a
vehicle's tyre and the road surface is a function of wheel slip, there is an optimum wheel
slip value at which the best road holding performance can be achieved. This optimum
wheel slip value will however change with differing road surfaces and vehicle speeds.
Optimising the wheel slip values has several advantages: both vehicle stopping and
acceleration distances can be optimised, vehicle handling during in-turn braking and
acceleration are optimised and tyre wear is reduced. Currently there are various ABS and
ASR systems available, with the common goal of optimising wheel slip. These systems
are however mechanically complex, while the operation of both these systems is usually
triggered when some wheel slip value is exceeded. Differing road surfaces can greatly
influence the effectiveness of these systems. The central theme of this research is the
development of a fuzzy logic control algorithm for vehicle traction control. The control
algorithm is tested with an experimental setup. The operating conditions experienced by
an ABS are closely simulated in order to study the feasibility of fuzzy logic for traction
control. The results obtained indicates the viability of fuzzy logic for wheel slip control.
Confirmation of these results, obtained with the experimental ABS, have to be validated
during vehicle testing. The main goal is to improve the performances of existing traction
control systems and the feasibility of fuzzy controllers in automobile applications.