Experimental Evaluation of anti-Lock Braking System Performance on Rough Road

To prevent accidents, the vehicles have to be designed for stopping at shortest distance on braking without losing control. Still researchers are studying on advances in Anti-Lock Braking System (ABS) for different road conditions. From the investigation, it is found that the ABS performance on rough road surface decreases because of lack of predictability in road surfaces. The performance can be enhanced in rough road by controlling the suspension and using proper intelligent prediction algorithm. For this, Artificial Neural Network (ANN) is used to generate the road surface. ANN is useful for training the different road surfaces and trained data is used for faster response and reducing stopping distance. For simplicity purpose, a quarter car planar model was considered and results of simulation are validated with experimental results. An experimental test rig is developed for testing ABS on flat and rough road surface. The results obtained from experimental and theoretical are approximately same which shows intelligent algorithms are more beneficial.