Evolution of Fuzzy Logic in Anti-Lock Braking System: A Technical Review

Authors

  • Rahul Pandey
  • Romit Kanabar
  • Rahul Padmakumar
  • Venugopal P
  • Ankamma Rao

Keywords:

ABS, fuzzy logic, neural optimizers, test benches, road conditions, Genetic Algorithms.

Abstract

Over the past decade there have been so many technological advancements and developments in the automotive sector, especially in the field of safety systems and automobile design. Many new systems have been developed that mainly focus on improving the safety and reliability of vehicles. This paper is a review paper that briefs about the journey of braking systems in automobiles and how the systems have become smarter, intelligent, robust and reliable. Each section of the paper focuses on a decade of braking system journey. Anti-lock braking systems, or ABS for short, are a popular safety feature that is becoming increasingly common. Bosch invented anti-lock brakes in the 1930s, and they have been standard on most cars since the 1970s. Anti-lock brakes operate by applying hydraulic pressure to your car's wheels to prevent them from locking up while braking, which can cause skidding and loss of control. The antilock braking system (ABS) which revolutionized the braking industry has been focused upon, different techniques after the development of ABS which further improvised the ABS by enhancing its performance has been focused upon. Different test benches and simulation methods used in the past have been covered that lead to the development of modern-day ABS systems. Over 3 decades of the journey from braking systems which was later transformed into anti-lock braking systems and modern-day fuzzy logic-based ABS and neural optimizer based braking systems have been described along with the results of each paper.

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Published

2022-06-12

How to Cite

Rahul Pandey, Romit Kanabar, Rahul Padmakumar, Venugopal P, & Ankamma Rao. (2022). Evolution of Fuzzy Logic in Anti-Lock Braking System: A Technical Review. International Journal of Progressive Research in Science and Engineering, 3(6), 16–34. Retrieved from https://journals.grdpublications.com/index.php/ijprse/article/view/614

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