Intelligent anti-lock braking system of electric vehicle with the possibility of mixed braking using fuzzy logic

Umnitsyn, A A; Bakhmutov, S V

doi:10.1088/1742-6596/2061/1/012101

Cited by 6 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The fuzzy logic is an intelligent control used by several researchers to control the automotive ABS systems [14,[36][37][38]. It is introduced in order to tackle the problem of the unknown environmental parameters.…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

Anti-lock braking system control design using a non-linear multi-body dynamic model for a two wheeled vehicle

Khadr,

Houidi,

Romdhane

2024

Eng. Res. Express

View full text Add to dashboard Cite

This paper investigates the design of an Antilock Braking System for a Two Wheeled Vehicle using a non-linear multi-body dynamic model developed by an approach widely used in robotics. The Antilock Braking System is controlled using Matlab/Simulink by applying the Bang-Bang, Proportional-Integral-Derivative and Fuzzy Logic controllers in order to set the longitudinal slip to a desired value. The developed model is used to study the braking performances of a Two Wheeled Vehicle in a straight-line maneuver under different road conditions: dry, wet and a transition between both. The simulation results indicate that the non-linear dynamic model can effectively simulate the behavior of the Two Wheeled Vehicle under emergency braking conditions and with the different types of controllers. The braking performance of the Two Wheeled Vehicle with Antilock Braking System was improved by decreasing the stopping distance, avoiding wheel lockup and therefore contributes to ensure the vehicle control and stability and to reduce the risk of falling. Also, it can be seen through comparative analysis that the Fuzzy logic is one of the most efficient controllers that improve the braking safety.

show abstract

Section: Fuzzy Logic Controllermentioning

confidence: 99%

Anti-lock braking system control design using a non-linear multi-body dynamic model for a two wheeled vehicle

Khadr,

Houidi,

Romdhane

2024

Eng. Res. Express

View full text Add to dashboard Cite

show abstract

“…Vehicle collisions incur significant financial implications, such as missed productivity, medical expenditures, property damage, and legal fees. According to the National Highway Traffic Safety Administration (NHTSA), motor vehicle accidents cost the US economy more than $242 billion in 2010 [3]. Vehicle collisions cause a significant number of injuries and fatalities each year.…”

Section: Introductionmentioning

confidence: 99%

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Yadav,

Goyal

2024

IJACSA

View full text Add to dashboard Cite

Vehicle collisions are a significant problem worldwide, causing injuries, fatalities, and property damage. There are several reasons for the collapse of vehicles such as rash driving, over speeding, less driving skills, increasing number of vehicles, drunk and drive, etc. However, over speeding is one of the critical factors out of all the reasons for vehicle collisions. To address the critical issues, the current article proposes a Fuzzybased algorithm to prevent and control the speed of the vehicle. The major objective of the proposed system is to control the speed of the vehicle for proactive collision avoidance. Deep learning and fuzzy system provide better integrated approach for the controlling of the speed and avoid vehicle collision. Fuzzification of the speed variable provides an advanced or viable solution for speed control. The current research used RNN and other deep learning algorithm to predict the traffic and identify the traffic frequency. The traffic frequency in a timeseries frame provides the frequency of the traffic within a time frame that can be detected by using involvement of IoT.

show abstract

Fuzzy Controllers of Antilock Braking System: A Review

Amirkhani

Molaie

2022

Int. J. Fuzzy Syst.

View full text Add to dashboard Cite

Intelligent anti-lock braking system of electric vehicle with the possibility of mixed braking using fuzzy logic

Cited by 6 publications

References 1 publication

Anti-lock braking system control design using a non-linear multi-body dynamic model for a two wheeled vehicle

Anti-lock braking system control design using a non-linear multi-body dynamic model for a two wheeled vehicle

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Fuzzy Controllers of Antilock Braking System: A Review

Contact Info

Product

Resources

About