Wheel slip ratio regulation for investigating the vehicle's dynamic behavior during braking and steering input

Abstract

In this study, the vehicle's dynamic behavior during braking and steering input is investigated by considering the quarter-car model. The case study for this research is a Sport-Utility Vehicle (SUV) with the anti-lock braking system (ABS) and nonlinear dynamic equations are considered for it along with Pacejka tire model. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet and icy) during braking is considered as the ABS control strategy. In order to regulating the wheel slip ratio in the optimal value, an intelligent adaptive fuzzy controller that can perform online parameter estimation is considered. In this regard, the proposed controller tracks the optimal wheel slip ratio with changing the condition of the road surface from dry to wet and icy. The adaptive fuzzy controller consists of linguistic base, inference engine and defuzzifier section. The wheel slip ratio and vehicle longitudinal acceleration are selected as inputs of the controller, controller adapter and detector of the road surface condition. During braking and steering input, effective parameters of the wheel that are affected on the vehicle's dynamic behavior and its stability are investigated.

Voltage-Based Braking Controls for Electric Vehicles Considering Weather Condition and Road Slope

“…Here, R is the wheel radius, according to [19]. The slip ratio shows the wheel slip according to the longitudinal velocity of the vehicle and the angular velocity of the wheel [19].…”

“…However, ref. [19] did not consider the road slope, as in our article. The authors of [16] addressed adaptive neural control of ABS incorporated with passive suspension dynamics.…”

“…However, [2] did not consider both weather condition and road slope. In [19], the vehicle's dynamic behavior during braking and steering input was investigated by considering a sport-utility vehicle (SUV) with the ABS. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet, and icy) during braking was considered as the ABS control strategy in [19].…”

“…In [19], the vehicle's dynamic behavior during braking and steering input was investigated by considering a sport-utility vehicle (SUV) with the ABS. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet, and icy) during braking was considered as the ABS control strategy in [19]. The authors of [19] showed that the Pacejka Formula has the most appropriate results for the full range of the wheel slip ratio than other tire models, such as polynomial model.…”

A Study on the Vehicle Antilock System Based on Adaptive Neural Network Sliding Mode Control

“…Feng and Hu [8] designed a discrete fuzzy adaptive PID control algorithm for automotive ABS with a single-wheel model of the vehicle to solve the problems of low skidding rate and poor braking performance of automotive ABS. Amirkhani et al [9] constructed an indirect exponential sliding mode controller based on interval type-2 fuzzy neural network using a quarter-vehicle model in order to improve the performance of vehicle antilock braking system in the face of uncertainty [10]. Considering a quartervehicle model, in order to control the wheel slip ratio at an optimal value, the effective parameters of the wheels that affect the dynamic performance and stability of the vehicle during braking and steering inputs are investigated using an intelligent adaptive fuzzy controller capable of estimating the parameters online.…”