Development of an electric active rollcontrol (ARC) algorithm for a SUV

Hwang, Hyunseung; Choi, Seokwoo; Kim, J.; Jang, Kilyong; Yi, Kyongsu

doi:10.1007/s12239-012-0021-8

Cited by 29 publications

(26 citation statements)

References 7 publications

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“…The work herein goes beyond the outcomes in [25]. Moreover, it has the potential to be useful for [13][14][15][16], where no actuator dynamics are considered. In addition, the outcomes achieved in the present research provide a viable alternative to the recent in [22][23][24], by means of a 4-DOF one-half vehicle suspension with two magnetorheological nonlinear dampers.…”

Section: Discussionmentioning

confidence: 99%

“…2 , 1 , and 1 are defined as in (12). Moreover, 16 fuzzy membership functions, ℎ 1 to ℎ 16 , are defined as in (13) and they comply with (14). As a result, the T-S system in (15) was obtained, and the model has to be tested regarding stability in closed-loop.…”

Section: Case Of Studymentioning

confidence: 99%

“…There is reported work related to a half vehicle through the so-called bicycle model [10,11]. Publications include vertical and roll dynamics as reported in Sammier et al [12] and more recently in Jeon et al [13] and Yu et al [14]. Novel reported work has handled onehalf suspension models, where the Bouc-Wen model has been applied for the complete control system, but without considering actuator's dynamics for control law computation [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

Félix-Herrán

Mehdi

Rodríguez-Ortiz

et al. 2015

Mathematical Problems in Engineering

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This work presents a novel semiactive model of a one-half lateral vehicle suspension. The contribution of this research is the inclusion of actuator dynamics (two magnetorheological nonlinear dampers) in the modelling, which means that more realistic outcomes will be obtained, because, in real life, actuators have physical limitations. Takagi-Sugeno (T-S) fuzzy approach is applied to a four-degree-of-freedom (4-DOF) lateral one-half vehicle suspension. The system has two magnetorheological (MR) dampers, whose numerical values come from a real characterization. T-S allows handling suspension’s components and actuator’s nonlinearities (hysteresis, saturation, and viscoplasticity) by means of a set of linear subsystems interconnected via fuzzy membership functions. Due to their linearity, each subsystem can be handled with the very well-known control theory, for example, stability and performance indexes (this is an advantage of the T-S approach). To the best of authors’ knowledge, reported work does not include the aforementioned nonlinearities in the modelling. The generated model is validated via a case of study with simulation results. This research is paramount because it introduces a more accurate (the actuator dynamics, a complex nonlinear subsystem) model that could be applied to one-half vehicle suspension control purposes. Suspension systems are extremely important for passenger comfort and stability in ground vehicles.

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Section: Discussionmentioning

confidence: 99%

Section: Case Of Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

Félix-Herrán

Mehdi

Rodríguez-Ortiz

et al. 2015

Mathematical Problems in Engineering

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“…Korean scholar Jangyeol Yoon et al, by tracking virtual test, designed a unified chassis control system combined with the electronic stability program and the active steering system [4]. K. JEON et al utilized an electric control AARSB, established a single degree freedom dynamic model, and applied the method of sliding mode control to stop a vehicle rollover [5]. Bal´azs Varga et al adopted LQ theory to calculate the required roll control torque of the hydraulically controlled AARSB for light commercial vehicles [6].…”

Section: Introductionmentioning

confidence: 99%

Study on Integrated Control of Active Anti-Roll Steel Bar and Electronic Stability Program Based on Particle Swarm Optimization

Song¹,

Li²,

Sun³

2017

Proceedings of the Second International Conference on Mechanics, Materials and Structural Engineering (ICMMSE 2017)

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Abstract. Since a vehicle is prone to instability and rollover when taking a rapid turning, in this paper, an integrated control strategy of Electronic Stability Program (ESP for short) and active anti-roll steel bar (AARSB for short) is proposed. Then a three-degree-of-freedom vehicle dynamic model is established for rollover prevention and yaw stability control. In order to prevent the rollover and the instability of a vehicle, a linear quadratic (LQ for short) optimal controller is designed. The Particle Swarm Optimization (PSO for short) is adopted to optimize the weight coefficients of the LQ controller. Seven parameters are taken as the assessment criteria to carry out the simulation experiments on the vehicle with integrated control of AARSB and ESP in yaw stability and roll stability. These seven parameters are yaw rate, side-slip angle of mass center, roll angular velocity, roll angle, lateral load transfer ratio, additional yawing moment generated by ESP, and anti-roll moment generated by AARSB. To demonstrate the effects of the integration of AARSB and ESP on rollover prevention and instability control, two time typical simulations are conducted. The simulation results show that the vehicles with integrated control of AARSB and ESP can prevent the rollover and instability of a vehicle effectively. Therefore, with the integrated control, the driving stability of the vehicle is significantly improved.

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“…For instance, Electronic Stability Control systems (ESC) have been originally introduced to stabilize the yaw motion and to prevent over or under steering accidents of modern road vehicles [1][2][3][4][5]. On the other hand, according to the control action, several active rollover prevention systems were proposed such as differential-braking [6][7][8][9][10][11][12], active front wheel steering [13], anti-roll bars [14,15] and active suspension [16,17] or an integration of different actuators [18][19][20][21]. The majority of approaches quantifies the rollover threat by an appropriate index and switches the control authority to a roll stabilizing controller when indicated.…”

Section: Introductionmentioning

confidence: 99%

Active Vehicle Safety Using Integrated Control of Body Roll and Direct Yaw Moment

Elhefnawy¹,

Sharaf²,

Ragheb³

et al. 2016

The International Conference on Applied Mechanics and Mechanica

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This paper presents an integrated active roll control (ARC) and direct yaw control (DYC) system to improve both the rollover and cornering stability of the vehicle. The presented controller is developed based upon a combination of feedback and feedforward fuzzy logic control for roll control, and a fuzzy logic control for yaw rate.A full vehicle model is used to describe and simulate the vehicle dynamics. Additionally, a yaw-roll plane model is introduced to compare and therefor control the yaw rate, the side slip angle and the roll angle of the vehicle body. Five input variables are considered by the three controllers namely; the vehicle foreword speed, the steering wheel angle, the roll angle, the yaw rate and the side slip angle of the vehicle body. The control action of the direct yaw control DYC and the active roll control ARC both are carried out by generating a differential braking across the front wheels. The numerical modeling is carried out through the MATLAB / SIMULINK environment which suits the control and optimization process.Different simulation results are carried out by considering standard test maneuvers with different speeds such as J-turn, fishhook, and the lane change. The simulation results are compared during four cases namely; the uncontrolled system, the ARC controller only, the DYC controller only and the integrated ARC and DYC controllers. The results show a substantial improvement of the vehicle stability in term of vehicle lateral acceleration, side slip angle, the yaw rate and the roll angle for the developed integrated ARC and DYC controllers compared to that of the individual controller or the uncontrolled system. The main advantage of the proposed controller that it is relies on one actuation which is the differential braking. KEY WORDSActive roll control, direct yaw control, integrated control, fuzzy logic control ‫ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ‬ ‫ـــــــــــــــــــــــــــــــــــ‬ ‫ــــــــــــــــــــــــــــــــــ‬ ‫ـــــــــــــــــــــــــــــــــــــــ‬ * Egyptian Armed Force. AE Location of the origin of vehicle frame of reference from front and rear axle [m] , C f r Damping coefficient of front/rear suspension [N.s/m] , C f r α α Cornering stiffness of front, rear tires [N/rad] , , Tire forces expressed at wheel coordinate systems [N] g Gravitational acceleration [m/s 2 ] , , I I I xx yy zz Mass moment of inertia of the vehicle sprung mass [Kg.m 2 ] , , I I I xy yz zx Mass product moment of inertia of the vehicle sprung mass [Kg.m 2 ] I wi Mass moment of inertia of wheels [Kg.m 2 ] , K f r Stiffness coefficient of front/rear suspension spring [N/m] L Wheelbase (distance between front and rear axle) [m] M B i Braking moment applied to each wheel [N.m] M D i Driving moment applied at each wheel hub [N.m] M s Sprung mass of the vehicle [Kg] M t Total mass of the vehicle [Kg] M U i Resisting moment applied at each wheel hub [N.m] M wi Unsprung mass at each wheel [Kg] , , M M M X Y Z Net moments affecting the vehicle body [N...

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Development of an electric active rollcontrol (ARC) algorithm for a SUV

Cited by 29 publications

References 7 publications

Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

Study on Integrated Control of Active Anti-Roll Steel Bar and Electronic Stability Program Based on Particle Swarm Optimization

Active Vehicle Safety Using Integrated Control of Body Roll and Direct Yaw Moment

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