Research Papers

Integrated Vehicle Dynamics Control Via Torque Vectoring Differential and Electronic Stability Control to Improve Vehicle Handling and Stability Performance

[+] Author and Article Information
Seyed Mohammad Mehdi Jaafari

Mechanical Engineering Department,
Faculty of Engineering,
Shahid Chamran University of Ahvaz,
Ahvaz 6135743337, Iran
e-mail: smm.jaafari@yahoo

Kourosh Heidari Shirazi

Mechanical Engineering Department,
Faculty of Engineering,
Shahid Chamran University of Ahvaz,
Ahvaz 6135743337, Iran
e-mail: k.shirazi@scu.ac.ir

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received February 3, 2017; final manuscript received December 1, 2017; published online January 16, 2018. Assoc. Editor: Junmin Wang.

J. Dyn. Sys., Meas., Control 140(7), 071003 (Jan 16, 2018) (13 pages) Paper No: DS-17-1066; doi: 10.1115/1.4038657 History: Received February 03, 2017; Revised December 01, 2017

This paper proposed a full vehicle state estimation and developed an integrated chassis control by coordinating electronic stability control (ESC) and torque vectoring differential (TVD) systems to improve vehicle handling and stability in all conditions without any interference. For this purpose, an integrated TVD/ESC chassis system has been modeled in Matlab/Simulink and applied into the vehicle dynamics model of the 2003 Ford Expedition in carsim software. TVD is used to improve handling in routine and steady-state driving conditions and ESC is mainly used as the stability controller for emergency maneuvers or when the TVD cannot improve vehicle handling. By the ββ˙ phase plane, vehicle stable region is determined. Inside the reference region, the handling performance and outside the region the vehicle stability has been in question. In order to control the integrated chassis system, a unified controller with three control layers based on fuzzy control strategy, ββ˙ phase plane, longitudinal slip, and road friction coefficient of each tire is designed in Matlab/Simulink. To detect the control parameters, a state estimator is developed based on unscented Kalman filter (UKF). Bees algorithm (BA) is employed to optimize the fuzzy controller. The performance and robustness of the integrated chassis system and designed controller were conformed through routine and extensive simulations. The simulation results via a co-simulation of MATLAB/Simulink and CarSim indicated that the designed integrated ESC/TVD chassis control system could effectively improve handling and stability in all conditions without any interference between subsystems.

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Fig. 3

Kinematic schemes of STC-TVD

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Fig. 2

The comparison of simulation results (CarSim) and field test data (Ref. [12])

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Fig. 1

Vehicle parameter in CarSim

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Fig. 4

Phase portrait of β−β˙ plan

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Fig. 5

(a) Schematic of control system and (b) structure of state estimator

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Fig. 12

Vehicle path and the β−β˙ phase trajectory in the phase plane in critical situation

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Fig. 8

(a) Desired path in double lane change (DLC) maneuver and (b) steering change in front wheels in J and fishhook

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Fig. 9

Yaw rate error and the β−β˙ phase trajectory in the phase plane in fishhook maneuver

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Fig. 10

Yaw rate error and the β−β˙ phase trajectory in the phase plane in DLC

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Fig. 6

Actual and estimated parameters

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Fig. 7

Flowchart of BA algorithm

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Fig. 11

Vehicle path and the β−β˙ phase trajectory in the phase plane in different μ conditions

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Fig. 13

(a) Input membership functions and (b) output membership functions for the fuzzy controller



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