Vehicle dynamics and control for improving handling and active safety: From four-wheel steering to direct yaw moment control

Abé, Masato

doi:10.1243/1464419991544081

Cited by 85 publications

(72 citation statements)

References 8 publications

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“…The FWS is assumed to be the uncontrolled vehicle model's behavior based on the input of the front steering angle only. On the other hand, for the conventional 4WS system, the rear steering angle is determined based on the yaw rate state feedback and the front steering angle feed-forward, which is similar to the work in [16]. Open loop lane change (LC) and step steer (SS) maneuvers are selected to evaluate the controller's effectiveness for the high speed and low speed simulations, respectively.…”

Section: Simulation Setupmentioning

confidence: 99%

Optimal Control Strategy for Low Speed and High Speed Four-Wheel-Active Steering Vehicle

Ariff

Zamzuri²,

Nordin

et al. 2015

J. Mech. Eng. Sci.

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In this work, based on the optimal control theory approach, a four-wheel-active steering (4WAS) system is proposed for low speed and high speed applications. A model following the control structure is adopted consisting of a feed-forward and feedback compensation strategy that serves as correction inputs to enhance the vehicle's dynamic behavior. The velocity dependent feed-forward control inputs are based on the driver's steering intention while the feedback control inputs are based on the vehicle's state feedback errors, being the sideslip and yaw rate of the vehicle. Numerical simulations are conducted using the Matlab/Simulink platform to evaluate the control system's performance. The performance of the 4WAS controller is tested in two designated open loop tests, being the constant steer and the lane change maneuver, to evaluate its effectiveness. A comparison with conventional passive front-wheel-steering (FWS) and conventional four-wheel-steering (4WS) systems shows the preeminent result performance of the proposed control strategy in terms of the response tracking capability and versatility of the controller to adapt to the system's speed environment. In high speed maneuvers, the improvement in terms of yaw rate tracking error in rms is evaluated and the proposed active steering system considerably beat the other two structures with 0.2% normalized error compared to the desired yaw rate response. Meanwhile, in low speed, turning radius reductions of 25% and 50% with respect to the capability of normal or typical FWS vehicles are successfully achieved.

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Section: Simulation Setupmentioning

confidence: 99%

Optimal Control Strategy for Low Speed and High Speed Four-Wheel-Active Steering Vehicle

Ariff

Zamzuri²,

Nordin

et al. 2015

J. Mech. Eng. Sci.

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show abstract

“…Substituting Eqns (8.5) and (8.6) into Eqns (8. 3) and (8.4) gives the response of the vehicle to steering wheel angle when the rear wheel steer is proportional to the front wheel steer…”

Section: Rear Wheel Steer Proportional To Front Wheel Steermentioning

confidence: 99%

Vehicle Dynamics with Active Motion Controls

Abe¹,

Manning²

2009

Vehicle Handling Dynamics

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“…In DYC systems, vehicle sideslip angle is very important for vehicle control (Tchamna and Youn, 2013) (Ding and Taheri, 2010). Many researchers proposed their own ideas for the estimation of sideslip angle, but many of those ideas need some parameters regarding such factors as the moment of inertia (Arndt, et al, 2004) or tire model (Abe, 1999) (Fukada, 1999) (Chumsamutr, et al, 2006) or cornering stiffness (Iijima et al, 2010). Those parameters are hard to measure, and so many DYC systems, like the electronic stability program (ESP), have difficulty in using the sideslip angle.…”

Section: Introductionmentioning

confidence: 99%

Development of adaptive sideslip angle estimator

Park

Gwak

Kwon

et al. 2016

JAMDSM

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The sideslip angle is used to control a vehicle for safety, however, it is hard to estimate the sideslip angle. In many researches, the estimator needs many unattainable variables, such as yaw inertia or cornering stiffness, to estimate the sideslip angle. This paper proposes the observer uses geometrically derived equations. The estimator needs a compensation value to estimate the sideslip angle instead of unattainable variables. The compensation value compensates the error from the imperfections of the formulas and nonlinearity motion at high speed. Estimator tunes its compensation value automatically, and uses the least squares method for estimating the compensation value and to apply to a real vehicle. Estimator is developed by LabVIEW, and gets the simulation result through CarSim. The algorithm of finding a proper compensation value is simply using the sensor data that are already mounted on vehicles, such as yaw rate, longitudinal speed, and lateral acceleration. The real vehicle test was conducted to verify the proposed algorithm. From the results, the algorithm can estimate the sideslip angle without unattainable variables.

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Vehicle dynamics and control for improving handling and active safety: From four-wheel steering to direct yaw moment control

Cited by 85 publications

References 8 publications

Optimal Control Strategy for Low Speed and High Speed Four-Wheel-Active Steering Vehicle

Optimal Control Strategy for Low Speed and High Speed Four-Wheel-Active Steering Vehicle

Vehicle Dynamics with Active Motion Controls

Development of adaptive sideslip angle estimator

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