Study on the performance of active front steering system

Xu, Yijun; Ahmadian, M.

doi:10.1007/s12239-013-0064-5

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…and A l , B l,d , and B M are defined as tire models expressed in (3) and (4). However, AFS and ESCs are most commonly activated when nonlinear characteristics of tire forces, such as the friction ellipse effect or tire force saturation, appear since vehicles tend to loose lateral stability when the tires generate lateral forces close to their frictional limits.…”

Section: Bicycle Model With Lagged Dynamicsmentioning

confidence: 99%

“…As a result, because of the potential characteristic of AFS that can assist ESC to minimize the longitudinal perturbation to stabilize the vehicles at the limits of handling, a wide range of studies that coordinates AFS and ESC to secure the vehicle yaw stability has been introduced in the literature. 3,4,16 Although the performances of these algorithms are satisfactory according to their simulations or experimental results, they do not appropriately account for the deteriorations of the performances caused by the lags of actuators of AFSs or ESCs. Since a vehicle in an unstable state region can rapidly deviate from its desired trajectory, even in a short time, small delays or lags of the vehicle safety systems can lead to fatal vehicle accidents.…”

Section: Introductionmentioning

confidence: 99%

“…3,4,16 Although the performances of these algorithms are satisfactory according to their simulations or experimental results, they do not appropriately account for the deteriorations of the performances caused by the lags of actuators of AFSs or ESCs. Since a vehicle in an unstable state region can rapidly deviate from its desired trajectory, even in a short time, small delays or lags of the vehicle safety systems can lead to fatal vehicle accidents.…”

Section: Introductionmentioning

confidence: 99%

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MPC for vehicle lateral stability via differential braking and active front steering considering practical aspects

Choi

2015

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a control architecture that simultaneously utilizes active front steering (AFS) and differential braking for vehicle lateral stability while minimizing longitudinal perturbations. This control scheme is based on the model predictive control (MPC) using the extended bicycle model that captures the lagged characteristics of tire forces and actuators. The nonlinearities of tire force are also reflected on the extended bicycle model by linearizing the tire forces at the operating points. Instead of casting the MPC problem into a quadratic program with constraints that require numerical solvers, the proposed method is designed to follow the reference states with desired inputs since the solutions of MPC problems with affine models to track desired states can be easily obtained by matrix inversion. Simulation results, obtained by the vehicle dynamics software Carsim, demonstrate that the suggested method is able to control the vehicle to track the desired path while keeping the vehicle lateral stability on various road surfaces.

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Section: Bicycle Model With Lagged Dynamicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MPC for vehicle lateral stability via differential braking and active front steering considering practical aspects

Choi

2015

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…A method to evaluate the system performance on involvement and dynamics is proposed. 5 A dynamic model of an AFS system is proposed. Two numerical simulations are implemented to verify the effectiveness of model.…”

Section: Introductionmentioning

confidence: 99%

A model free controller based on reinforcement learning for active steering system with uncertainties

Zhao

Cheng

Zhang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Vehicle steering control is crucial to autonomous vehicles. However, unknown parameters and uncertainties of vehicle steering systems bring a great challenge to its control performance, which needs to be tackled urgently. Therefore, this paper proposes a novel model free controller based on reinforcement learning for active steering system with unknown parameters. The model of the active steering system and the Brushless Direct Current (BLDC) motor is built to construct a virtual object in simulations. The agent based on Deep Deterministic Policy Gradient (DDPG) algorithm is built, including actor network and critic network. The rewards from environment are designed to improve the effectiveness of agent. Simulations and testbench experiments are implemented to train the agent and verify the effectiveness of the controller. Results show that the proposed algorithm can acquire the network parameters and achieve effective control performance without any prior knowledges or models. The proposed agent can adapt to different vehicles or active steering systems easily and effectively with only retraining of the network parameters.

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“…Especially the objective evaluation of the oncentre handling range is in large parts unexplored. Lately several papers have been published on this topic and the importance of the on-centre handling became more recognized (Xu and Ahmadian, 2013;Harrer and Porsche, 2008;Kim and Kim, 2008;Mouri et al, 2007;Pfeffer, 2006;Badawy et al, 1999;Engels, 1994;Nybacka et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Vehicle and steering system dynamics in the context of on-centre handling

Ende

Küçükay

Henze

et al. 2015

Int.J Automot. Technol.

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The interaction of the vehicle and steering system is important to evaluate the vehicle on-centre handling. To analyse the vehicle and steering system dynamics at small steering wheel angle inputs a methodological approach to validate a simulation model is developed in this paper. The presented model is focused on the description of the major on-centre handling phenomena and characteristics. For the validation of the model adjusted test manouevres and a certain procedure to achieve highly reproducible measurement data are described. Due to the collected measurement data it is possible to describe the vehicle on-centre behaviour and to validate the overall model in a phased manner and more exactly. The results show the importance of the steering system characteristics and its influence on the on-centre handling regarding small steering wheel angles at low frequencies. Next to the steering system friction and elasticity the influence of the vehicle and steering system hysteresis loop is presented.

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Study on the performance of active front steering system

Cited by 10 publications

References 12 publications

MPC for vehicle lateral stability via differential braking and active front steering considering practical aspects

MPC for vehicle lateral stability via differential braking and active front steering considering practical aspects

A model free controller based on reinforcement learning for active steering system with uncertainties

Vehicle and steering system dynamics in the context of on-centre handling

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