Lateral stability controller design for electrical vehicle based on active rear wheel steering

Guo, Hongyan; Hao, Ningfeng; Chen, Hong

doi:10.1109/wcica.2016.7578507

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…On the other hand, a few researchers concentrate on perfect steering characteristics, namely, to stabilize vehicles by applying active front steering (AFS) or active rear steering (ARS) technique (Shuai et al, 2014). To achieve satisfactory lateral stability with ARS control, Guo et al (2016) proposed a nonlinear model predictive control (NMPC) method, and they further investigated the integration control based on AFS and DYC via NMPC (Guo et al, 2017). An AFS controller was designed by using terminal sliding mode algorithm, besides a disturbance observer was applied to deal with uncertainty and external disturbance (Jin et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Stability control of in-wheel motor electric vehicles under extreme conditions

Zhao

Wang

Zhang

2018

Transactions of the Institute of Measurement and Control

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To investigate the stability of in-wheel motor electric vehicles (IWMEVs) under extreme conditions, a novel control strategy including active rear steering (ARS) mode and direct yaw moment control (DYC) mode is proposed in this paper, utilizing the adaptive dynamic neural network (ADNN) algorithm to make the most of the two control modes. Firstly, a three-degree of freedom nonlinear vehicle model as well as some subsystems is established. Then, a two-layer stability control strategy is put forward, where the upper-layer calculates the desired rear steering angle as well as the differential torque of the rear wheels and the lower-layer executes commands and returns relevant signals. Besides, a stability controller based on ADNN algorithm is designed in the upper-layer so as to take advantage of the two modes under extreme conditions. Next, the impacts of initial values of the connection weights on the ability of ADNN algorithm to train and learn are revealed. Consequently, the optimal initial values can be ascertained before the following simulations. Finally, the closed loop simulations of ARS and DYC are carried out under some extreme conditions such as high velocity and low adhesion coefficient roads, and the results indicate that compared with DYC’s difficulty in playing its role, ARS mode can significantly improve the stability of IWMEVs even under extreme conditions.

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Section: Introductionmentioning

confidence: 99%

Stability control of in-wheel motor electric vehicles under extreme conditions

Zhao

Wang

Zhang

2018

Transactions of the Institute of Measurement and Control

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“…Thus, a particular advantage of MPC is the capability of coordinating several constrained actuators to achieve multiple goals encoded in the performance criterion like done in [3,23,35]. Several other authors have proposed vehicles integrated control based on MPC ( [15,[36][37][38][39]). All of them have to balance computation cost and complexity of the model.…”

mentioning

confidence: 99%

A cooperative control strategy for yaw rate and sideslip angle control combining torque vectoring with rear wheel steering

Vignati

Sabbioni

2021

Vehicle System Dynamics

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Automobiles are becoming more and more complex as multiple control systems are integrated into the vehicle platform. This paper investigates the coordination of active rear steering (RWS) and torque vectoring (TV) -which is enabled by independent electric motors at the rear axle -in controlling vehicle lateral dynamics. Specifically, the proposed controller aims at enhancing vehicle handling performance and stability while cornering. The coordination of the two control systems is achieved by weighting their contribution based on their impact on vehicle dynamics according to the working condition. The impact of each control system is assessed by means of phase portraits. These plots are in fact a very powerful tool for analyzing vehicle nonlinear dynamics as they readily display vehicle stability properties and map equilibrium point locations and movement to changing parameters and control inputs. Based on phase portrait analysis, a performance index is thus proposed, which weights more the control action (TV or RWS) capable of leading the vehicle at the nearest equilibrium point with the fastest rate. The controller performance is assessed through numerical simulations carried out using a nonlinear 14 dofs vehicle model. Results are compared with ones of the two controllers alone (RWS and TV) in different cornering maneuvers and considering different adherence conditions.

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Lateral stability based hybrid controller designed of torque control for distributed wheel-driven electric vehicles

Gao

Liu

et al. 2022

2022 34th Chinese Control and Decision Conference (CCDC)

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Lateral stability controller design for electrical vehicle based on active rear wheel steering

Cited by 8 publications

References 9 publications

Stability control of in-wheel motor electric vehicles under extreme conditions

Stability control of in-wheel motor electric vehicles under extreme conditions

A cooperative control strategy for yaw rate and sideslip angle control combining torque vectoring with rear wheel steering

Lateral stability based hybrid controller designed of torque control for distributed wheel-driven electric vehicles

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