Phase Plane Analysis for Vehicle Handling and Stability

Zhang, Hao; Li, Xiansheng; Shi, Shuming; Liu, Hongfei; Guan, Rachel; Liu, Li

doi:10.2991/ijcis.2011.4.6.9

Cited by 23 publications

(11 citation statements)

References 24 publications

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“…Figure 7f shows the sideslip angle rate and the sideslip angle in the phase plane. The curve of the adaptive control, compared with the other two controls, is most concentrated on the origin, which indicates that the stability control effect is best [21,31]. Figure 7g-i show the torque of each hub motor under the speed control, common control, and adaptive control, respectively.…”

Section: µ-Split Roadmentioning

confidence: 96%

Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient

Hou

Zhai

Sun³

2018

Energies

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In order to enhance the steering stability of a four hub-motor independent-drive electric vehicle (4MIDEV) on a road with varying adhesion coefficient, for example on a joint road, this paper proposes a hierarchical steering stability control strategy adapted to the road adhesion. The upper control level of the proposed strategy realizes the integrated control of the sideslip angle and yaw rate in the direct yaw moment control (DYC), where the influences of the road adhesion and sideslip angle are both studied by the fuzzy control. The lower control level employs a weight-based optimal torque distribution algorithm in which weight factors for each motor torque are designed to accommodate different adhesion of each wheel. The proposed stability control strategy was validated in a co-simulation of the Carsim and Matlab/Simulink platforms. The results of double-lane-change maneuver simulations under different conditions indicate that the proposed strategy can effectively achieve robustness to changes in the adhesion coefficient and improve the steering stability of the 4MIDEV.

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Section: µ-Split Roadmentioning

confidence: 96%

Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient

Hou

Zhai

Sun³

2018

Energies

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“…Therefore, the effects of DB and AS can be compared by the variations of yaw moment and yaw rate, which can be calculated using Eqs. (21) and (29), respectively. From Figure 6, the feasibility of this comparison method can be proved.…”

Section: Comparisonmentioning

confidence: 99%

“…Figure 6 shows the comparison under different conditions, where the solid lines are results from Eqs. (21) and (29). DB or AS operate to generate an opposite yaw moment after steering.…”

Section: Comparisonmentioning

confidence: 99%

“…[18], AFS and DYC have been integrated via fuzzy logic based on stability index obtained by the phase plane analysis. The phase plane analysis is widely discussed and applied for vehicle stability analysis and control [19][20][21]. Empirical methods such as setting gains [22,23] and fuzzy logic [18,24] are also employed in integrated control methods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Zhang¹,

Zong²,

Chen³

et al. 2019

Chin. J. Mech. Eng.

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Differential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both differential braking and active steering. This research proposes an integrated control system that can simultaneously invoke differential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.A) l i−1 − l v > 0, B bli ≥ 0, A bli < 0, δ i > 0 B) l i−1 − l v > 0, B bli > 0, A bli < 0, δ i = 0 C) l i−1 − l v = 0, δ i = 0 a4 B bri = 0, A bri = 0 (Cannot use this wheel to brake) B bli = 0, A bli = 0 (Cannot use this wheel to brake)

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“…Shen et al examined the relationship between bifurcations in the β-r phase plane and the difference between front and rear tyre slip angles using a joint-point locus approach [9]. Zhang et al summarised the use of the β-r plane and the locations of equilibria to describe the stability of the vehicle [10].…”

Section: Introductionmentioning

confidence: 99%

Vehicle control synthesis using phase portraits of planar dynamics

Bobier-Tiu

Beal

Kegelman

et al. 2018

Vehicle System Dynamics

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Phase portraits provide control system designers strong graphical insight into nonlinear system dynamics. These plots readily display vehicle stability properties and map equilibrium point locations and movement to changing parameters and system inputs. This paper extends the usage of phase portraits in vehicle dynamics to control synthesis by illustrating the relationship between the boundaries of stable vehicle operation and the state derivative isoclines in the yaw rate-sideslip phase plane. Closed-loop phase portraits demonstrate the potential for augmenting a vehicle's open-loop dynamics through steering and braking. The paper concludes by applying phase portrait analysis to an envelope control algorithm for yaw stability and a sliding surface controller for stabilising a saddle point equilibrium in drifting.

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Phase Plane Analysis for Vehicle Handling and Stability

Cited by 23 publications

References 24 publications

Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient

Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient

A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Vehicle control synthesis using phase portraits of planar dynamics

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