Coordination strategy between AFS and ASB with fault-tolerant mechanism for ground vehicle

Pi, Dawei; Yan, Maode; Liu, Yulong; Liu, Yahui

doi:10.1177/0954407019896141

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…The controller parameters are tuned by the fuzzy algorithm. This problem was also taken up by Dawei, et al [32]. According to Zhuo, et al., the roll angle of the vehicle body can be reduced if the active stabilizer bar is used to replace the conventional passive stabilizer bar.…”

Section: Introductionmentioning

confidence: 98%

Using a novel fuzzy 3-inputs algorithms to control the active hydraulic stabilizer bar with the complex model of the vehicle nonlinear dynamics

Nguyen

2023

PLoS ONE

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Under the influence of centrifugal force, the rollover phenomenon may occur. The vehicle rolls over when the wheel is completely separated from the road surface, i.e., the vertical force of the wheel is reduced to zero. To overcome this problem, the active stabilizer bar is used at the front and rear axles of the vehicle. The active stabilizer bar works on the difference in fluid pressure inside the hydraulic motor. This article is aimed at studying the vehicle rollover dynamics when the hydraulic stabilizer bar is used. In this article, the model of a complex dynamic is established. This is a combination of the model of spatial dynamics, the model of nonlinear double-track dynamics, and the nonlinear tire model. The operation of the hydraulic actuator is controlled by a fuzzy algorithm with 3-inputs. The defuzzification rule is determined based on the combination of 27 cases. The process of calculation and simulation is done with four specific cases corresponding to steering angles. In each case, three situations were investigated. Besides, the speed of the vehicle is also gradually increased from v1 to v4. As a result of the simulation, which was performed in the MATLAB-Simulink environment, the output values such as roll angle, change of the vertical force, and roll index were significantly reduced when the active stabilizer bar was used. If the vehicle does not use the stabilizer bar, the vehicle may roll over in both the second, third, and fourth cases. If the vehicle uses a mechanical stabilizer bar, this also occurs in the third and fourth cases (only at a very high velocity, v4). However, the rollover phenomenon did not occur if the vehicle used a hydraulic stabilizer bar controlled by the fuzzy 3-inputs algorithm. In all investigated cases, the stability and safety of the vehicle are always guaranteed. Besides, the responsiveness of the controller is also very good. An experimental process needs to be conducted to verify the correctness of this research.

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Section: Introductionmentioning

confidence: 98%

Using a novel fuzzy 3-inputs algorithms to control the active hydraulic stabilizer bar with the complex model of the vehicle nonlinear dynamics

Nguyen

2023

PLoS ONE

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“…The four-wheel torque of the distributed drive electric vehicle can be accurately controlled independently, providing an important solution to high-performance control of vehicle dynamics [1] . At present, tire force regulation is the most direct and effective active control technology, but a single tire forces regulation inevitably has a control blind area, and the integration of multiple tire forces will lead to coupling or even conflict of control actions [2] . The traditional control method is difficult to achieve effective decoupling of vehicle nonlinear dynamics systems, and the process is complex and difficult.…”

Section: Introductionmentioning

confidence: 99%

Improved Deep Reinforcement Learning Decision for Integrated Control of Distributed Drive Electric Vehicle Dynamics

Huang

2023

J. Phys.: Conf. Ser.

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To solve the problem of nonlinear coupling with longitudinal and lateral tire forces in the integrated control of distributed driving electric vehicles, an improved SAC reinforcement learning algorithm is proposed to coordinate the control method of active front steering (AFS) and torque distribution. The coordinated control adopts a layered structure, and the upper layer adopts the LQR controller to determine the additional front wheel rotation angle and yaw moment required for stability control. The three-level reward function is designed with the goal of vehicle stability and state tracking and is determined by the reinforcement learning algorithm. For the weight factors of the two optimization objectives, the SAC reinforcement learning algorithm is used to coordinate the decision-making of the active front wheel steering and the additional yaw moment; the lower controller uses the comprehensive utilization rate of the tire as the objective function to perform the optimal torque distribution. A co-simulation platform is established in MATLAB/Simulink and CarSim software. The results show that compared with AFS control, SAC coordinated control can not only ensure the stability of the vehicle and achieve accurate tracking of the reference state but also effectively reduces the comprehensive utilization rate of tires and the effectiveness of coordinated control.

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“…An introduction to the hydraulic stabilizer bar system of BMW vehicles should be consulted as in Ref. 44 Hydraulic stabilizer bars can be combined with the active steering system for better performance, according to Dawei et al 45 Control algorithms play a crucial role in ensuring the bar's operation. In Ref., 46 Varga et al propose a control design for hydraulic stabilizer bars with a hierarchical control algorithm.…”

Section: Introductionmentioning

confidence: 99%

Proposing a novel fuzzy control algorithm for automotive active stabilizer bars based on views of roll stability and ride comfort

Nguyen

2023

Proceedings of the Institution of Mechanical Engineers, Part K:

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Using stabilizer bars in cars to limit rollover is a necessity applied to many vehicles today. In this article, the author proposes using a new fuzzy method to control the hydraulic stabilizer bars. Previous studies only focused on improving the roll stability of cars, while this article focuses on ensuring both the roll stability and ride comfort of the vehicle, which is considered the new contribution of the article. Vehicle oscillations are described through a complex nonlinear dynamic model. The MATLAB® application performs the simulation with two specific cases, including fish-hook steering and J-turn steering. According to the findings of this research, the roll angle value is significantly reduced when using active stabilizer bars directed by the novel algorithm. In addition, the risk of the rollover was also strongly reduced for both simulations (there are four-speed thresholds used in each case). For the first case, rollover does not occur when the car utilizes active stabilizer bars, even when travelling at v4 = 100 (km/h). In the other case, the rollover occurs only for the Active situation when travelling at a very high speed. In contrast, this phenomenon occurs in the None situation at v1 and the Passive situation at v2. The results found from this work help to evaluate the performance of the fuzzy control algorithm for active stabilizer bars.

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Coordination strategy between AFS and ASB with fault-tolerant mechanism for ground vehicle

Cited by 10 publications

References 25 publications

Using a novel fuzzy 3-inputs algorithms to control the active hydraulic stabilizer bar with the complex model of the vehicle nonlinear dynamics

Using a novel fuzzy 3-inputs algorithms to control the active hydraulic stabilizer bar with the complex model of the vehicle nonlinear dynamics

Improved Deep Reinforcement Learning Decision for Integrated Control of Distributed Drive Electric Vehicle Dynamics

Proposing a novel fuzzy control algorithm for automotive active stabilizer bars based on views of roll stability and ride comfort

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