Vehicle roll centre estimation with transient dynamics via roll rate

Zhang, Xinjie; Yan, Yipeng; Guo, Konghui; Yang, Yi; He, Guanjie

doi:10.1080/00423114.2020.1838565

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…In [5], Brandt et al analyzed the instability of vehicles when traveling at high speeds, which is caused by crosswinds. Factors related to the vehicle's dimensions, such as the height of the center of gravity (CG), the wheelbase, the mass, etc., also significantly affected lateral instability when steering [6]. Besides, external factors such as the quality of the road surface or weather conditions also greatly influenced this problem [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Development of a Fuzzy Algorithm With Multiple Inputs for the Active Stabilizer Bar to Improve Vehicle Stability When Steering

Nguyen

2023

IEEE Access

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In this article, the author discusses the issue of vehicle roll instability when steering at high speeds. Installing an active stabilizer bar in a car is recommended to prevent it from rolling over and make it more stable when it does. A complex dynamic model is set up to evaluate and analyze vehicle oscillations. Besides, a fuzzy algorithm with three independent inputs is used to control the operation of the active stabilizer bar. This algorithm uses three separate inputs derived from the vehicle's oscillating signals.In addition, the membership function and fuzzy rule are designed to ensure that the quality and efficiency of the system are well-maintained and stable. This is an entirely new method, which is rarely used for complex models of cars. Numerical simulation is carried out in a Simulink environment with many specific cases and situations. According to research findings, the roll angle of the vehicle body increases as the speed increases. This causes a greater change in wheel dynamics force and increases the risk of rollover. If the car is equipped with an active stabilizer bar controlled by the fuzzy algorithm with three inputs, these problems are significantly reduced compared to all other situations. So, when this new algorithm is added to the active stabilizer bar, the car's stability and safety can improve even.

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Section: Introductionmentioning

confidence: 99%

Development of a Fuzzy Algorithm With Multiple Inputs for the Active Stabilizer Bar to Improve Vehicle Stability When Steering

Nguyen

2023

IEEE Access

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“…The value of the roll index can be accurately calculated using complex dynamic models instead of just a simple formula. This is because the roll center's position changes continuously as the vehicle moves, according to Zhang et al [18].…”

Section: Introductionmentioning

confidence: 99%

An original fuzzy control approach for active anti-roll bars to prevent rollover

Nguyen

2023

PLoS ONE

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In this article, the author introduces a new fuzzy control solution to direct active anti-roll bars (hydraulic stabilizer bars) in order to enhance the vehicle’s roll stabilization efficiency. The original fuzzy algorithm designed in this work can satisfy all the roll stability, comfort, and response speed requirements, while previous algorithms could only meet one of these criteria. In addition, a fully dynamic model is established to simulate the vehicle’s roll oscillations instead of only using a simple half-dynamic model combined with the single-track dynamic model. The calculation and simulation processes take place in the Simulink environment. Two cases of steering are used as input to the simulation problem; the car’s speed is gradually increased through three levels. According to results of research, the roll angle and roll index of the car increase as the speed and steering angle increase. The interaction between the road and wheel decreases sharply as the roll angle increases, which can lead to a rollover. In the first case, the rollover occurs only when the car travels at v3 without the stabilizer bar and has a maximum roll angle of 9.81°. In the second case, this occurs for the (None) situation when traveling at speed v1 with a maximum roll angle of 9.52° and for the (Passive) situation when traveling at speed v2 with a peak value of 11.93°. Meanwhile, the vehicle’s stability is still well guaranteed when utilizing active anti-roll bars controlled by an original fuzzy algorithm.

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Proposing a new control method for active stabilizer bars using an intelligent self-learning algorithm

Nguyen

2024

Proceedings of the Institution of Mechanical Engineers, Part D:

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This article’s main content is directed toward designing and applying a new control algorithm for automotive stabilizer bars. Previous studies often only used classical control algorithms or simple fuzzy algorithms to control hydraulic anti-roll systems on cars based on safety criteria. In this article, a self-learning algorithm (ANFIS) is established based on inheriting the advantages of previous algorithms. Additionally, this algorithm is modified and improved to increase the convergence of the results after the end of the steering process. Simulations show that when the self-learning solution is applied to active anti-roll bars, the roll angle value and the attenuation of the vertical force at wheels decrease significantly. In complex motion conditions (second case, v3), rollover occurs if the automobile does not have an anti-roll bar. However, roll stability and road holding ability are always ensured when applying the ANFIS algorithm to control active anti-roll bars. According to these findings, the minimum value of the vertical force at the rear wheel can be up to 1384.02 N even when the car is traveling in extremely harsh conditions (second case, v4). In addition, the response speed and convergence of values are always well-controlled when the intelligent self-learning algorithm is applied to the anti-roll control system.

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Vehicle roll centre estimation with transient dynamics via roll rate

Cited by 4 publications

References 18 publications

Development of a Fuzzy Algorithm With Multiple Inputs for the Active Stabilizer Bar to Improve Vehicle Stability When Steering

Development of a Fuzzy Algorithm With Multiple Inputs for the Active Stabilizer Bar to Improve Vehicle Stability When Steering

An original fuzzy control approach for active anti-roll bars to prevent rollover

Proposing a new control method for active stabilizer bars using an intelligent self-learning algorithm

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