Vibration Control of Truck Cabins With the Adaptive Vectorial Backstepping Design of Electromagnetic Active Suspension System

Başaran, Sinan; Başaran, Murat Alper

doi:10.1109/access.2020.3025357

Cited by 13 publications

(6 citation statements)

References 70 publications

(81 reference statements)

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“…Finally, the results showed that the proposed approach gave an improvement in ride comfort. Basaran [28] proposed an electromagnetic active suspension system for a three-axle truck cabin. The purpose of their work is to reduce vibration transmitted from road unevenness by using electromagnetic actuators.…”

Section: Kim and Leementioning

confidence: 99%

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

et al. 2021

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One type of vehicle suspension system is the air suspension system. One of the important functions of the suspension system is to reduce vibration transmitted to the vehicle body from road unevenness. Soft suspension results in better ride comfort and worst handling. While stiff suspension results in better handling and worse comfort. This paper investigates the performance of air suspension in terms of passenger ride comfort and vehicle handling. The performance is tested once with Fuzzy logic control and another with Fuzzy control augmented with Neuro-Fuzzy inference system. A mathematical model is developed to describe the air-spring stiffness behavior. The air-spring suspension is merged on two degrees of freedom model. The air pressure is controlled by a Fuzzy controller as done previously in the literature. On the other hand, our approach is to control the volume change by connecting the air-spring volume to two additional unequal volumes through ON-OFF solenoid valves. The solenoid valves are controlled by Adaptive Neuro-Fuzzy Inference System (ANFIS). A single-degree-of-freedom setup was built from which the required training data for the ANFIS controller was carried out. The experimental setup is developed with variable excitation input in terms of frequency and amplitudes. The acceleration of the sprung mass has been measured and stored at different operating conditions and including different air volumes. The stored data is used for training of volume controller. The controller is tested with Sinusoidal excitation then with ISO 8608 road profile. It is found that increasing the air volume reduces the sprung mass acceleration. Also, the results showed that implementing the Neuro-Fuzzy controller with Fuzzy logic control reduces the sprung mass acceleration significantly by an average value that reaches 5 cm/s 2 at frequencies above 1 Hz while maintaining road holding.

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Section: Kim and Leementioning

confidence: 99%

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

et al. 2021

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“…In addition, an active suspension system is also proposed to compensate for the vibration. The previous studies propose PID (Proportional–Integral–Differential controller) designed based on the dynamic model (Wang et al, 2018) and the adaptive control method (Basaran et al, 2020) for the active suspension system. Although these methods effectively compensate for vibration, implementing additional parts for the suspension system increases the cost.…”

Section: Introductionmentioning

confidence: 99%

Compensation for low-frequency vibration in lateral control of truck by adaptive feed-forward cancellation

Yabui

Suzuki

Fukazawa

et al. 2023

Journal of Vibration and Control

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The role of truck transportation is becoming increasingly important in the growth of the e-commerce market. Self-driving trucks are being developed for efficient transportation. To realize a safe self-driving system, the control system should compensate for various vibrations while the truck is running. In the yaw direction, the mechanical resonance of the chassis suspension can cause low-frequency vibration. There are two approaches to compensate for the vibration. The first is a vibration control by using the truck suspension system. The method effectively compensates for vibration; implementing additional parts increases the cost. The second is vibration control based on the yaw-rate feedback control system. A notch filter or a lowpass filter decreases the gain at the vibration frequency and is effective in compensating for vibrations. The tracking performance of the reference signal can be degraded by decreasing the gain in the low-frequency range. Therefore, it is required that a solution can compensate for the vibration without the additional parts and no performance degradation. This paper proposes the use of an adaptive feed-forward cancellation (AFC) to compensate for low-frequency vibrations in the yaw-rate feedback control system. The AFC generates a compensation signal based on the difference between the reference signal and the actual yaw rate. The AFC does not reduce the gain near the vibration frequency; therefore, the AFC can achieve low-frequency vibration compensation while maintaining the tracking performance. In addition, the proposed control system does not require additional parts. The effectiveness of the proposed method was verified by experiments using an actual commercial truck.

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“…The analysis of the active suspension system is also widely discussed due to its impact on the safety and comfort of driving, especially in heavy vehicles. Basaran [13] developed an analytical model of the active suspension system of a truck cabin. The system is controlled by an electromagnetic actuator, which, compared to a pneumatic system, is precise and operates with lower inertia.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Correctness of Mapping the Passage of a Semi-Trailer through a Road Obstacle on a Road Simulator

Czarnuch,

Stembalski,

Szydłowski

et al. 2023

Sensors

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Road simulators enable accelerated durability tests under similar-to-real road conditions. However, the road simulator itself generates the signals with the appropriate strength and amplitude that is adequate to the response registered by the sensors during the real run. Therefore, there is a need for verification of the validity of the representation of vehicle runs on a road simulator in terms of the shape of the generated profile and possible sources of uncertainty. The tests in this study were carried out for a multi-axle vehicle passing an obstacle of known shape. Various signals were registered while the vehicle was passing over the obstacle. The MTS (System Corporation) road simulator’s response to the signal given by the obstacle was then checked. The results showed a 99% correlation between the simulation and the road test results. A numerical model of the vehicle was developed to verify the quality of representation of the real conditions by the road simulator, especially in terms of forces resulting from the road profile. Interestingly, the input signal generated by the road simulator provided a very good accuracy of the vehicle response, as tested with use of the numerical model.

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Vibration Control of Truck Cabins With the Adaptive Vectorial Backstepping Design of Electromagnetic Active Suspension System

Cited by 13 publications

References 70 publications

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

Compensation for low-frequency vibration in lateral control of truck by adaptive feed-forward cancellation

Analysis of the Correctness of Mapping the Passage of a Semi-Trailer through a Road Obstacle on a Road Simulator

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