Sensing methodologies to determine automotive damper condition under vehicle normal operation

Ferreira, Carlos; Ventura, P.J.; Morais, Raul; Valente, António; Neves, Carlos; Reis, Manuel J. C. S.

doi:10.1016/j.sna.2009.03.035

Cited by 29 publications

(15 citation statements)

References 24 publications

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“…The shock-absorber force is related to the pressure loss across a simple throttle valve. 22,23 The pressure loss is connected with the volume flows A A ð _ q 1x À _ q sx Þ and A B ð _ q 1x À _ q sx Þ between chambers A and B of the shock-absorber…”

Section: Model Of the Horizontal Suspension With Seated Human Bodymentioning

confidence: 99%

“…The shock-absorber force is related to the pressure loss across a simple throttle valve. 22,23 The pressure loss is connected with the volume flows AA(q·1x-q·sx) and AB(q·1x-q·sx) between chambers A and B of the shock-absorber where ρo is the density of liquid and is assumed as a constant value, ζ(B→A) and ζ(A→B) are the pressure loss coefficients for the flow from chamber B to chamber A and from chamber A to chamber B respectively, AA and AB are the surfaces of shock-absorber piston (side A and side B, respectively), …”

Section: Model Of the Horizontal Suspension With Seated Human Bodymentioning

confidence: 99%

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Shaping the vibro-isolation properties of horizontal seat suspension

Maciejewski

Krzyżyński

Meyer³

et al. 2017

Journal of Low Frequency Noise, Vibration and Active Control

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In this paper, an effective procedure of shaping the vibro-isolation properties of seat suspension system is presented. The simulation model is created to determine the dependence of evaluation criteria to the design parameters by means of which the system characteristics are formed. The developed optimisation procedure allows to find Pareto-optimal system configuration for the conflicted vibro-isolating criteria, i.e. the frequency weighted transmissibility factor used to evaluate dynamic seat comfort based on acceleration signals and the suspension travel. In order to optimise both the conflicted vibro-isolation criteria, a minimising of the transmissibility factor (primary criterion) is proposed taking into account the suspension travel that is transferred to a non-linear inequality constraint. The correctness of proposed procedure is evaluated using experimental research of the best solution of horizontal seat suspension. This research is performed using the passive system with optimal visco-elastic characteristics, which are selected especially for the welldefined input vibration. The satisfactory agreement of experimental and numerical results is obtained for the analysed vibration reduction system.

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Section: Model Of the Horizontal Suspension With Seated Human Bodymentioning

confidence: 99%

Section: Model Of the Horizontal Suspension With Seated Human Bodymentioning

confidence: 99%

Shaping the vibro-isolation properties of horizontal seat suspension

Maciejewski

Krzyżyński

Meyer³

et al. 2017

Journal of Low Frequency Noise, Vibration and Active Control

View full text Add to dashboard Cite

show abstract

“…Different researches have been focused for fault diagnosis in suspension components, particularly failures in dampers, using residual generation based on parity spaces [8,9], unknown input observers [18], and robust observers [17]. Other researches use the frequency domain analysis to diagnosis faulty damping configurations [7,9]. Based on the frequency modal analysis, this paper extends the Fault Diagnosis and Isolation (FDI) properties of the FDI presented in [9] for diagnosis damper and spring faults, whose methodology here has been validated in different vehicle suspension models.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis for Vehicle Suspensions Using Modal Frequency Analysis

Piña-Alanís

Lozano-Cerda

Cavazos-Alanis

et al. 2021

Lecture Notes in Networks and Systems

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The fault diagnosis of an automotive suspension can become ambiguous because there is no general methodology to detect suspension problems. The main purpose of this work is to introduce a numerical analysis to determinate the state of a suspension system which is meant to be developed in future works for its practical application. It is considered that the spring and damper are the elements of the suspension that deteriorate the most over time, causing greater inconvenience to the driving experience, also, it is worth mentioning that being the main components of the suspension, these are the ones that most affect the system at the time of failure. The methodology to find suspension failures presented in this paper is based on the modal analysis of the frequency response of a quarter of vehicle model. To validate the methodology, different vehicles will be used to identify a pattern in the behavior that allows to generalize the appropriate response in a vehicle. The condition of the suspension can be determined by a graphical inspection of the frequency response: As the damper is tailing, the magnitude in the resonance frequency tends to ∞. On the other hand, as the spring fails, the resonance frequency tends to zero, independently of the damper state, allowing to isolate the fault.

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“…Approaches in the field of Fault Detection and Isolation (FDI) can be categorized as reliability-based, model-based, signal-based, and statistical-based FDI [1]. Existing approaches in monitoring the health of the chassis system of a vehicle are often model-based [2][3][4] or signal-based [5,6]. However, to the authors' knowledge, there is no such approach applied in a series production vehicle.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing Automotive Damper Defects Using Convolutional Neural Networks and Electronic Stability Control Sensor Signals

Zehelein

Hemmert-Pottmann

Lienkamp

2020

JSAN

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Chassis system components such as dampers have a significant impact on vehicle stability, driving safety, and driving comfort. Therefore, monitoring and diagnosing the defects of these components is necessary. Currently, this task is based on the driver’s perception of component defects in series production vehicles, even though model-based approaches in the literature exist. As we observe an increased availability of data in modern vehicles and advances in the field of deep learning, this paper deals with the analysis of the performance of Convolutional Neural Networks (CNN) for the diagnosis of automotive damper defects. To ensure a broad applicability of the generated diagnosis system, only signals of a classic Electronic Stability Control (ESC) system, such as wheel speeds, longitudinal and lateral vehicle acceleration, and yaw rate, were used. A structured analysis of data pre-processing and CNN configuration parameters were investigated in terms of the defect detection result. The results show that simple Fast Fourier Transformation (FFT) pre-processing and configuration parameters resulting in small networks are sufficient for a high defect detection rate.

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Sensing methodologies to determine automotive damper condition under vehicle normal operation

Cited by 29 publications

References 24 publications

Shaping the vibro-isolation properties of horizontal seat suspension

Shaping the vibro-isolation properties of horizontal seat suspension

Fault Diagnosis for Vehicle Suspensions Using Modal Frequency Analysis

Diagnosing Automotive Damper Defects Using Convolutional Neural Networks and Electronic Stability Control Sensor Signals

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