Kalman filtering based prognostics for automatic transmission clutches

Ompusunggu, Agusmian Partogi; Papy, Jean-Michel; Vandenplas, Steve

doi:10.1109/tmech.2015.2440331

Cited by 34 publications

(15 citation statements)

References 21 publications

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“…5) When considered as random variables, the SoH and the speed of degradation allows the IFORM to predict the RUL with probability bounds (see Section 3.D). Usually, the confidence in the state estimation of the EKF has been extensively used for assessing the precision [15]. Despite the fact that the value of the computed uncertainty is strongly dependent on the setting of the observer, it is usually not discussed in the consulted literature.…”

Section: A Generalities and Methodsmentioning

confidence: 99%

Fuel cell remaining useful life prediction and uncertainty quantification under an automotive profile

Bressel

Hilairet

Hissel

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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Proton exchange membrane fuel cell is a clean and efficient energy converter that can be use to power an electrical vehicle efficiently. Nevertheless, degradation mechanisms affect the lifespan of this electrochemical converter. Consequently, the estimation of the State of Health and Remaining Useful Life have been the subject of numerous researches in the past years. However, most of the methods available in the literature dealing with fuel cell prognostic do not allow the uncertainty quantification of the estimation that can be implemented online due to the computational cost. As a novelty, this paper presents a prognostic algorithm based on an Extended Kalman Filter. This observer estimates the State of Health, the speed of the degradation and also provides the estimation uncertainty. Then, an Inverse First Order Reliability Method computes the Remaining Useful Life with a 90% confidence interval based on the estimation of the observer. This method is applied on a 175 hours dataset coming from a experimental test on a 8-cells fuel cell stack subjected to an automotive power profile.

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Section: A Generalities and Methodsmentioning

confidence: 99%

Fuel cell remaining useful life prediction and uncertainty quantification under an automotive profile

Bressel

Hilairet

Hissel

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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“…• Optimizing shifting duration for improving drivability A fully automatic (AT) transmission deploys prognostics by fusing a degradation model with the pre-lockup feature from measurement, under the extended Kalman filtering framework developed by Ompusunggu, Make, Belgium, Papy, and Vandenplas (2015). A condition monitoring method for wet friction clutches that can be used in real-life applications has been developed and discussed in this paper.…”

Section: Amt Clutch Prognosticsmentioning

confidence: 99%

Integrated Prognostics Observer for Condition Monitoring of an Automated Manual Transmission Dry Clutch System

Ramalingam

Prasad

Regalla

2020

IJPHM

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The closed loop feedback control system of an Automated Manual Transmission (AMT) electro-pneumatic clutch actuator is used for intelligent real time condition monitoring, enhanced diagnostics and prognostic health management of the dry clutch system, by integrating with the existing gearbox prognostics observer. The real-time sensor data of the clutch actuator piston position is analyzed for monitoring the condition of the clutch system. Original parameters of the new clutch are stored in the Electrically Erasable Programmable Read-only Memory (EEPROM) of the AMT controller and the real-time data is used by the observer for assessing the degradation/wear of the frictional clutch parts. Also, clutch slip during torque transmission is monitored, using the engine speed and the gearbox input shaft speed from Controller Area Network (CAN). Condition monitoring of clutch system provides enhanced prognostic functionality for AMT system which ensures consistent clutch performance, gear shift quality and timely warning for recalibration, repair and/or replacement of the critical wear and tear parts. Also, systematic analysis of the monitored data provides an accurate diagnosis of a developing fault. Thus, with the advanced control systems in place for AMT, a closed loop feedback based condition monitoring system is modelled for improved diagnostics and prognostics of AMT clutch system.

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“…State-of-the art diagnosis and prognosis methods can e.g. be found in [26][27][28][29][30][31][32]. Below, we specify how we assume the diagnosis and prognosis result to be specified.…”

Section: Assumptionsmentioning

confidence: 99%

Timely condition-based maintenance planning for multi-component systems

Verbert

Schutter

Babuška

2017

Reliability Engineering & System Safety

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Last-minute maintenance planning is often undesirable, as it may cause downtime during operational hours, may require rescheduling of other activities, and does not allow to optimize the management of spare parts, material, and personnel. In spite of the aforementioned drawbacks of last-minute planning, most existing methods plan maintenance activities at the last minute. In this paper, we propose a new strategy for timely maintenance planning in multi-component systems. As a first step, we determine for each system component independently the most appropriate maintenance planning strategy. This way, the maintenance decisions can be tailored to the specific situations. For example, conservative maintenance decisions can be taken when the risk tolerance is low, and maintenance decisions can be made timely when we can accurately predict future degradation behavior. In the second step, we optimize the maintenance plan at the system level. Here, we account for economic and structural dependence with the aim to profit from spreading or combining various maintenance activities. The applicability of the method is demonstrated on a railway case. It is shown how the different cost functions (e.g. costs of maintenance, downtime, and failure) influence the maintenance decisions.

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Kalman filtering based prognostics for automatic transmission clutches

Cited by 34 publications

References 21 publications

Fuel cell remaining useful life prediction and uncertainty quantification under an automotive profile

Fuel cell remaining useful life prediction and uncertainty quantification under an automotive profile

Integrated Prognostics Observer for Condition Monitoring of an Automated Manual Transmission Dry Clutch System

Timely condition-based maintenance planning for multi-component systems

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