A novel approach for diesel particulate filter diagnostic using resistive sensor

Youssef, Bilal

doi:10.1109/aset.2018.8379852

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…It is particularly suitable for nonlinear systems with short available computation time [32][33][34] and allows to reduce dispersions impact. 35,36 The signature based trapped mass estimation scheme exclusively uses cylinder pressure sensor without the need for additional unknown variables or the use of mathematical models. It provides a comprehensive and practical trapped mass (TM) estimator on a cycle by cycle basis with a light amount of calibration efforts enabling an easy use for industrial applications.…”

Section: Introductionmentioning

confidence: 99%

“…The signature approach provides an estimation method that uses the observations to deduce unknown parameters that are difficult to derive in analytical way. It is particularly suitable for nonlinear systems with short available computation time 32‐34 and allows to reduce dispersions impact 35,36 . The signature based trapped mass estimation scheme exclusively uses cylinder pressure sensor without the need for additional unknown variables or the use of mathematical models.…”

Section: Introductionmentioning

confidence: 99%

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Trapped mass estimation in automotive diesel engines based on in‐cylinder pressure signal projection

Youssef

2020

Adaptive Control & Signal

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Cylinder pressure signal provides key feedback information that allows for several engine monitoring and control capabilities. During the last few years, the use of cylinder pressure traces for advanced combustion strategies has become the focus of several research works. This is primarily due to the availability of reliable and inexpensive cylinder pressure sensors with expected durability that meets the vehicle lifetime. In this context, several approaches have been proposed to determine the engine trapped mass from the cylinder pressure measurements. A recent innovative approach for trapped charge determination based on a two-dimensional graphical signature is proposed in a previous work. The resulting estimator uses cylinder pressure signal as a unique input and allows to deduce the trapped mass on a cycle by cycle basis in steady and transient operating conditions. It has been validated in a wide range of engine operating conditions using instrumentation and industrial cylinder pressure sensors. This paper provides a theoretical framework and in-depth analysis for the signature based trapped mass estimator. A state-space model for in-cylinder conditions during the compression phase that complies with the signature modeling structure is developed. Extensive numerical investigations using an experimentally validated simulation platform are then performed. The objective is to select the optimal signature generation interval that reduces the impact of cycle to cycle fluctuations in terms of intake valve closing temperature and polytropic index. The obtained results are promising and clearly show the performance and robustness of the signature based trapped mass estimator that can provide relevant feedback information for adaptive engine control systems. It can be easily implemented for real-time monitoring and control in industrial automotive applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Trapped mass estimation in automotive diesel engines based on in‐cylinder pressure signal projection

Youssef

2020

Adaptive Control & Signal

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Review: Soot (Particulate Matter) Sensor with an application to control pollution in diesel exhaust

Kulkarni¹,

Chorage²

2019

2019 5th International Conference on Computing, Communication, Control and Automation (ICCUBEA)

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Innovative Model-Free Onboard Diagnostics for Diesel Particulate Filter

Youssef

2023

SAE Int. J. Engines

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<div>Recent legislations require very low soot emissions downstream of the particulate filter in diesel vehicles. It will be difficult to meet the new more stringent OBD requirements with standard diagnostic methods based on differential sensors. The use of inexpensive and reliable soot sensors has become the focus of several academic and industrial works over the past decade. In this context, several diagnostic strategies have been developed to detect DPF malfunction based on the soot sensor loading time. This work proposes an advanced online diagnostic method based on soot sensor signal projection. The proposed method is model-free and exclusively uses soot sensor signal without the need for subsystem models or to estimate engine-out soot emissions. It provides a comprehensive and efficient filter monitoring scheme with light calibration efforts. The proposed diagnostic algorithm has been tested on an experimentally validated simulation platform. 2D signatures are generated from soot sensor signal for nominal and faulty configurations. Gaussian dispersions on soot estimator (30%) and sensor model (15%) have been considered. Based on a statistical analysis, a relevant threshold is defined satisfying a compromise between non-detection and false alarm rates. The selected threshold is then used for online DPF diagnostic using NEDC cycle. The obtained results are promising and clearly show the performance of the proposed method in terms of non-detection and false alarm rates. The resulting diagnostic scheme can be easily integrated in the ECU for onboard DPF monitoring.</div>

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A novel approach for diesel particulate filter diagnostic using resistive sensor

Cited by 3 publications

References 8 publications

Trapped mass estimation in automotive diesel engines based on in‐cylinder pressure signal projection

Trapped mass estimation in automotive diesel engines based on in‐cylinder pressure signal projection

Review: Soot (Particulate Matter) Sensor with an application to control pollution in diesel exhaust

Innovative Model-Free Onboard Diagnostics for Diesel Particulate Filter

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