Failure diagnosis and tolerant control method for hydrothermally aged SCR system by utilizing EKF observer and MRAC controller

Hu, Jie; Li, Wei

doi:10.1016/j.energy.2018.05.094

Cited by 20 publications

(9 citation statements)

References 44 publications

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“…Using this model, Hu et al simulated catalyst degradation by scaling the NOx reduction rate (Hu, Zeng, Wei, & Yan, 2017). In another paper, they scaled the NH 3 storage capacity, which is estimated using an Extended Kalman Filter (EKF) (Hu, Zeng, & Wei, 2018) (Jiang, Yan, & Zhang, 2019). It should be noted that none of these aging models have been validated on an actual aged catalyst yet.…”

Section: Intrusive Vs Non-intrusivementioning

confidence: 99%

Diagnostics-oriented Model for Automotive SCR-ASC

Jain¹,

Kuo²,

Meckl

et al. 2023

IJPHM

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This paper presents a diagnostics-oriented aging model for combined Selective Catalytic Reduction (SCR) and Ammonia Slip Catalyst (ASC) system, along with a model-based on-board diagnostic (OBD) method applied to both test-cell data and on-road data from commercial trucks. The key challenge with model development was unavailability of NOx and NH3 measurements between SCR and ASC. Since it would have been very difficult to calibrate both SCR and ASC dynamics without any measurements between SCR and ASC, therefore ASC was modeled using static look-up tables to determine ASC’s NH3 conversion efficiency and its selectivity to NOx and N2O as a function of temperature and flow rate. The traditional three-state single-cell ordinary differential equation (ODE) model was used for SCR. Hot Federal Test Procedure (hFTP) was used to calibrate the model. Cold FTP (cFTP) and Ramped Mode Cycle (RMC) were used for validation. Results show that the SCR-ASC model can capture the aging signatures in tailpipe NOx, NH3, and N2O reasonably well for cFTP, hFTP, and RMC cycles in the testcell data. After slight re-calibration and combining with a simple model for commercial NOx sensor’s cross-sensitivity to NH3, the model works reasonably well for on-road data from commercial trucks. A model-based on-board diagnostic (OBD) method has been presented with enable conditions designed to detect operating conditions suitable for detecting aging signatures, while minimizing false positives and false negatives. The OBD method is applied to both test-cell and real-world truck data with commercial NOx sensors. Results on test-cell data demonstrate the challenges of robust SCR monitoring even on the limited data set used in this work. The model-based enable conditions are shown to be robust but extremely restrictive as the OBD gets enabled at very few points in the test-cell data. Application on truck data showed that the proposed OBD method can be implemented on commercial trucks with limited sensors. In the truck data, the enable conditions were satisfied on many more points than the test-cell data. Results on truck data show encouraging trends between relative degradation level and the number of miles on four trucks. In future work, these trends will be validated using more data from commercial trucks with known aging levels.

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Section: Intrusive Vs Non-intrusivementioning

confidence: 99%

Diagnostics-oriented Model for Automotive SCR-ASC

Jain¹,

Kuo²,

Meckl

et al. 2023

IJPHM

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show abstract

“…In this section, an EKF observer 18,19 coupled to a K c s model for an SCR system to simultaneously estimate the deterioration trend of the N O x and N H 3 emissions and the dynamic of θ N H 3 from the N O x sensor readings is proposed. As shown in Figure 3, the proposed estimation strategy of the SCR system consists of the EKF observer based on the control-oriented model and the segmented K c s model based on T o u t dynamic.…”

Section: Ekf Observer Coupled To the Kcs Modelmentioning

confidence: 99%

Design of extended Kalman filter observer coupled to ammonia cross-sensitivity model for an SCR system

Zhao

Zhang

Wang

et al. 2022

International Journal of Engine Research

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Commercial diesel vehicles that comply the China/EURO VI emission regulations are generally equipped with selective catalytic reduction (SCR) systems for reducing [Formula: see text] emission and [Formula: see text] sensors at its downstream for accurate closed-loop control. However, [Formula: see text] sensors have significant ammonia cross-sensitivity pushing up their readings. Moreover, for the closed-loop control of SCR systems effectively estimating the critical states from the [Formula: see text] sensor readings remains a further challenge. In this paper, an ammonia cross-sensitivity model with segmented sin and quadratic composite functions describing high frequency characteristics is established by analyzing the experimental data of an SCR system. A control-oriented three-states model of an SCR system is established, and based on it an extended Kalman filter (EKF) observer coupled to the ammonia cross-sensitivity model is proposed. The simulation results show that from the [Formula: see text] sensor readings the EKF observer can effectively estimate the deterioration trend of the [Formula: see text] and [Formula: see text] emissions, and describe the dynamic change process of the ammonia coverage rate. The experimental results under the four non-excitation cycles show that the EKF observer can effectively estimate the deterioration trend, that the average estimated accuracy of [Formula: see text] and [Formula: see text] during their deterioration stage can respectively reach 86.16% and 54.87%, and that the observer has better robustness to disturbances from the operating conditions.

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“…As a result, MLP achieved the better performance. Control of the aftertreatment system: Hu et al 26 presented an extended Kalman filter (EKF) observer to identify the ageing state of the SCR and an model reference adaptive controller (MRAC) to improve its control. As main achievement, the accuracy and stability of the control of the SCR system were improved.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous NOx and NH3 slip prediction in a SCR catalyst under real driving conditions including potential urea injection failures

Plá

Piqueras

Bares

et al. 2021

International Journal of Engine Research

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To reach the emission limits imposed by governments and reduce the negative impact on the environment, the use of aftertreatment systems has become essential for internal combustion engine (ICE) based powertrains. In particular, the selective catalytic reduction (SCR) system is a widespread aftertreatment technology with high efficiency for [Formula: see text] abatement which shows complex dynamics and requires urea injection as reducing agent. Current urea injection strategies usually rely on the [Formula: see text] emissions feedback. This work presents a model for the on-line simultaneous prediction of [Formula: see text] and [Formula: see text] emissions after the SCR catalyst, allowing the emissions estimation even in conditions of urea injector failure, when it is not possible to rely on the injector feedback signal. The proposed model is based on state of the art on-board after-treatment instrumentation and proposes an extended Kalman filter (EKF) to combine a data-based model and the analysis of sensor signals to provide a reliable estimation of [Formula: see text] and [Formula: see text] slip. The proposed strategy is experimentally assessed in dynamic driving cycles, such as Worldwide harmonised Light vehicles Test Cycle (WLTC) and Standardised Random Test (RTS). The proposed method is evaluated in standard conditions (without failures) and with urea injection failures of 25% and 120% of the nominal injection amount. As a result, the prediction on [Formula: see text] and [Formula: see text] slip has been improved in all injection failure conditions, by an overall average of 47.8% and 61.8%, respectively, when compared to state-of-the-art control oriented models (physically based zero dimensional model or data-based).

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Failure diagnosis and tolerant control method for hydrothermally aged SCR system by utilizing EKF observer and MRAC controller

Cited by 20 publications

References 44 publications

Diagnostics-oriented Model for Automotive SCR-ASC

Diagnostics-oriented Model for Automotive SCR-ASC

Design of extended Kalman filter observer coupled to ammonia cross-sensitivity model for an SCR system

Simultaneous NOx and NH3 slip prediction in a SCR catalyst under real driving conditions including potential urea injection failures

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