Diagnostics-oriented Model for Automotive SCR-ASC
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.
Selective Calatytic Reduction, Ammonia Slip Catalyst, Diagnostics, Modeling
Carb approves heavy-duty obd amendments, adopts real nox and co2 tracking [Computer software manual]. (2018 (accessed Nov 30, 2021)). (https://dieselnet.com/news/2018/11carb.php)
Chen, P., & Wang, J. (2016). Estimation and adaptive nonlinear model predictive control of selective catalytic reduction systems in automotive applications. Journal of Process Control, 40, 78–92.
Daya, R., Desai, C., & Vernham, B. (2018). Development and validation of a two-site kinetic model for nh 3-scr over cu-ssz-13. part 1. detailed global kinetics development based on mechanistic considerations. Emission Control Science and Technology, 4(3), 143–171.
Daya, R., Joshi, S. Y., Luo, J., Dadi, R. K., Currier, N. W., & Yezerets, A. (2020). On kinetic modeling of change in active sites upon hydrothermal aging of cu-ssz-13. Applied Catalysis B: Environmental, 263, 118368.
Devarakonda, M., Parker, G., Johnson, J. H., Strots, V., & Santhanam, S. (2008). Adequacy of reduced order models for model-based control in a urea-scr aftertreatment system (Tech. Rep.). SAE Technical Paper.
Emissions Compliance, A. R., & Science Division, C. (2018 (accessed Nov 30, 2021)). Workshop for 2018 hd obd regulations update [Computer software manual]. (https://ww2.arb.ca.gov/sites/default/files/classic/msprog/obdprog/hdobd 2017wspresentation.pdf)
Hsieh, M.-F. (2010). Control of diesel engine urea selective catalytic reduction systems (doctoral dissertation). The Ohio State University.
Hsieh, M.-F., & Wang, J. (2011). Development and experimental studies of a control-oriented scr model for a two-catalyst urea-scr system. Control Engineering Practice, 19(4), 409–422.
Hu, J., Zeng, J.,&Wei, L. (2018). Failure diagnosis and tolerant control method for hydrothermally aged scr system by utilizing ekf observer and mrac controller. Energy, 156, 103–121.
Hu, J., Zeng, J., Wei, L., & Yan, F. (2017). Improving the diagnosis accuracy of hydrothermal aging degree of v2o5/wo3–tio2 catalyst in scr control system using an gs–pso–svm algorithm. Sustainability, 9(4), 611.
Jiang, K., Yan, F., & Zhang, H. (2019). Hydrothermal aging factor estimation for two-cell diesel-engine scr systems via a dual time-scale unscented kalman filter. IEEE Transactions on Industrial Electronics, 67(1), 442–450.
Ma, Y., &Wang, J. (2017). Observer-based estimation of aging condition for selective catalytic reduction systems in vehicle applications. Journal of Dynamic Systems, Measurement, and Control, 139(2), 021002.
Matsumoto, A., Furui, K., Ogiso, M., & Kidokoro, T. (2016). Model-based obd logic utilizing adsorption and desorption model of nh 3 in scr catalyst (Tech. Rep.). SAE Technical Paper.
Nova, I., & Tronconi, E. (2014). Urea-scr technology for denox after treatment of diesel exhausts. Springer.
Ofoli, A. R. (2014). Experimental demonstration of ammonia storage and slip modeling with control for an scr aftertreatment system. IEEE Transactions on Industry Applications, 50(4), 2342–2348.
Romijn, M., & Kumar, U. (2018 (accessed Nov 30, 2021)). California hd obd program—summary of 2018 amendments [Computer software manual]. (https://dieselnet.com/news/2018/12obd.php)
Schär, C. M., Onder, C. H., Geering, H., & Elsener, M. (2004). Control-oriented model of an scr catalytic converter system (Tech. Rep.). SAE Technical Paper.
Schar, C. M., Onder, C. H., & Geering, H. P. (2006). Control of an scr catalytic converter system for a mobile heavy-duty application. IEEE Transactions on Control Systems Technology, 14(4), 641–653.
Shrestha, S., Harold, M. P., Kamasamudram, K., Kumar, A., Olsson, L., & Leistner, K. (2016). Selective oxidation of ammonia to nitrogen on bi-functional cu–ssz-13 and pt/al2o3 monolith catalyst. Catalysis Today, 267, 130–144.
Stadlbauer, S., Waschl, H., & del Re, L. (2015). Adaptive scr model for mpc control including aging effects (Tech. Rep.). SAE Technical Paper.
Upadhyay, D., & Van Nieuwstadt, M. (2002). Modeling of a urea scr catalyst with automotive applications. In Asme international mechanical engineering congress and exposition (Vol. 36290, pp. 707–713).
Yuan, X., Liu, H., & Gao, Y. (2015). Diesel engine scr control: current development and future challenges. Emission Control Science and Technology, 1(2), 121–133.
Zhao, J., Chen, Z., Hu, Y., & Chen, H. (2015). Urea-scr process control for diesel engine using feedforward-feedback nonlinear method. IFAC-PapersOnLine, 48(8), 367–372.