Design and optimization of exhaust gas aftertreatment system for a heavy-duty diesel engine

Abstract

Diesel engines meeting the latest emission regulations must be equipped with exhaust gas aftertreatment system, including diesel oxidation catalysts (DOC), diesel particulate filters (DPF), and selective catalytic reduction (SCR). However, before the final integration of the aftertreatment system (DOC+DPF+SCR) and the diesel engine, a reasonable structural optimization of the catalytic converters and a large number of bench calibration tests must be completed, involving large costs and long development cycles. The design and optimization of the exhaust gas aftertreatment system for a heavy-duty diesel engine was proposed in this paper. Firstly, one-dimensional (1D) and three-dimensional (3D) computational models of the exhaust gas aftertreatment system accounting for the structural parameters of the catalytic converters were established. Then based on the calibrated models, the effects of the converter’s structural parameters on their main performance indicators, including the conversion of various exhaust pollutants and the temperatures and pressure drops of the converters, were studied. Finally, the optimal design scheme was obtained. The temperature distribution of the solid substrates and pressure distributions of the catalytic converters were studied based on the 3D model. The method proposed in this paper has guiding significance for the optimization of diesel engine aftertreatment systems.

Keywords

diesel engine / emission / exhaust gas aftertreatment / computational model / optimal design

References

[1] Che MatS, IdroasM Y, HamidM F, et al.. Performance and emissions of straight vegetable oils and its blends as a fuel in diesel engine: A review [J]. Renewable and Sustainable Energy Reviews, 2018, 82: 808-823

[2] LiuJ, SunP, HuangH, et al.. Experimental investigation on performance, combustion and emission characteristics of a common-rail diesel engine fueled with polyoxymethylene dimethyl ethers-diesel blends [J]. Applied Energy, 2017, 202: 527-536

[3] TanP, LiY, ShenH. Effect of lubricant sulfur on the morphology and elemental composition of diesel exhaust particles [J]. Journal of Environmental Sciences, 2017, 55: 354-362

[4] LeeJ, TheisJ R, KyriakidouE A. Vehicle emissions trapping materials: Successes, challenges, and the path forward [J]. Applied Catalysis B: Environmental, 2019, 243: 397-414

[5] MartinN R, KelleyP, KlaskiR, et al.. Characterization and comparison of oxidative potential of real-world biodiesel and petroleum diesel particulate matter emitted from a nonroad heavy duty diesel engine [J]. Science of the Total Environment, 2019, 655: 908-914

[6] TanP, CaoC, HuZ, et al.. A phenomenological model for particle number and size distributions of a diesel engine with a diesel oxidation catalyst [J]. Science of the Total Environment, 2019, 672: 536-550

[7] MyungC L, KoA, ParkS. Review on characterization of nano-particle emissions and PM morphology from internal combustion engines: Part 1 [J]. International Journal of Automotive Technology, 2014, 15(2): 203-218

[8] LeskovjanM, KočíP, MaunulaT. Simulation of diesel exhaust aftertreatment system DOC-pipe-SCR: The effects of Pt loading, PtO_x formation and pipe configuration on the deNO_x performance [J]. Chemical Engineering Science, 2018, 189: 179-190

[9] RenS, WangB, ZhangJ, et al.. Application of dual-fuel combustion over the full operating map in a heavy-duty multi-cylinder engine with reduced compression ratio and diesel oxidation catalyst [J]. Energy Conversion and Management, 2018, 166: 1-12

[10] KangS B, HazlettM, BalakotaiahV, et al.. Effect of Pt: Pd ratio on CO and hydrocarbon oxidation [J]. Applied Catalysis B: Environmental, 2018, 223: 67-75

[11] CorroG, FloresA, Pacheco-AguirreF, et al.. Biodiesel and fossil-fuel diesel soot oxidation activities of Ag/CeO₂ catalyst [J]. Fuel, 2019, 250: 17-26

[12] DaviesC, ThompsonK, CooperA, et al.. Simultaneous removal of NO_x and soot particulate from diesel exhaust by in situ catalytic generation and utilisation of N₂O [J]. Applied Catalysis B: Environmental, 2018, 239: 10-15

[13] VanderW R L, YezeretsA, CurrierN W, et al.. HRTEM study of diesel soot collected from diesel particulate filters [J]. Carbon, 2007, 45(1): 70-77

[14] StamatellouA M, StamatelosA. Overview of diesel particulate filter systems sizing approaches [J]. Applied Thermal Engineering, 2017, 121: 537-546

[15] De-La-TorreU, Pereda-AyoB, MolinerM, et al.. Cu-zeolite catalysts for NO_x removal by selective catalytic reduction with NH₃ and coupled to NO storage/reduction monolith in diesel engine exhaust aftertreatment systems [J]. Applied Catalysis B: Environmental, 2016, 187: 419-427

[16] TanP, WangS, HuZ, et al.. Durability of V₂O₅−WO₃/TiO₂ selective catalytic reduction catalysts for heavy-duty diesel engines using B20 blend fuel [J]. Energy, 2019, 179: 383-391

[17] KuK W, HongJ G, ParkC W, et al.. Effects of various factors on the conversion efficiency of urea solution in a urea selective catalytic reduction system [J]. Energy & Fuels, 2014, 28(9): 5959-5967

[18] CaliskanH, MoriK. Environmental, enviroeconomic and enhanced thermodynamic analyses of a diesel engine with diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) after treatment systems [J]. Energy, 2017, 128: 128-144

[19] YamamotoK, SakaiT. Simulation of continuously regenerating trap with catalyzed DPF [J]. Catalysis Today, 2015, 242: 357-362

[20] ZhangJ, WongV W, ShuaiS, et al.. Quantitative estimation of the impact of ash accumulation on diesel particulate filter related fuel penalty for a typical modern on-road heavy-duty diesel engine [J]. Applied Energy, 2018, 229: 1010-1023

[21] ChenK, MartirosyanK S, LussD. Transient temperature rise during regeneration of diesel particulate filters [J]. Chemical Engineering Journal, 2011, 176–177: 144-150

[22] GillotS, DacquinJ P, DujardinC. High intrinsic cataly-tic activity of CeVO4-based catalysts for ammonia-SCR: influence of pH during hydrothermal synthesis [J]. Top Catal, 2016, 59: 987-995

[23] QiuT, LiX, LeiY, et al.. The prediction of fuel injection quality using a NO_x sensor for the on-board diagnosis of heavy-duty diesel engines with SCR systems [J]. Fuel, 2015, 141: 192-199

[24] SharmaS, FadnavisJ, KhotA. Empirical model to predict melt volume for different range of diesel exhaust fluid tank volumes used in selective catalytic reduction systems [J]. Applied Thermal Engineering, 2018, 129: 916-926

[25] SharmaH, MhadeshwarA. A detailed microkinetic model for diesel engine emissions oxidation on platinum based diesel oxidation catalysts (DOC) [J]. Applied Catalysis B: Environmental, 2012, 127: 190-204

[26] Jia-qiangE, ZuoW, GaoJ, et al.. Effect analysis on pressure drop of the continuous regeneration-diesel particulate filter based on NO₂ assisted regeneration [J]. Applied Thermal Engineering, 2016, 100: 356-366

[27] BaiS, TangJ, WangG, et al.. Soot loading estimation model and passive regeneration characteristics of DPF system for heavy-duty engine [J]. Applied Thermal Engineering, 2016, 100: 1292-1298

[28] QuD, LiJ, LiuY. Research on particulate filter simulation and regeneration control strategy [J]. Mechanical Systems and Signal Processing, 2017, 87: 214-226

[29] TorregrosaA J, SerranoJ R, PiquerasP, et al.. Experimental and computational approach to the transient behaviour of wall-flow diesel particulate filters [J]. Energy, 2017, 119: 887-900

[30] ZhangB, Jia-qiangE, GongJ, et al.. Multidisciplinary design optimization of the diesel particulate filter in the composite regeneration process [J]. Applied Energy, 2016, 181: 14-28

[31] FahamiA R, NovaI, TronconiE. A kinetic modeling study of NO oxidation over a commercial Cu-CHA SCR catalyst for diesel exhaust aftertreatment [J]. Catalysis Today, 2017, 297: 10-16

[32] ÅbergA, WiddA, AbildskovJ, et al.. Parameter estimation and analysis of an automotive heavy-duty SCR catalyst model [J]. Chemical Engineering Science, 2017, 161: 167-177

[33] BaletaJ, MartinjakM, VujanovićM, et al.. Numerical analysis of ammonia homogenization for selective catalytic reduction application [J]. Journal of Environmental Management, 2017, 203: 1047-1061

[34] WeiL, YanF, HuJ, et al.. No_x conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine [J]. Applied Energy, 2017, 206: 959-971

[35] De-La-TorreU, Pereda-AyoB, Gutiérrez-OrtizM A, et al.. Steady-state NH₃-SCR global model and kinetic parameter estimation for NO_x removal in diesel engine exhaust aftertreatment with Cu/chabazite [J]. Catalysis Today, 2017, 296: 95-104