Simulation Study of Ammonia Storage Characteristics of Selective Catalytic Reduction for Diesel Engines

Abstract

Non-road machinery is very important, but non-road machinery has problems such as working under complex operating conditions. Agricultural machinery is an important type of non-road machinery, which mainly relies on diesel engines due to their high fuel efficiencies. The exhaust temperature of agricultural machinery changes drastically under different working conditions. This article aims to research on pollution control of non-road machinery. Among the exhaust after treatment technologies, selective catalytic reduction (SCR) technology is a very important method to reduce NO_x. In this study, a series of tests was conducted to investigate the effects of temperature and exhaust gas mass flow on the NO_x conversion and dynamic ammonia storage space distribution characteristics in simulation models. The genetic algorithm, a kind of global optimization algorithm that can avoid local optimization, was used in the parameter identification process. The simulation results showed that the ammonia storage capacity of SCR catalyst decreases as the temperature of SCR increases. With the decrease in temperature, the NH₃ desorption rate gradually decreased. An uneven distribution of ammonia storage similar to the shape of ɛ was observed in the simulation and this kind of uneven distribution is obvious at low temperature. The effective area of the catalyst is near the inlet of the catalyst. This work presents an approach to help figure out the details in the ammonia storage process. This work provides information about the dynamic ammonia storage characteristics and guide for better SCR design.

Introduction

Diesel engines have attracted significant attention in recent years mainly due to their higher fuel efficiencies and lower CO₂ emissions compared to gasoline engines. However, one of the drawbacks of diesel engines is the higher NO_x emissions. These NO_x emissions have health effects, such as causing respiratory tract infections and asthma, and cause environmental problems, like acid rain and photochemical smoke (Knecht, 2008). Various methods have been adopted to reduce NO_x emissions in diesel engines, mainly including in-engine purification technologies and exhaust aftertreatment technologies (Raptotasios et al., 2015; Hosseini et al., 2017; Liu et al., 2019). In-engine purification technologies include the optimization of the fuel injection system, the optimization of the combustion chamber, intercooling technology, and exhaust gas recirculation (Park and Yoon, 2015; Yoo, 2015). Exhaust aftertreatment technologies mainly include selective catalytic reduction (SCR) technology, lean NO_x trap technology, NH₃ oxidation catalytic technology, and lean NO_x catalyst technology (Aswani et al., 2004; Zhao et al., 2011; Qian et al., 2017).

With future emission legislation becoming more stringent, SCR technology with a 32.5% aqueous urea solution (AdBlue) introduced to the diesel exhaust to provide reductant for NO_x reduction reactions is currently used to meet the emission standards. The injected urea is converted to ammonia by three different processes: AdBlue evaporation, urea decomposition, and isocyanic acid (HNCO) hydrolyzation. The ammonia will be adsorbed onto the SCR catalyst to react with NO_x. SCR has expanded into worldwide use. Furthermore, SCR technology will be required for many applications. However, too much urea will lead to tailpipe ammonia slip. The amount of tailpipe ammonia slip must be minimized, while trying to raise the NO_x conversion efficiency. There are a series of factors affecting the SCR performance.

Xu et al. (2018) investigated the impact of a series of urea injection and mixing modules on NO_x conversion through several tests. In engine dynamometer tests, the NH₃ distribution was examined (Xu et al., 2018). It is widely recognized that the achievable NO_x conversion can be sensitive to the spatial distribution of NH₃-to-NO_x ratio (ANR) at the converter inlet (McKinley et al., 2010). Oesterle et al. (2008) concluded that the maldistribution of NH₃ can affect the SCR performance and the service life of the catalyst. In the automotive industry, the ammonia distribution on the catalyst surface has an important impact on the NO_x conversion of SCR. The maximum conversion was found to be dependent on the distribution of NO_x and NH₃ on the surface in a vanadium-based SCR catalytic converter (Johansson et al., 2008). Maldistribution results in a decrease in the NO_x conversion efficiency and increase in the ammonia slip (Vikas et al., 2012). Karlsson et al. (2006) illustrated that it is important to ensure that the ammonia profiles match the NO_x profile for good NO_x conversion, while evaluating the ammonia distribution of different mixer solutions. A mismatch will definitely have significant adverse effects on the SCR NO_x reduction performance or lead to ammonia slip (Karlsson et al. 2006).

Hsieh et al. (2011) argued that unexpected ammonia slip can occur if the ammonia adsorption capability is not well estimated in SCR modeling. Tang et al. (2015) conducted experiments and found that the reaction rate will be higher when the concentration of ammonia on the surface of the catalyst increases. Many SCR models have been established for both Cu-zeolite and Fe-zeolite catalysts. A single ammonia storage site was used in most of the published models (Markatou et al., 2011; Watling et al., 2011; Colombo et al., 2012). Colombo et al. (2012) developed a new dual-site approach to establish a new model for obtaining an accurate description of the NH₃ adsorption/desorption over the entire 50–550°C temperature window. Song et al. (2014) investigated the effects of maldistribution of NH₃ on SCR performance using a one-dimensional (1D) model for a Cu-zeolite SCR and concluded that the SCR inlet NH₃ maldistribution had an adverse effect on NO_x reduction efficiency over a surrogate Heavy-duty federal test procedure cycle.

Several studies have suggested that the catalyst ammonia adsorption capability can change with temperature, and the ammonia adsorption/desorption reactions are highly related to the SCR storage capacity (Ciardelli et al., 2004; Willems et al., 2007; Joo et al., 2008). Olsson et al. (2015) have developed a kinetic model for ammonia-SCR over a Cu/SSZ-13 catalyst and propose a three-site model. The model using these three storage sites could well describe the ammonia Temperature Programmed Desorption experiments, with storage at 50°C and 150°C. When using the full model, including the N₂O mechanism, the model was capable of describing all experimental features for NO, NH₃, and N₂O across the entire temperature interval (100–600°C) (Olsson et al. 2015). Gong et al. (2016) propose a heterogeneous single-site model considering the heterogeneity of ammonia storage sites. This model more accurately predicts ammonia storage in the temperature window of 150–400°C.

Song et al. (2013) pointed out that the stored NH₃ participates in all SCR reactions, so the ammonia storage capability of the catalyst has a significant impact on the reaction rates of SCR reactions. The ammonia storage at different axial locations of the SCR system can be predicted using their proposed model, which is of great value for control applications (Song et al., 2013). Kalyankar et al. (2015) developed two predictive modeling approaches to assess the effect of ANR nonuniformity on the SCR + ammonia slip catalyst performance. They found that the ANR uniformity is of great significance for NO_x conversion. The transient de-NO_x efficiency increased with increase in the weighted uniformity index, which was proposed in this work as being more representative of a transient cycle (Kalyankar et al., 2015). Lin and Chen (2019) established a new SCR platform and conducted simulations with it to investigate the impact of ammonia storage nonuniformity on SCR performance. To estimate the ammonia storage coverage ratio uniformity, a novel diagnostic methodology was introduced and verified under the US06 cycle (Lin and Chen, 2019).

Many studies have been conducted on SCR technology. Most of these studies focused on the NO_x conversion efficiency, control strategies, and ammonia tailpipe slip of the SCR. Studies on the temporal and spatial distribution of NH₃ in the SCR would be useful for studying the chemical reaction process inside the SCR in detail. Ammonia storage nonuniformity has an adverse effect on the SCR performance. For urea-based SCR systems, the ammonia concentrations in the radial and axial directions are difficult to detect because no exhaust sensor can directly measure the ammonia storage on the catalyst surface. The effect of NO_x and ammonia uniformity at the SCR catalyst entry on the NO_x conversion and ammonia slip is of interest. In this article, the influence of the SCR inlet temperature and the influence of the initial ANR on the dynamic characteristics of the spatial distribution of ammonia storage and the NOx conversion efficiency in the SCR are studied in simulations. A diesel engine, a supporting SCR system, and the professional engine Computational Fluid Dynamics simulation software AVL FIRE and AVL BOOST were used to study the spatial distribution characteristics of NH₃ inside the SCR over time, the results of which can be used to optimize the SCR system. The kinetics parameters are adjusted by an automatic parameter optimization procedure in AVL Boost software. The genetic algorithm, a kind of global optimization algorithm that can avoid local optimization, was used in the parameter identification process to optimize the parameters. The numerical model, based on SCR kinetics, is validated with experiment data.

In this work, a non-road steady cycle (NRSC) test was conducted to verify the accuracy of the SCR 1D model and the effects of the inlet temperature of SCR on the dynamic characteristics of the ammonia storage space distribution at different times were studied. There are not many studies focused on the dynamic characteristics of the ammonia storage space distribution. The simulation can be used to support design decisions and shorten the overall development process of SCR systems.

Experiment and Methods

Experimental equipment

This study was conducted in accordance with the declaration of China, and the protocal for this original articles was approved by the Institutional Review Board. The study focused on a vanadium-based SCR catalyst from an exhaust system equipped with an agricultural supercharged intercooled diesel engine (Fig. 1).

FIG. 1.

Schematic diagram of the experimental system. (1) Intercooler. (2) AVL 500/1.5-4Rx electric dynamometer. (3) Computer program control system. (4) Diesel engine. (5) Data acquisition and terminal. (6) SCR. (7) AMA i60 gas analyzer. SCR, selective catalytic reduction.

The parameters of the SCR that is used in the experiment are shown in Table 1. The specification of the engine that is used in the experiment is described in Table 2. The test equipment is listed in Table 3.

Table 1.

Specifications of the Selective Catalytic Reduction System

Parameter	Specification
Diameter × length (mm × mm)	Ø330.2 × 203.2
Volume (L)	21.73
Cell density (cell/in²)	400
Catalyst loading (g/ft³)	3

Table 2.

Engine Specifications

Project	Specification
Engine type	In-line four cylinders, intercooled, turbocharged
Fuel supply system	Common rail
Displacement (L)	2.8
Backpressure (kPa)	7.8
Rated power (kW)	66
Rated speed (r/min)	2,400
Max torque (N · m)	332
Idle speed (r/min)	800

Table 3.

Detailed Information of Test Equipment

Equipment	Model	Manufacturer
Electric dynamometer	500/1.5–4Rx	AVL
Exhaust gas analyzer	AVL AMA i60	AVL
NH₃ analyzer	LDS-6	SIEMENS
Fuel pressure regulating module	PR3	AVL
Fuel temperature regulating module	753C	AVL
Engine temperature control device	KWK-02A	Claude machinery
Air cooler	KL-21	Kawasaki machinery
Fuel consumption meter	753S	AVL

Experiment data

In the NRSC, the engine speed, engine torque, and NO_x concentration at the SCR outlet from 0 to 4,800 s are shown in Fig. 2. The NO_x concentration at the SCR outlet changes as the torque and speed of the engine change from 0 to 4,800 s in the NRSC test.

FIG. 2.

The engine speed, engine torque, and NO_x concentration at the SCR outlet in NRSC. NRSC, non-road steady cycle.

Figure 2 shows that the NO_x concentration at the SCR outlet was high when the engine load was high. There was a relationship between the NO_x concentration at the SCR outlet and the torque of the diesel engine. Around 2,500 s, the NO_x concentration at the SCR outlet increased heavily. That was because the torque of the engine increased suddenly, leading to an increase in fuel injection and an increase in temperature. The high temperature of the diesel engine can easily cause NO_x.

AVL AMA i60 gas analyzer was used to measure the NO_x concentration in the experiment test. The NO_x concentration at the inlet and outlet of the SCR is measured by the AVL AMA i60 gas analyzer; the NO_x conversion efficiency is defined as

(the NO_x concentration at the inlet of the SCR − the NO_x concentration at the outlet of the SCR)/the NO_x concentration at the inlet of the SCR.

Figure 3 shows the NO_x conversion efficiency and the exhaust temperature in NRSC. It can be concluded that the NO_x conversion efficiency has a relationship with the exhaust temperature, which was mainly due to the fact that the activity of the SCR catalyst increased with the temperature in the temperature range in the experiments.

FIG. 3.

Exhaust temperature and NO_x conversion efficiency in NRSC.

Figure 4 shows the NO concentration and NO₂ concentration in NRSC. The NO₂ concentration was far less than the NO concentration. This result was in line with the fact that the NO concentration accounted for almost 90% of the diesel engine exhaust and NO₂ concentration accounted for almost 10% of the diesel engine exhaust in most situation.

FIG. 4.

NO concentration and NO₂ concentration in NRSC.

Around 2,500 s, the NO₂ and NO concentration increased rapidly, which was because the engine torque increased and the engine speed decreased, leading to rapid increase in exhaust temperature. At high temperature, engines generate nitrogen oxides easily, which was why the NO₂ and NO concentration increased rapidly around 2,500 s.

Model description

To calculate the NO_x concentration at the SCR outlet in the simulation, many equations such as the solid energy balance equation, the species conservation equation, the energy balance equation of the gas phase, the solid phase energy balance equation, and the SCR reaction equations were included in the model.

The main assumptions in this study are as follows: (1)

Ignore the effect of H₂O on the SCR reaction;

(2)

In the SCR, the oxidation of NO is ignored and the reaction of NH₃ and O₂ is considered;

(3)

The SCR conforms to the Eley-Rideal reaction mechanism, that is, the gas phase NO reacts with strongly adsorbed NH₃, and the process of NH₃ adsorption and desorption is considered;

(4)

Suppose that the urea aqueous solution is completely evaporated and decomposed into NH₃;

(5)

Assuming that the fluid flow in the channel is 1D steady flow, and the gas phase components are evenly distributed at the inlet cross-section of the catalyst model channel;

(6)

Assuming that the conditions of each single channel of the catalyst model are exactly the same, there is no radial fluid velocity gradient and material concentration gradient in the normal section perpendicular to the fluid flow direction;

(7)

Ignore the heat transfer between the catalyst carrier and the external environment, assuming that the model is insulated from the outside.

Based on these assumptions, a 1D high-fidelity model and a three-dimensional (3D) model were built up for simulating species transport from the bulk fluid stream to the solid surface and chemical reactions that occur inside the porous catalyst, considering both the physical transport and chemical kinetic steps.

Due to chemical reactions, the number of moles in the SCR changes, but their overall mass remains constant. Therefore, mass balances are often preferred.

The models describe a system consisting of two different phases (gas and solid substrate) with two different volumes. The volume of the gas phase in this system is given by means of an overall volume fraction. This volume fraction of gas phase in the entire system is defined as follows: $ε_{g} = \frac{V_{g}}{V}$ (1)

where ɛ_g is the volume fraction of the phase g(as) in the entire volume V.

The volume of the solid phase V_s is evaluated by $V_{s} = (1 - ε_{g}) V = ε_{s} V$ (2)

If one phase comprises several different species, the density of the entire phase ρ_g is the sum of the densities of all different species k in it; k is the species index. $P_{g} = \sum_{k}^{K} ρ_{k, g}$ (3)

The mass fraction w_k,g of one species in a system is defined as follows: $w_{k, g} = \frac{ρ_{k, g}}{ρ_{g}}$ (4)

where ρ_k,g is the density of the species and ρ_g is the total density.

In the models, the ideal gas law is applied: $P_{g} = \frac{p_{g}}{R T_{g}} M G_{g}$ (5) $M G_{g} = \frac{1}{\sum_{k}^{K} \frac{w_{k, g}}{M G_{k, g}}}$ (6)

where ρ_g is the mass density, p_g is the pressure, MG_g is the total molar mass, which is a function of the composition of the different species k in the considered phase, T_g is the temperature, R is the ideal gas constant, and MG_k,g represents the molar mass of species k in the gas phase.

Solid energy balance equation:

where V_s is the solid volume part of the cell, ρ_s is solid density, c_p,s is the specific heat of the solid phase, T_g and T_s are the gas and solid temperature, t is the time, V is the volume of a computational cell, A_s is the surface of the solid part in a computation cell, K is the anisotropic heat conduction matrix, n is the normal vector to the surface cell, S is the surface of the solid part of a computational cell, k_h is the gas-solid heat transfer coefficient, a_trans is the geometric surface area per unit volume, and S_r is the chemical reaction source.

The chemical reaction source is given by $S_{r} = \sum_{k = 1}^{K} ṙ_{k} H_{f k | 298 K} V$ (8)

where $ṙ_{k}$ is the reaction rate of species k, $H_{f k | 298 K}$ is the formation enthalpy of species k at 298 K, and V is the volume of a computational cell.

The sources in the species conservation equations are given by $S_{{\tilde{w}}_{k}} = ṙ_{k} M G_{k} V$ (9)

The entire converter can be represented by one single channel under the assumption that radial transport effects are small compared to the heat transport in axial direction.

The continuity equation of the gas phase is as follows: $\frac{\partial ρ_{g}}{\partial t} = \frac{\partial ρ_{g} ν_{g}}{\partial z}$ (10)

where ρ_g the density of the gas phase, t is the time, $ν_{g}$ is the interstitial gas velocity, and z is the spatial coordinate in axial direction.

The momentum conservation equation is given by the steady-state Darcy equation: $\frac{\partial p_{g}}{\partial z} = A_{D} ν_{g}$ (11)

where p_g is the pressure of the system. The Darcy constant A_D can be described by: $A_{D} = φ \frac{ν_{g}}{2} \frac{ρ_{g}}{d_{h y d}} ς$ (12)

d_hyd represents the hydraulic channel diameter and $ς$ is a friction coefficient. The factor $φ$ is called Fanning friction factor and takes into account deviations from round channel cross-sections.

The species conservation equation is as follows: $\begin{matrix} E_{g} \frac{\partial ρ_{g} w_{k, g}}{\partial t} & = ε_{g} \frac{\partial ρ_{g} w_{k, g} ν_{g}}{\partial z} + ε_{g} \frac{\partial}{\partial z} (ρ_{g} D_{e f f} \frac{\partial w_{k, g}}{\partial z}) \\ + M G_{k, g} \sum_{i}^{I} ν_{I, k} ṙ_{i} (c_{k}^{L}, T_{s}) \end{matrix}$ (13)

where $D_{e f f}$ is an effective diffusion coefficient and $ṙ_{i} (c_{k}^{L}, T_{s})$ represents the molar reaction rate of the catalytic surface reactions with their stoichiometric coefficients $ν_{I, k}$ .

The energy balance of the gas phase is as follows:

where h_k is the total enthalpy of the component k, λ_g is the thermal conductivity, k_h is the gas–solid heat transfer coefficient, and Δh_i is heat of reaction I; this heat is released in the solid phase and converted into the gas phase.

The solid phase energy balance equation is as follows: $\begin{matrix} (1 - ε_{g}) ρ_{s} \frac{\partial (c_{p, s} T_{s})}{\partial t} & = (1 - ε_{g}) \frac{\partial}{\partial z} (λ_{s} \frac{T_{s}}{\partial z}) - a_{t r a n s} k_{h} (T_{s} - T_{g}) \\ + \sum_{i}^{I} Δ h_{i} ṙ_{i} (c_{k}^{L}, T_{s}) + {\dot{q}}_{R a d} \end{matrix}$ (15)

where λ_s is the thermal conductivity of the catalyst wall and ${\dot{q}}_{R a d}$ represents a heat loss to the surrounding.

Under the assumption of quasi steady-state conditions, the rates of the catalytic surface reactions balance the diffusive transport from the bulk gas to the surface. Thus, the molar surface concentration $c_{k}^{L}$ of the component j can be evaluated using $a_{t r a n s} k_{k, m} (c_{k}^{L} - c_{k, g}) = \sum_{i}^{I} ṙ_{i} (c_{k}^{L}, T_{s})$ (16)

where $c_{k, g}$ is the molar concentration of species k in the bulk gas and $k_{k, m}$ is the mass transfer coefficient of the individual species.

The amount of a certain species stored on the surface is represented by a surface fraction θ. The conservation of this species on the surface is accounted for by the following equation: $\frac{\partial θ_{k}}{\partial t} (Θ a_{t r a n s}) = ṙ_{k} k = 1 \dots \dots . . K_{s t o r e}$ (17)

where the product $Θ a_{t r a n s}$ of the side density $Θ$ and the geometrical reaction surface $a_{t r a n s}$ are a measure for the entire storage capacity.

The models calculate the transfer coefficients for mass and heat inside the catalytic monoliths based on empirical relationships for Nusselt and Sherwood numbers. One researcher (Perry, 1942) suggests the following equations should be applied: $N u = 1 . 86 {(R e P r \frac{d}{l})}^{\frac{1}{3}}$ (18)

where Re is the Reynolds number, Pr is the Prandtl number, Sc is the Schmidt number, l is the channel length, and d is the channel diameter.

A 1D high-fidelity model with mass transfer, heat transfer, and a global reaction mechanism was developed for the vanadium-zeolite SCR. The model was calibrated and validated for both the reactor and engine experimental data.

The following reactions are considered (Wurzenberger and Wanker, 2005): $R 1 : H C N O + H_{2} O \to N H_{3} + C O_{2}$ $R 2 : 4 N H_{3} + 4 N O + O_{2} \to 4 N_{2} + 6 H_{2} O$

R 3 : 4 N H_{3} + 2 N O + 2 N O_{2} \to 4 N_{2} + 6 H_{2} O

R 4 : 8 N H_{3} + 6 N O_{2} \to 7 N_{2} + 12 H_{2} O

R 5 : 4 N H_{3} + 3 O_{2} \to 2 N_{2} + 6 H_{2} O

The ammonia storage reaction includes the following reactions and the rates of the reactions are described. The model considers the adsorption and desorption of ammonia at the solid surface and is dedicated to resolve transient operating conditions. The dynamic ammonia storage is important for NO_x conversion and we take it into consideration in the model. The stored amount of ammonia influences different SCR reactions. $R_{a} : N H_{3} + S \to N H_{3} (S)$

R_{d} : N H_{3} + S \to N H_{3} + (S)

The rate expressions for NH₃ adsorption and desorption are described as follows: $r_{a} = k_{a} c_{N H_{3}} (1 - θ_{N H_{3}})$ (20) $r_{d} = k_{d} exp [- \frac{E_{d}}{R T} (1 - α_{1} θ_{N H_{3}})] θ_{N H_{3}}$ (21)

k_a is adsorption rate constant, $c_{N H_{3}}$ is the NH₃ concentration, $θ_{N H_{3}}$ is the NH₃ converge, K_d is adsorption rate constant, α₁ is a model constant, which describes the dependence of desorption activation energy E_d on NH₃ converge $θ_{N H_{3}}$ , R is the ideal gas constant, and T is the temperature.

All simulations began with no NH₃ storage in the SCR catalyst. The experiment was carried out on a small agricultural machinery diesel engine in NRSC. The test operation points are shown in Table 4.

Table 4.

Non-Road Diesel Steady Cycle Operation Points

Number	N (r/min)	Load (%)
1	2,400	100
2	2,400	75
3	2,400	50
4	2,400	10
5	1,680	100
6	1,680	75
7	1,680	50
8	800	0

Ei, activation energy of the reaction I, and K, the frequency factor, are selected as the parameters to be identified. To improve the accuracy of the models, the AVL Design Explorer tool was applied to optimize the parameters. After the model parameters were identified by the AVL Design Explorer tool, the NO_x conversion of the SCR was compared in the tests and the simulation.

Genetic algorithm is an algorithm that simulates biological evolution mechanism. It has strong global optimization capabilities. It is a simple and easy method that is suitable for multiobjective optimization. The number of parameters to be identified in the SCR model is large, meaning a multiobjective optimization. Based on this, the genetic algorithm in the AVL Design Explorer tool is selected as the optimization algorithm. The genetic algorithm is suitable for multiobjective optimization and can avoid local optimization, while being used in the parameter identification process.

The genetic algorithm is needed to optimize parameters that include Ei and K. These factors directly affect the DeNOx capability of the SCR catalyst under different conditions and have an influence on the internal reaction rate of SCR.

The parameters of the genetic algorithm used in the parameter identification process are shown in Table 5. With the aid of the AVL Design Explorer platform, genetic algorithm is selected to optimize the simulation model. Genetic algorithm is a global optimization method based on natural biological evolution theory. The values of the genetic algorithm parameters in Table 5 are set in the AVL Design Explorer platform, while applying genetic algorithm. The NO_x concentration at the outlet of the SCR can reflect the performance of the SCR. The NO_x concentration is selected as the target curve in the AVL Design Explorer platform, and the average value of the variance of the NO_x concentration at the outlet of the SCR in the simulation and the experiment is selected as the objective function.

Table 5.

Genetic Algorithm Parameters

Parameter	Meaning	Value
Algebra	Optimized algebra	25
Population size	Number of individuals per generation	50
Crossover probability	In the range [0, 1]	0.65
Cross probability distribution	In the range [5, 20]	15
Mutation probability	In the range [0, 1]	0.06
Mutation probability distribution	In the range [5, 50]	15

The GA is used to optimize parameters Ei and K in the 1D model. The parameters listed in Table 5 are the internal results of the GA. Based on these results in the 1D model, the 3D SCR catalyst model was established in the AVL FIRE software. The simulation of the storage was obtained in the 3D SCR catalyst model.

The SCR NO_x conversion comparison between the model and experiments is shown in Fig. 5.

FIG. 5.

The SCR NO_x conversion comparison between the model and experiments after the parameters were identified.

The simulated values of the SCR NO_x conversion efficiencies of the model after the model parameters were identified were similar to the experimental values overall. The average difference between the two was about 5%. Thus, the SCR 1D model was deemed sufficiently accurate.

The influence of the SCR inlet temperature and the exhaust gas mass flow at the SCR inlet on the NO_x conversion of SCR and tailpipe ammonia slip was studied in the model.

Results and Discussion

Effect of the inlet temperature of SCR catalyst on conversion efficiency

In the model, the exhaust gas mass flow was set as 480 kg/h, the ANR at the inlet of the SCR system was set as 1:1, and the volume fractions of NH₃ and NO_x were 750 × 10⁻⁶.

To illustrate how the conversion efficiency of NO_x changes when temperature varied, simulations were conducted. The relationship between the NO_x conversion and the SCR inlet temperature is shown in Fig. 6.

FIG. 6.

Relationship between the NOx conversion of the SCR, volume fraction of NH₃ at the SCR outlet, and the SCR inlet temperature.

The NO_x conversion efficiency first increased and then decreased when the temperature increased within the range of 100°C and 550°C. The catalyst basically lost its catalytic reaction ability when the temperature exceeded 550°C.

Because the NO_x conversion was low when the temperature was lower than 100°C or higher than 450°C, the simulation to examine the relationship between the volume fraction of NH₃ at the outlet of the SCR system and temperature was conducted within a temperature range of 100°C and 450°C. The relationship between the volume fraction of NH₃ at the SCR outlet and the SCR inlet temperature is shown in Fig. 6.

As shown in Fig. 6, the volume fraction of NH₃ at the outlet of the SCR system decreased first and then increased with an increase in temperature. When the inlet temperature was 150°C, the volume fraction of NH₃ at the outlet of the SCR system was 100 × 10⁻⁶. Within the temperature range of 200–400°C, the tailpipe ammonia slip was very low because the reaction in the SCR catalyst proceeded thoroughly. The minimum of the tailpipe ammonia slip was ∼10 × 10⁻⁶ at 350°C. When the temperature was 450°C, the volume fraction of NH₃ at the outlet of the SCR system was as high as 150 × 10⁻⁶. When the temperature further increased, the activity of the reaction catalyst decreased rapidly, resulting in high tailpipe ammonia slip.

Effect of exhaust gas mass flow on conversion efficiency

In the model, the ANR at the SCR inlet was set to 1:1, meaning that the volume fractions of NH₃ and NO_x were 750 × 10⁻⁶.

Simulations were conducted to study the relationship between the NO_x conversion, as well as the tailpipe ammonia slip and the exhaust gas mass flow when the SCR outlet temperature was 150°C. The NO_x conversion has a strong relationship with the SCR inlet temperature. However, the SCR inlet temperature was set as 150°C all the time when exhaust gas mass flow increases, resulting that NO_x conversion does not change a lot.

As shown in Fig. 7, when the exhaust gas mass flow was in the range of 200–1,500 kg/h, the NO_x conversion gradually decreased a little as the exhaust gas mass flow increased. As the exhaust gas mass flow continued to increase, its effect on the NO_x conversion efficiency gradually weakened. When the exhaust gas mass flow was between 200 and 800 kg/h, the NO_x conversion efficiency decreased from 57.98% to 55.62%. In the range of 800–1,500 kg/h, the NO_x conversion efficiency decreased from 55.62% to 55.06%, and thus, it was almost unaffected by the exhaust gas mass flow. Figure 7 shows that the volume fraction of NH₃ at the outlet of the SCR system increased with an increase in the exhaust gas mass flow.

FIG. 7.

Relationship between the NOx conversion, the NH₃ concentration at the SCR outlet, and the exhaust gas mass flow when the SCR outlet temperature was 150°C.

SCR 3D simulation based on ammonia storage dynamics

In the previous sections, the parameters of the SCR 1D catalyst model were identified, and the experimental results were compared with the simulation results to prove the accuracy of the 1D model. Based on these results, a 3D SCR catalyst model was established in the AVL FIRE software. The SCR parameters in the 3D SCR catalyst model were consistent with the 1D model. The 3D model is used to analyze the ammonia storage characteristics inside the SCR catalyst. The SCR 3D model and grid established by the AVL FIRE software are shown in Fig. 8.

FIG. 8.

(a) Three-dimensional SCR catalyst model, (b) Model grid of the three-dimensional SCR catalyst model, (c) selected three cross-sections α, β, and γ, along the axial direction of the SCR and the three sections divide the carrier into four equal parts.

The material transport and aftertreatment modules were included in the 3D model. Based on the 1D simulation model parameters, the inlet boundary conditions of the 3D model were set, including the diesel exhaust gas temperature, exhaust gas mass flow, and gas component concentrations. The SCR outlet pressure was set as standard atmospheric pressure. To simplify the model, the temperatures of the tube wall surface and catalyst were set to 300 K. The initial temperature of the fluid was also set to 300 K. The initial values of the parameters in the 3D model are shown in Table 6. In the analysis below, the influence of temperature of the inlet of SCR on the dynamic characteristics of the spatial distribution of ammonia storage and its effect on the NO_x conversion efficiency are examined by changing the temperature of the inlet of the SCR system at different times.

Table 6.

Initial Values of Parameters in the Three-Dimensional Model

Parameters	Value
Pressure	100,000 Pa
Density	0.5 kg/m³
Temperature	300 K
Turbulent energy	0.001 m²/s²
Turbulence length scale	0.001 m
Turbulent dissipation rate	0.00519615 m²/s³

Effect of inlet temperature of SCR on dynamic characteristics of ammonia storage along axial direction

Due to the nonuniformity of fluid flow and heat exchange, the temperature of the SCR catalyst is not uniform. The rate of reaction has a relationship with the temperature of the SCR, resulting in an uneven ammonia distribution in the SCR catalyst. The distribution of ammonia storage in the SCR is critical to the NO_x conversion efficiency. In the models, the exhaust gas mass flow was set to 480 kg/h, the ANR at the inlet of the SCR was set to 1:1, and the volume fractions of NH₃ and NO_x were 750 × 10⁻⁶. The influence of temperature on the performance of the catalyst is analyzed; 150°C, 350°C, and 500°C were selected as the low, medium, and high temperature, respectively. The distribution maps of the ammonia storage mass fraction along the axial direction are shown in Fig. 9. Figure 9 shows the ammonia storage in the SCR catalyst along the axial direction at different temperatures and different time. The scale on the left represents the amount of the NH₃ adsorbed, the unit is kg/m³.

FIG. 9.

Axial distributions of ammonia storage at different inlet temperatures of the SCR.

It can be observed that large numbers of NH₃ is adsorbed on the front end of the SCR first and the adsorption in the central area is larger. As the NH₃ continues to flow in, the NH₃ gradually expands and reaches a saturated state at a certain time. The adsorption amount of NH₃ is higher in the center area and the area near the wall surface than other areas when the carrier reaches the adsorption saturation state, forming an uneven distribution similar to the shape of ɛ. This phenomenon is mainly due to the uneven distribution of flow velocity and temperature inside the SCR. The flow velocity in the center area of the SCR is high, providing enough NH₃ supply. In addition, the heat exchange between the wall of the carrier and the external environment makes the wall temperature relatively low, which results in higher adsorption near the wall area. The distribution similar to the shape of ɛ is obvious at low temperature and middle temperature, but it is not obvious at high temperature. The major reason is that the effect of the flow velocity on the adsorption amount is relatively weak because of the high temperature and high rate of adsorption.

As the temperature increases, the amount of saturated adsorption on the carrier decreases, meaning that the ammonia storage capacity of the catalyst decreases with temperature.

The effective length of the SCR is over 95% of the total length at low temperatures. At high temperatures, the effective length of the SCR is about 1/3 of the total length.

At different temperatures, the time it takes to reach the saturated adsorption state is different. It takes about 25 s at 150°C, about 20 s at 350°C, and about 15 s at 500°C for the SCR to reach the saturated adsorption state in the models. The time consumed to reach the saturation state does not depend on the temperature of the SCR, but depends on the storage capacity of the SCR and the rate of adsorption at different temperatures.

At low temperatures, the storage capacity of the SCR is high and the rate of adsorption is high. At high temperatures, the storage capacity of the SCR is low and the rate of adsorption is low.

The rate of adsorption can be described as follows: $r = r_{a} - r_{d} - r e a c t$

where r is the rate of the total adsorption, r_a is the rate of the adsorption of NH₃, r_d is the rate of the desorption, and r_react is the rate of the NH₃ consumed in reactions.

At high temperatures, the storage capacity of the SCR is low and the catalyst is active. r_a, r_d, and r_react are high at high temperatures. And r, the rate of the total adsorption, is low at high temperatures.

Effect of inlet temperature of SCR on dynamic characteristics of ammonia storage along radial direction

An initial temperature of 350°C was selected to study the radial ammonia storage dynamic characteristics using the 3D simulation. Three cross-sections were selected to study the radial ammonia storage dynamic characteristics in the 3D model, as shown in Fig. 8. Select three positions α, β, and γ, along the axial direction of SCR to study the dynamic characteristics of ammonia storage of SCR at 350°C.

Figure 10 shows the distribution of the dynamic ammonia storage mass fraction along the radial direction of SCR model at 350°C over time at the selected three cross-sections. At the beginning, the temperature at section α is higher than section β and γ because section α is near the SCR inlet. The ammonia storage at section α is more than section β and γ because exhaust gas flows along the axial direction of the SCR and ammonia first adsorbs at section α.

FIG. 10.

Radial distribution of ammonia storage mass fraction with time at 350°C in the selected three cross-sections.

At the different axial positions, the radial ammonia storage dynamic characteristics were basically the same, and the adsorption of NH₃ diffused radially from the center to the edges. After reaching the saturated ammonia storage state, the desorption of NH₃ also began from the center.

Figure 11 shows that ammonia storage began to show an uneven distribution at 35 s. This was mainly due to the uneven distribution of the temperature and space velocity at this stage.

FIG. 11.

Radial distribution of ammonia storage mass fraction in the selected three cross-sections at 35 s.

As shown in Fig. 12, the ammonia storage in all three regions reached a steady state at 130 s. The ammonia storage amount at this time gradually decreased along the axial direction from the first to the third region. This showed that the storage of ammonia was high in the center, low in the surrounding areas, and high at the edges. These phenomena were caused by the uneven distribution of temperature and space velocity.

FIG. 12.

Distribution of NH₃ at 130 s when the storage state was stable.

At 350°C, the adsorption started at 5 s. At this time, the amount of NH₃ adsorbed at the center of section α is 0.017–0.018 kg/m³, and the amount of the NH₃ adsorbed at the center of sections β and γ is almost 0 kg/m³. Section α reaches the adsorption saturation state at about 10 s. Section β reaches the adsorption saturation state at about 15 s. Section γ reaches the adsorption saturation state at about 20 s. It can be seen that the time consumed to reach adsorption saturation state increases with the deepening of the axial position. The adsorption amount in the central area and near the edge is the largest, which is due to the uneven distribution of ammonia storage caused by different temperatures and space velocities in different positions of the SCR. The flow velocity is high in the center area of the SCR and low near the edge area. The temperature near the center of the SCR is high and the temperature near the edge of the SCR is low.

Summary and Conclusions

In this study, a diesel engine and a vanadium-based SCR catalytic converter were studied in the NRSC. The effects of the temperature and exhaust gas mass flow on the SCR performance were studied in the SCR 1D model. A 3D model of SCR catalyst was established to study the ammonia storage characteristics of SCR. The following conclusions were obtained:

(1)

When the inlet temperature of the SCR was in the range of 100–550°C, the NO_x conversion efficiency increased first and then decreased as the temperature increased. The rate of reaction increased with increasing temperature. The effect of the exhaust gas mass flow on the NO_x conversion efficiency was evident at low temperature conditions.

(2)

The ammonia storage capacity of the SCR catalyst decreased as the temperature of the SCR increased.

(3)

The effective length of the SCR decreased as the temperature of the SCR increased, and the effective area of the catalyst was near the inlet of the catalyst.

(4)

An uneven distribution of ammonia storage similar to the shape of ɛ was observed in the simulation and this kind of uneven distribution was obvious at low temperature.

Footnotes

Acknowledgments

This work was supported by the National Key R&D Program of China (grant number 2017YFC0211205). The authors would like to thank the editors and anonymous reviewers for their suggestions to improve this article.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by the National Key R&D Program of China [grant number 2017YFC0211205]. The authors would like to thank the editors and anonymous reviewers for their suggestions to improve this paper.

Nomenclature

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