Simulation of Hydrocarbon Injection used for Catalyzed Diesel Particulate Filter during Active Regeneration Process

ISSN 1674-8484
CN 11-5904/U
汽车安全与节能学报, 第 8 卷 第 3 期 , 2017 年
J Automotive Safety and Energy, Vol. 8 No. 3, 2017
268 — 278
Simulation of Hydrocarbon Injection used for Catalyzed Diesel
Particulate Filter during Active Regeneration Process
ABDALLA Aniseh, WANG Guoyang, ZHANG Jun, SHUAI Shijin
(State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China)
Abstract: Diesel oxidation catalyst (DOC) upstream of catalyzed diesel particulate filter (CDPF) with additional
diesel injection (hydrocarbon injection, HCI) were used to control the particulate matter (PM) emissions to
meet stringent emission regulations for heavy-duty diesel vehicles. This study optimized the location of injector
upstream of DOC by evaluating the uniformity of HC distribution on the entrance of DOC. An HCI was used in
active regeneration to enhance the exothermic heat of CDPF to initiate the soot regeneration. Numerical analysis
was established for the combination of after-treatment technology DOC-CDPF, and a spray model for HCI was
implemented into a commercial CFD code named AVL FIRE. Different locations and orientations of the injector
were tested. The results show that injector location has a significant effect on the optimal mixing between the
exhaust gas and injected hydrocarbon (HC). Optimum injector location is the injector located farthest from
DOC, while the long distance between injector and DOC allows enough time for injected HC to form secondary
droplets, as it mixes well with exhaust gas downstream. Using HCI upstream of DOC causes the exhaust gas
temperature to increase and reaches 550 ℃ at the entrance of CDPF, which is enough to initiate active DPF
Key words: vehicle exhaust emission; particulate matter (PM); hydrocarbon injection (HCI); catalyzed diesel
particulate filter (CDPF); diesel oxidation catalyst (DOC); active regeneration
柴油机颗粒过滤器再生过程的碳氢喷射模拟 ( 英文 )
艾尼塞,王国仰,张 俊,帅石金
(清华大学 汽车安全与节能国家重点实验室,北京 100084,中国)
摘 要:为满足严格的重型柴油机排放法规,柴油催化氧化器 (DOC) 和催化型柴油颗粒捕集器
(CDPF) 得到了广泛的应用。碳氢喷射 (HCI) 是一种实现 DPF 主动再生的有效方法。该文通过改变柴
油喷嘴位置来优化 DOC 入口的碳氢化合物 (HC) 分布。使用计算流体力学软件 AVL-FIRE,建立了
DOC-CDPF 模型,用软件内置 HCI 喷雾模型,对喷射器的安装位置和喷射方向进行了数值模拟。模
拟结果显示:喷射器的位置对 HC 分布有很大的影响,喷射器位置距离 DOC 越远,DOC 入口处的
HC 混合均匀性越高,这是因为喷雾在 DOC 前有更长的距离和时间形成均匀混合气;排气管喷射柴油
可以使 DPF 入口温度达到 550 ℃,满足了CDPF 主动再生的需求。
收稿日期 / Received :2017-06-05。
基金项目 / Supported by :国家“十三五”规划重点研发项目 / National Key R&D Program of China (2017YFC0211105) 。
第一作者 / First author :艾尼塞 / ABDALLA Aniseh (1985 - ) ,女 / female,约旦 /Jordan,博士后 /Postdoctoral research fellow.
E-mail: [email protected]。
关键词:汽车废气排放;颗粒物 (PM) ;碳氢喷射 (HCI) ;催化型柴油颗粒捕集器 (CDPF) ;柴油催
化氧化器 (DOC) ;主动再生
中图分类号:TK 411+.5 文献标识码:A DOI: 10.3969/j.issn.1674-8484.2017.03.007
In general, the soot particles are divided into five categories
according to its size in aerodynamic diameter [1]:
1) Large particles represents particles diameter, Dp >
10 μm;
2) Coarse particles represents, Dp = 2.5~10 μm;
3) Fine particles represents, Dp = 0.1~2.5 μm;
4) Ultra- fine particles represents, Dp = 50~100 nm;
Burtscher reported that the small size particles that make up
nuclei mode as shown in Figure 2 are present in the greatest
number, but contribute little to the particle mass of diesel
engine PM emissions. On the other hand, larger size particles
are found in small numbers that make up accumulation mode
and contribute more to the particle mass [1-2, 5].
In general, the particulate emission regulations are being
legislated mainly in a particulate mass (PM). Last emission
regulations (Euro VI & Beijing VI) are legislated not only in
particulate mass (PM) but also included the particulate number
(PN). PN is used to control the small size particles since the
Ash and other 13%
Unburnt oil SOF
Fine particles
DP< 2.5 μm
DP< 50 nm
Ultra fine particles
DP< 100 nm
DP< 10 μm
DP / μm
Fig 2 Concentration of PN and PM vs. Particle Size
Distribution from Diesel Exhaust [1]
small size particles are more harmful to human health than
relatively large size particles [3, 9]. Table 1 compares emission
standards for Europe, U.S., and China. The legislation for China
III-V are based on Euro III-V which was adopted in 2005 [10].
Table 1 Exhaust Emission Standards for Heavy-Duty
5) Nanoparticles represents, Dp < 50 nm.
Normalized conccntration
[dN / d lg(DP / μm)] /cm-3
Emission control technologies are required to achieve stringent
emission regulations such as Beijing VI (equivalent to Euro
VI) to overcome air pollution problem caused by diesel engine
vehicles since diesel engine vehicles are a major source of
particulate matter (PM) emissions. Figure 1 represents the
PM composition emitted from a heavy-duty diesel engine [1, 2].
The composition of PM of the exhaust gas emitted from diesel
engines is mainly characterized as a mixture of soot, soluble
organic fraction (SOF), sulfates, and inorganic materials
(ash) [3-5]. Figure 1 shows that the soot concentration is the
highest in the composition of PM. Those PM compositions are
depending on several factors, such as engine design, operating
conditions, and fuel used [6-8].
Soot 41%
Fuel SOF 7%
Fig 1 PM Composition Emitted from a Heavy-Duty
Diesel Engine. Engine Test Bench has been
Carried out in a Transient Cycle Test [5]
on-Road Diesel Engines [1, 10-11]
Legislation, Year
1011·(kWh) -1
Euro IV, 2005
20, (ESC)
30, (ETC)
Euro V, 2008
20, (ESC)
30, (ETC)
Euro VI, 2013
10, (ESC)
10, (ETC)
8, (WHSC)
6, (WHTC)
US 2007, 2007
US 2010, 2010
China IV, 2015
China V, 2015
China VI b , 2017
8, (WHSC)
6, (WHTC)
VI b — Proposed Beijing VI limits,
ESC — European steady cycle,
ETC — European transient cycle,
ELR — European load response test,
WHSC — world harmonious steady cycle,
WHTC — world harmonious transient cycle.
第 8 卷 第 3 期 2017 年
Current emission regulation in Beijing is Beijing V, Beijing
V was implemented from 1st of June 2015. It is reported
that Beijing will implement Beijing VI emission regulation
in December 2017, and China in 2020. The bad quality air
becomes significant public health problem not only in Beijing
but also in many cities around the world. Therefore, strict
regulations for air pollutant emissions are necessary. Diesel
particulate filter (DPF) is the most efficient system that is used
to trap the PM emissions. Figure 3 illustrates a configuration of
an after-treatment system that consists of catalyzed filter (DPF
and DOC). A wall-flow monolith is used as the most common
type of DPF. Wall-flow filter structure commonly made of
silicon carbide (SiC) or Cordierite (Cd) ceramic material coated
with a catalyst which is widely used in heavy-duty engine
applications [1]. The main design criteria of DPF’s wall-flow
filters that contribute to optimum filtration and regeneration
performance are high filtration efficiency, low-pressure drop,
high maximum operating temperature, low thermal expansion,
high resistance to the thermal stress, low reactivity with ash
and high durability [1].
Inside the DPF there are many parallel channels, these channels
are divided into inlet and outlet channels. The inlet channel
inside the DPF is plugged at the end of the channel to force the
exhaust gas to pass through the wall of the filters into outlet
channel [12]. Therefore, the exhaust gas is allowed to enter the
inlet channels which are open toward the inlet side. The soot
accumulates on the walls of the inlet channels; the process
is called soot loading. As the filter accumulate more soot, it
builds up backup pressure that may cause engine/filter failure
and decreases fuel economy [44]. Therefore, the DPF have to
remove the accumulated soot from the wall filter to avoid the
high backpressure due to soot accumulation; the process is
called regeneration [13-14]. On heavy-duty diesel engines, the
combination of passive regeneration (continuous regeneration
during regular operation) and active regeneration (periodic
regeneration starts when the soot loading of DPF reaches a
threshold) are necessary to achieve reliable DPF regeneration
at all driven conditions [1]. Passive regeneration does not
involve additional energy source for soot oxidation. In contrast,
active regeneration relies on external energy sources such as
additional diesel injection (HCI).
Soot particle
A wide range of studies on passive and active regeneration
indicate that DOC-CDPF after-treatment system is very
efficient in controlling the soot, carbon monoxide (CO), and
hydrocarbon (HC) emissions. CDPF is suitable not only for
light-duty engines but also for heavy-duty diesel engines in
highway and non-road applications [15-18]. The scheme of the
after-treatment system is shown in Figure3.
The combination of passive and active regeneration is required
to ensure the CDPF regeneration at all driven conditions [21], For
example, if the vehicle is driven at low speed or suddenly stops
during uncontrolled regeneration, it could lead to overheating
and damaging the CDPF. Passive regeneration does not
involve additional energy source for soot oxidation. In contrast,
active regeneration relies on external energy sources. Active
regeneration of DPF with direct injection of diesel (Hydrocarbon
injection, HCI) into the exhaust pipe is the most widely used
regeneration method for heavy-duty diesel engines [41-43].
As mentioned before, hydrocarbon injection (HCI) is also
called secondary fuel (diesel) injection is used to increase the
exhaust gas temperature to initiate the soot regeneration within
Honeycomb wall-flow filter
15.25 cm
45 cm
Pressure sensor
R=13.5 cm
In order to meet the latest Euro VI emission regulation, diesel
injection (hydrocarbon injection, HCI) was used with DOC
upstream of CDPF which raises the exhaust gas temperature
by injecting a small amount of diesel into the exhaust stream
in order to enhance thermal oxidation of soot during active
regeneration (also called periodic regeneration). DOC is used
not only to raises the exhaust gas temperature but also to
produce more Nitrogen Dioxide (NO2) by converting Nitrogen
Monoxide (NO) to NO2. NO2 assisted oxidation of soot in the
CDPF during continuous regeneration (also called passive
regeneration) [40].
Temperature sensor
27.97 cm
After-treatment technologies such as DPF, becomes mandatory
to control soot emissions, while heavy-duty diesel engines are
a major source of soot emissions. Kuwahara et al. investigated
catalyzed DPF (CDPF), and he found that CDPF enhances soot
regeneration efficiency and oxidation activity [45]. Therefore,
CDPF is applied in this study. There are many studies
investigated the CDPF and developed coated catalysts in
order to enhance filtration efficiency of soot. The demand and
consequently the development of after-treatment technologies
are expected to increase over the coming few years.
Soot Particles
Ash Particles
20 cm
Soot removal
HC,CO removal
Fig 3 Configuration of an After-Treatment System (DOC-CDPF) with Secondary Fuel Injection (Hydrocarbon Injection, HCI) [14, 19-20]
The injected HC is burnt in DOC. The injector is mounted in
the exhaust pipe upstream of DOC, to increase the exhaust gas
temperature to a level suitable for soot oxidation (e. g. from
339℃ to 550 ℃ ). Thermal oxidation of soot at regeneration
process is enhanced when the CDPF temperature is greater
than 500 ℃ , while optimum temperature for soot regeneration
is 600 ℃ [21-22]. The mixture of exhaust gas contains nitric
monoxide (NO), carbon monoxide (CO), and HC emissions
which are oxidized inside the DOC, resulting in thermal load
over DOC and CDPF, which may lead to damage to the DOC
or/CDPF components due to the thermal stress [23]. Therefore,
it is important to control the exhaust gas temperature by
controlling several factors including the amount of diesel
fuel injected into the exhaust pipe (upstream of DOC), diesel
injector (HCI) location and exhaust mass flow rate [15] (in this
study, mass flow rate is kept constant). Exothermic reactions in
DOC are described by the following reactions [24]:
The amount of liquid diesel fuel (hydrocarbons (HC)) added by
the injector to provide the heat required to initiate the CDPF
regeneration was calculated by the following equation [15]:
is the mass flow rate of diesel injection (HCI),
is the mass flow rate of exhaust gas, ∆Texh is the
temperature difference between target temperature and actual
exhaust gas temperature at DOC outlet, cp is the specific heat
of the exhaust gas, and Hu is the lower heating value of the
diesel fuel. The lower heating value of the diesel fuel Hu is set
to 42.76 MJ/kg.
Dongfeng commercial diesel engine X7 is used in this study,
and the exhaust after-treatment system consisted of DOC and
CDPF are used to control the soot emission. The main objective
of this study is to optimize the injector location for active
regeneration process of a CDPF. However, the main challenges
for CDPF systems in automotive applications are controlling
the regeneration process and ensuring the safety of catalyzed
filter (CDPF and DOC) materials. To control the regeneration
process of CDPF, several issues are considered in the study: the
amount of diesel fuel injected into the exhaust pipe; the injector
location and orientation; hydrocarbon (HC) concentration field
on the DOC upstream, and temperature distribution at CDPF.
The commercial CFD code named AVL FIRE is used for
numerical analysis [25].
It is essential to estimate the HC distribution on the entrance
of DOC and optimize the location of the injector by enhancing
the uniformity of HC distribution on the entrance of DOC.
We observed that high concentration of injected diesel could
cause hot spots in the entrance of DOC. Therefore, this
phenomenon could be avoided by optimizing the location of
the injector when possible or using mixers to enhance the
mixing efficiency. Uniformity indices have been used to rank
the uniformity of the catalyst flow. The uniformity index γ of φ
(in this case φ represent HC concentration) at a catalyst crosssection is defined as follows [20]:
Here, ADOC is the front area of DOC, N is total number of
computational cell. Uniformity index γ is mainly evaluated
for assessing the performance of the catalyst (DOC/CDPF) for
those parameters which have an influence on the performance
of the after-treatment systems, such as HC distribution,
temperature distribution, and velocity distribution.
This study investigated HCI which is used for the heavyduty diesel engine on a stationary operating point. We also
optimized the injector location by enhancing the uniformity of
HC distribution in the entrance of DOC.
1 Numerical Methodology
1.1 Governing Equations
The Reynolds-average governing equations for mass
conservation, momentum, and energy are solved to predict
the behavior of the compressible multicomponent gas. For gas
mixture (exhaust gas and injected HC) distribution problems,
the solution of the governing equations is necessary to be in
transient form. Therefore, the governing equations conducted
in this work are the unsteady average Navier-Stokes equations.
The computations are initiated with 3-D transient simulations.
The fluid properties’ (temperature, pressure, velocity, etc.) in
the multicomponent gas are solved by transport equations. The
HC is injected from a nozzle (injector hole diameter is 0.5 mm)
as a spray. Injected diesel fuel assigned as a vapor phase. The
transport equation for multicomponent exhaust gas for each
gas species is defined as following [26-30]:
Where, ρ is the density of the gas mixture, Yα is the mass
fraction of gas species α, t is the computational time in
seconds, Jα is the mass diffusion flux vector, and U is the
velocity component in three-directions (x, y, z). The source
(S α) is the net rate of creation of the conserved mass inside the
control volume; it can be converted by phase changes from one
state (liquid) to other states (gas) or split into a component by
CDPF. HCI is one of the promising external energy sources
that is used to enhance the exothermic heat of CDPF to initiate
the soot regeneration [16]. HCI is positioned in the exhaust pipe
in the direction of the exhaust stream to ensure optimal mixing
between injected hydrocarbon (HC) and exhaust gas. The
hydrocarbon (HC) is introduced by injector as spray during the
regeneration process. HCI location has a significant influence
on the mixing of HC with exhaust gas flow [20]. Therefore, it is
important to optimize the injector location and orientation.
chemical reactions. Simulation of the transport Eq. (7) for each
gas species get the general continuity mass Eq. (10), because
of summation source term (S α) of Eq. (7) for each gas species
equal to zero. Summation of the mass fraction for each mixture
component α is determined as following, here N is the number
of the components α.
The diffusion flux for the component α is defined as:
第 8 卷 第 3 期 2017 年
purpose, k-ζ-f turbulence model has been used to close the
Reynolds average equations. It is known that all quantities in
Eq. (10) are considered time-averaged values for the turbulence
models. To solve these time-averaged quantities, a set of
transport equations of turbulence quantities (the turbulent
kinetic energy (k) and, the rate of dissipation of k (ε)) is applied
with the artificial turbulent viscosity (μtur) (see Eq. (20)). μtur
is used to account for the additional diffusion flux due to
turbulent motion. Therefore, the effective diffusion coefficient
Γ is defined as following:
Where, Jα is the diffusion flux of gas species, ρ is the density
of the gas mixture, Yα is the mass fraction of gas species α, Dα
is the mass diffusion coefficient of gas species α, and Sct is the
turbulent Schmidt number. Thus, Jianjun XIAO pointed out
that turbulent Schmidt number Sct can be selected between 0.5
and 1.0 values [31]. The general form of conservation equations
for mass, momentum, and energy in the Cartesian coordinate
system have the following form:
Here, the symbol“tur”represents the turbulent flow, σf is the
turbulence Prandtl number based on the diffusivity of variable f .
The k-ζ-f turbulence model is developed by Hanjalic,
Popovac and Hadziabdic (2004). The k-ζ-f turbulence model
solves a transport equation for the velocity scales ratio ζ,
which makes the model more robust and less sensitive to grid
non-uniformities [32]. The k, ε, ζ and transport equation of
turbulence kinetic energy (k) are defined by the following
equations [26, 29, 33-34]:
Here, f is the general dependent variable, u, v, and w are the
velocities in the x, y, and z directions. The diffusion coefficient
Γf and the source term Sf are unique to each dependent variable
f , as shown in Table 2.
Table 2 Source Terms in Cartesian Coordinate Systems
ρg x + Vx -R x -( P/ x)
ρg y + Vy -Ry -( P/ y)
ρgz + Vz -R z -( P/ z)
dP / dt +
Here, Vx, Vy, Vz are the balance for the viscous diffusion term,
R x, Ry, R z are the distributed resistance due to solid structures
in a momentum control volume, rb is the rate of heat liberated
from solid structures per unite fluid volume, is the rate of
internal heat generation per unite fluid volume, and Φ is the
dissipation function.
Here, ν is the kinematic molecular viscosity (μ/ρ), the terms
in Eq. (15) are:
A: the production of k due to mean shear,
B: the production or destruction of k by buoyancy,
C: a loss of k to heat through viscous dissipation,
D: the diffusive transport of k and randomizing action of
the pressure-strain correlation.
To solve Eq. (15) for turbulent kinetic energy k, closure
relations are used, then transport equation of k [see Eq. (15)] is
simplified and integrated over control volume as follows:
1.2 Turbulence Models
The governing equations for turbulent flow are not closed.
Therefore, turbulence models are required for closing the
). For this
system of non-linear Reynold stress term (
The k-ζ-f turbulence model consists of three transport
equations, one for the turbulent kinetic energy k as shown in
Eq. (16), one for its dissipation rate ε, see Eq. (18), and one for
normalized velocity scale ζ as shown in Eq. (19).
The transport equation of rate of dissipation ε, velocity scale
ratio ζ, and eddy viscosity are obtained by the following
, (18)
The droplet breakup process is described by standard
wave model [38], where the size of the secondary droplets is
determined. Droplet wall interaction behavior is modeled by
Kuhnke model [39]. Heat transfer between wall and droplet is
determined following a model proposed by Wruck 1998.
The mass transfer rate during evaporation from the wall-film
is determined by using the combination of Still-Himmelsbach
and Diffusion models. The combination model has a good
estimation for the single component liquid fluids and engine
applications, while for multi-component fluids a homogenous
mixture is used to predict the evaporation rate [25]. It is known
that Kuhnke model is suitable for diesel spray simulations; this
model distinguishes between four wall impingement regimes
by dimensionless wall temperature (T*) and droplet velocity (K)
parameters. These parameters are defined as following [25]:
Pk in the three transport equations, see Eq. (16), Eq. (18)
and Eq. (19), represents the turbulence production due to the
mean velocity gradients, σζ, σk and σε are the turbulent Prandtl
numbers, f is the elliptic relaxation function, T is the turbulence
time scale, L is the turbulence length scale, S is the mean rate
), μ is the molecular viscosity,
of strain tensor (
and μtur is the turbulent viscosity. The model coefficients
applied to the k-ζ-f turbulence model are listed in the below [32]:
Cμ =0.22, Cε1=1.4(1+0.012 ⁄ ζ), Cε2=1.9,
C3=0.8, C2'=0.65, CT =6, CL=0.36, Cη =85,
C4=0.33, σk =1.0, σε =1.3, σζ =1.2.
To correctly predict the large variation in the values of
turbulence properties (gradient of momentum, energy flux, k,
and ε) near wall, wall function treatment is used. Wall function
treatment is an analytical solution which is used to simplify
turbulence equations. Numerical solution of turbulence
equations close to the wall is impractical because the fine mesh
is required near a wall. Moreover, if sufficient grid resolution is
used near a wall, then large computational times are required.
Therefore, in order to avoid the grid resolution problem and the
significant error due to steep flow properties variations near
a wall, special wall treatments are employed. Unfortunately,
there is no single wall function that can promise good accuracy
for various types of flows. The generalized wall treatment,
also called hybrid wall treatment can be used as low Reynolds
model near the wall, which is proposed by Popovac and
Hanjalic [35]. Therefore, hybrid wall treatment is applied with
k-ζ-f turbulence model in the simulations of this study.
1.3 Spray and Wall-Film Models
The droplet dispersion of spray and the effect of turbulent on
droplets are modeled by Gosman and Ioannidis [36]. Droplet
heat-up evaporation is predicted by using Dukowicz model [37].
Here, Tw is the wall temperature, Ts is the particle surface
temperature, ρd is the droplet density, dd is the droplet diameter,
ud is the droplet velocity, σd is the surface tension of the droplet
and μd is the dynamic viscosity of droplet.
Kuhnke model considers four wall impingement regimes, as
shown in Figure 4: Rebound, Thermal breakup, Deposition,
and Splash.
These regimes are modeled based on the wall temperature T*
and droplet velocity K as following:
A: Rebound regime formed when wall temperature higher than
1.1 value ( T*>1.1) with low droplet velocity. Existing vapor
layer between wall and droplet prevent wall film formation
B: Thermal breakup regime formed when wall temperature
higher than 1.1 value ( T*>1.1) with high droplet velocity.
Thermal breakup
This model assumes that the droplet is evaporating in a noncondensable gas.
Fig 4 Four Wall Impingement Regimes Based on Kuhnke Model [39]
第 8 卷 第 3 期 2017 年
Secondary droplets are formed, and no wall film is formed
C: Deposition regime formed when wall temperature less
than 1.1 value ( T*<1.1) with low droplet velocity. Wall film is
created due to completely deposed of droplets on the wall
D: Splash regime formed when wall temperature less than 1.1
value ( T*<1.1) with high droplet velocity. Secondary droplets
with wall film are formed.
2 Boundary Conditions
Inlet, outlet and wall boundary conditions were specified.
Gas temperature with 339 ℃ , mass flow rate with 600 kg/
h of the gas and gas species’ mass fraction were applied to
the inlet face. Exhaust gas was assumed to be an ideal gas.
Pressure boundary with 1 bar value was used on the outlet face.
Adiabatic heat transfer was estimated on the wall boundaries.
The boundary conditions and the injector geometry parameters
used for the HCI simulations are summarized in Table 3. In
order to optimize HCI location in the exhaust pipe upstream of
DOC, four different locations are settled at A, B, C and D. See
Figure 6.
Table 3 Inlet Boundary Conditions of CFD Model and
Geometrical Data Parameters of the Injector
Inlet gas flow rate
Inlet gas temperature
Injected fuel
600 kg/h
339 ℃
diesel (HC)
Fuel injection rate
65 g/min.
Number of nozzle hole
Injector hole diameter
0.5 mm
Spray cone angle
20 m/s
Averaged droplet size
100 μm
HCI is simulated with 339 ℃ initial gas temperature and 600
kg/h mass flow rate. The regeneration process is controlled
by controlling gas temperature rate flowing through the aftertreatment system. While gas temperature is controlled by
the HCI dosing (amount of diesel fuel) and optimizing HCI
location and orientation. The amount of diesel fuel injected into
the exhaust pipe upstream of DOC was 65 g/min, this amount
is calculated by Eq. (4). Figure 6 is the schematic diagram of
the simulated HC injector positions. A, B, C, and D indicate
the location of the injector, and the arrows attached to those
injectors indicate the spray direction. HC injector location and
orientation are optimized to ensure optimal mixing between
injected HC and exhaust gas.
Figure 7 shows the HCI characteristics in the exhaust gas for
the injector located at 35 cm from the end of tube bend with
injection angle 45°(Design“A”). The simulation results of
the HC mass fraction distribution at the entrance of DOC is
shown in Figure 7.
Initial droplet velocity
ESE Aftertreatment Tool of AVL FIRE. The 3D mesh created
at AVL FIRE is based on sweeping a 2D mesh through space
along a trajectory. Higher mesh density is used near HC
injector, and very small artificial time step (1 ms) is applied
to capture mass and heat transfer process of droplets. The
structured grid has been used for the After-treatment system
is shown in figure 5. Mesh independent study was performed
in order to achieve mesh resolution that could provide
independent mesh solution. Therefore, 64,000 cells and 298,100
cells were tested to examine the sensitivity of the simulation
results to grid refinement. We found no significant difference
in the simulation results between fine and coarse mesh. The
resolution of the used coarse mesh (64,000 cells) is sufficient
to capture the spray and exhaust gas mixture phenomena.
Therefore, for HCI simulation, 64,000 cells has been used on 4
core CPU.
3.1 Optimization of Injector Location
3 Results and Discussions
All the 3D simulation results presented in this paper were
performed by FIRE-V2014.1 where spray and wall film
models were used. Structural type mesh was generated by
Different locations and orientations of the injector have been
tested to optimize the injector location. Four injectors are
installed at various places as shown in Figure6. Uniformity
index and HC mass fraction simulation results are compared,
and the comparison of the simulations results are shown in
Fig 5 Computational Model of the After-Treatment System (DOC-CDPF) with Secondary Fuel (HC) Injector
Uniformity index of HC
6 cm
15.25 cm
35 cm
27.97 cm
t / ms
Fig 6 The Scheme of Injector Positions for Different
Injectors Settled at A, B, C and D
Fig 8 Uniformity Index of HC Species Distribution at
the Entrance of DOC for Various Injectors
HC mass fraction / 10-3
Mean HC Mass Fraction / 10-3
entrance of DOC
The simulation results in Figure 8, shows that the HC
distribution is not uniform for the HC injector“D”because
the distance between HC injector and DOC is very short.
Therefore, a mixer is required to enhance the mixing in front of
the DOC when injector“D”is used. The best injector location
was found to be injector“A”(see Figure 7). The long distance
between injector and DOC allows enough time for injected HC
t / ms
Fig 9 Transient HC Mass Fraction Distribution at the
Entrance of DOC for Various Injectors
Fig 7 HCI Characteristics in the Exhaust Gas and Contour Plot
of Hydrocarbon Distribution at the Entrance of DOC
figure 8 and Figure 9 respectively.
to form secondary droplets, as it mixes well with exhaust gas
downstream. The nozzle angle 45°of injector“A”has higher
uniformity index of HC at the entrance of DOC than injector“C”
Injector“C”is positioned at the center of the exhaust pipe of
the exhaust gas, and its injection direction is parallel to the exhaust gas stream. Uniformity index γ of HC at the entrance of
DOC is compared for the various injectors as shown in Table 4.
Figure10 shows the contour plot of HC distribution at the
Uniformity Index
γ / 10 -2
γ = 0.96
γ = 0.88
γ = 0.93
γ = 0.55
Fig 10 Contour Plot of HC Distribution at the Entrance of DOC and Corresponding Gamma Values for Various Injectors
第 8 卷 第 3 期 2017 年
entrance of DOC and corresponding gamma values γ for
various injectors. We observed that the best location for the
injector is position“A”.
Injector location
Uniformity index of HC, γ
Table 4 Uniformity Index Values (γ) for Each HC Injector
1 000
Fig 11 Contour Plot of Temperature Distribution at the
Entrance of CDPF (CDPF_Upstream) and the End of
CDPF (CDPF_Downstream) During Active Regeneration
The heat released from the catalytic reaction of injected HC in
DOC causes the exhaust gas temperature to increase and reach
almost 550 ℃ at the entrance of CDPF (CDPF_upstream).
The 3D simulation results of temperature distribution during
active regeneration on the entrance and the end of CDPF are
shown in Figure 11. The temperature distributions in the CDPF
are simulated with 4 g/l soot loading. Figure 12 shows the
simulation results of temperature distribution on the entrance
of CDPF (CDPF_upstream) and the end of CDPF (CDPF_
Therefore, thermal oxidation of soot at CDPF is enhanced
when the exhaust temperature is greater than > 500 ℃ , and the
temperature spreads along the CDPF and continues to increase
due to the soot oxidation. The resulting heat released causes
a rapid increase in the temperature at the end of CDPF and
reaches regeneration temperature after 120 s from injecting
HC. High regeneration temperature may lead to damage to the
CDPF substrate due to thermal stress (maximum temperature
limit of filter wall is 1050 ℃ ) [23]. Therefore, it is important to
control the temperature of CDPF by controlling the amount of
diesel fuel injected upstream of DOC, and controlling the mass
flow rate of the exhaust gas.
Fig 12 Simulation Results of Transient Temperature Distribution
at the Entrance of CDPF (CDPF_Upstream) and the End of
CDPF (CDPF_Downstream) During Active Regeneration. The CDPF Initial Soot Loading is Set to 4 g/L
3.2 Regeneration Estimations and CDPF Model
The CDPF regeneration simulation is performed using diesel
injection upstream of DOC, while HC is injected into the
exhaust pipe at 100 s. Active regeneration process in CDPF
has been the focus in the following regeneration simulations.
Simulation results are compared to experimental (measured)
data in order to validate the numerical model. The experiment
is conducted by Dongfeng commercial diesel engine X7 with
steady low load engine operating condition (1 320 r/min, 320
Nm). For this investigation, CDPF soot loading is accumulated
to 4 g/L, inlet mass flow rate is 600 kg/h, and inlet temperature
is 339 ℃ .
Transient temperature, pressure drop and soot accumulation
of CDPF are simulated, and the regeneration (soot oxidation)
method is set as oxygen thermal regeneration with wall
catalytic reaction. Regeneration reactions considered in this
study are listed as follows:
2C(s)+O2 → 2CO,
C(s)+O2 → CO2,
CO+1 ⁄ 2 O2 → CO2,
C3 H6+9 ⁄ 2 O2 → 3CO2+3H2 O.
Figure 13 shows the transient temperature profile at the end of
CDPF during active regeneration, and maximum regeneration
temperature increases and reach 600 ℃ after activating the HC
Figure 14 is the transient pressure drop across the CDPF during
active regeneration, the pressure drop increased due to the
volumetric expansion occurring after 100 s when the injected
HC reacts inside the DOC. After 180 s, pressure drop stars to
decrease due to the initiation of soot oxidation at CDPF.
Figure 15 is the transient soot mass amount during active
regeneration inside CDPF. Initial soot mass was 4 g/L and soot
starts to oxidize at almost 180 s and cause pressure drop to
decrease as shown in Figure 14. Entire soot is regenerated at
almost 950 s.
Figure 13-15 are the comparison of measured data and
Measured data
t/ s
1 000
Fig 13 Comparison of Measured Data and Simulation Results
for Temperature Profile at the End of CDPF
Overall pressure drop / kPa
Measured data
t/ s
1 000
Fig 14 Comparison of Measured Data and Simulation Results for Pressure drop Profile along CDPF
Overall soot mass /(g·L-1)
Measured data
4 Conclusion
DOC-CDPF after-treatment system is very efficient in
controlling the PM emissions. Secondary fuel injection
(Hydrocarbon injection, HCI) is used to enhance exothermic
heat which is needed to raise CDPF temperature in order to
initiate soot regeneration. We observed that the hydrocarbon
(HC) injector location has a large influence on the HC
distribution at DOC. The simulation results of different
hydrocarbon injector locations are compared to optimize the
injector location and orientation to ensure optimal mixing
between injected HC and exhaust gas. HC uniformity index at
the entrance of CDPF is used to optimize the injector location.
HC species uniformity index for design“A”was around 0.96.
This index indicates that HC distribution at the entrance of
DOC was homogeneous since the location and orientation of
injector“A”allow good mixing with exhaust gas. Therefore, no
mixer is required for design“A”.
Simulation results of the temperature, pressure drop and soot
mass at the end of CDPF are compared with the experimental
data in order to validate the numerical model, and good
estimations are observed.
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