- Email: [email protected]
Soot formation and oxidation mechanisms in a diesel engine separated swirl combustion system
Fuel 257 (2019) 115955
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Full Length Article
Soot formation and oxidation mechanisms in a diesel engine separated swirl combustion system
T
⁎
Haiqin Zhou, Xiangrong Li , Fushui Liu School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Separated swirl combustion system A single-cylinder engine Soot formation Soot oxidation
The separated swirl combustion system (SSCS) is a new combustion system developed to improve fuel efficiency and reduce soot emissions in diesel engines. While soot emissions from the SSCS can be tested in a real-world single-cylinder engine, soot formation and oxidation cannot be; therefore, the mechanisms behind those processes have not yet been researched. To understand the mechanisms of soot formation and oxidation in the SSCS, soot evolution must be investigated using a simulation model. To bridge this gap, this study analyzed the combustion and emission performance of the SSCS under different speeds in a real-world single-cylinder engine. Then, a new phenomenological model was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The experiment results show that at 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. The simulation results show that the DSCS generates more incipient soot particles and soot mass than the SSCS, and surface soot oxidation is faster in the SSCS. The mechanisms analysis shows that the equivalence ratio is smaller in the SSCS than in the DSCS, so fewer incipient soot particles are generated, and the temperature is higher, which speeds up soot oxidation. Furthermore, the combustion duration is much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion and the exhaust valve opening is longer, granting more time for soot oxidation. Due to the decreased soot formation and faster soot oxidation, the soot mass is also lower in the SSCS than in the DSCS.
1. Introduction Given the negative environmental effects of diesel engines, significant research has been devoted to reducing the particulate matter (PM) that diesel engines emit [1–3]. PM is mainly composed of soot, which is produced during incomplete combustion of fuel at high temperatures. Diesel engines are the primary pollutants of soot, and soot accounts for 50–80% of all emission particles [4,5]. Around the world, comprehensive research has been conducted and stricter regulations have been implemented aimed at improving combustion performance and reducing emissions [6,7]. One of the most promising strategies is to optimize the shape of the combustion chamber to realize a more homogeneous fuel/air mixture by better guiding the air flow. The double swirl combustion system (DSCS) is a product of chamber-shape optimization efforts and is shown in Fig. 1. The DSCS design includes a circular ridge on the chamber wall. When the fuel collides with the circular ridge, two swirls are generated in the inner and outer chambers, which reduces the accumulation of fuel on the wall
⁎
and improves air utilization in the central area of the chamber. Experimental and simulation results show that the DSCS effectively reduces fuel consumption and soot emission. Fig. 2 shows a TCD combustion chamber, the design of which includes a cyclic structure on the wall that reduces soot emission by guiding the fuel to diffuse into a larger space. A similar cyclic structure, which improves air efficiency in the squish area of the chamber, is widely used in many diesel engine chambers. The circular ridge of the DSCS chamber improves air utilization in the central area of the chamber. The cyclic structure of the TCD chamber improves air utilization in the squish area of the chamber. To improve air efficiency in both areas of the chamber, the separated swirl combustion system (SSCS) was developed that makes use of the geometric advantages of both the DSCS and TCD chambers. Fig. 3 shows the SSCS chamber, the design of which includes the cyclic structure of the TCD chamber and the circular structure of the DSCS chamber. In the SSCS, there are two circular ridges (the first circular ridge and the second circular ridge), and the entire chamber consists of the inner chamber, the outer chamber and the separated
Corresponding author. E-mail address: [email protected] (X. Li).
https://doi.org/10.1016/j.fuel.2019.115955 Received 19 May 2019; Received in revised form 2 August 2019; Accepted 4 August 2019 Available online 19 August 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 5. The design principle of SSCS.
different sprays collide with the circular ridges in the chamber. When this happens, swirls form, which improves air utilization in the chamber and accelerates the fuel/air mixture process, as shown in Fig. 5. While soot emissions from the SSCS can be tested in a real-world single-cylinder engine, soot formation and oxidation cannot be; therefore, the mechanisms behind those processes have not yet been researched. To understand the mechanisms of soot formation and oxidation in the SSCS, soot evolution must be investigated using a simulation model. Existing soot models can be divided into three categories: 1) simplistic, 2) phenomenological and 3) complicated kinetic. Hiroyasu's simplistic model is most widely used to describe soot formation using two reaction steps [8]. The model can accurately predict soot distribution in high-temperature combustion, but oversimplification of the diesel soot formation processes becomes evident at low temperatures. A detailed kinetic soot model was developed by Frenklach et al. to study soot formation in premixed flames [9,10]. The model can predict the mean number density and soot volume fraction during the combustion process. However, it is computationally costly. To reduce computation time, a phenomenological soot modeling approach with reduced chemistry mechanisms is more useful for 3D computational fluid dynamics (CFD) engine simulations and can reduce the computational cost of simulating spray combustion. In this study, the combustion and emission performance of the SSCS under different speeds was tested in a real-world single-cylinder engine. Then, a new phenomenological soot model using KIVA-3V R2 code and integrated with a reduced n-heptane/PAH mechanism was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The research results are significant for informing the design of diesel engines to reduce soot emissions.
Fig. 1. Double swirl combustion system.
Fig. 2. TCD combustion system.
Fig. 3. SSCS chamber.
2. Analytical method 2.1. Experimental setup The experimental test was carried out on an 1132Z single-cylinder diesel engine. The system diagram is shown in Fig. 6. The main parameters of the single-cylinder engine are shown in Table 1. The Bosch electronic unit pump was used for fuel supply. The diameter and the pre-stroke of the plunger were 12 mm and 9 mm, respectively. The maximum absorption power of the AC electrical dynamometer was 160 kW, the maximum speed was 4500 r/min, the accuracy of the torque was ± 0.2% FS, and the speed accuracy was ± 2 r/min. To accurately measure real-time fuel consumption, a ToCeiL-CMF instantaneous fuel meter with fuel heating and thermostatic control was used. The response time was less than 0.1 s, and the measurement error was less than 0.12% FS. A Kistler 6052 with a maximum measurement pressure of 25 MPa was used to measure the cylinder pressure with an accuracy of 0.1% FSO. In the test, the Kibox transient data acquisition and analysis system was used to collect cylinder pressure, injection pressure, needle valve lift and other relevant information. The Kistler data acquisition box was also used to collect the inlet and outlet temperature and pressure, the fuel temperature and pressure and the cooling water temperature. A HORIBA MEXA-720 NOx analyzer was used to measure the NOx emission with an accuracy of ± 30 ppm (0–1000 ppm), and the AVL 415S smoke meter was used to measure the
Fig. 4. Spray angles.
chamber. The injector used in the SSCS has two types of holes: upper and lower. They are arranged in alternating order, and their angles differ, which renders two distinct sprays, as shown in Fig. 4. The 2
Fuel 257 (2019) 115955
H. Zhou, et al.
ToCeiL-CMF instantaneous fuel meter 1. Fuel injection pressure sensor 2. Needle lift sensor 3. In-cylinder pressure sensor Fuel supply 4. Air flow sensor pump Fuel 5. Intake air pressure sensor return 6. Intake air temperature sensor Water Water 7. Inlet water temperature sensor outlet inlet 8. Outlet water temperature sensor Fuel export 9. Oil temperature sensor VHN-16/8 10. Oil pressure sensor compressor PC1 11. Exhaust air temperature sensor Electronic Intake air 12. Exhaust air pressure sensor unit pump Fuel import
Fuel tank Water tank Water heater Oil tank Oil heater Oil pump
ECU
4
Oil return pump
1 6 Fuel injector
5
2
4
5
8
9
6
7
Data acquisition device
10 11
3 Water pump
Stable pressure Air Stable pressure box heater box
Piston
8 7
9
PC3 11 12 AVL 415S smoke meter
10
XXXX
MEXA-720 NOx analyzer
Exhaust air
Angle encoder Frequency PC4 multiplier
Electric dynamometer
PC3
Test engine
Control module
1 2 3
Kibox combustion analyzer
PC2
Fig. 6. Pedestal diagram of the engine. Table 1 Parameters of the single-cylinder engine. Parameter
value
Compression ratio Cylinder diameter Stroke Connecting rod length The number of nozzles Nozzle diameter
13.5 132 mm 145 mm 262 mm 8 0.27 mm
Fig. 8. The nozzle angles of the SSCS.
soot emission with an accuracy of ± 0.2 FSN. Fig. 7 shows the DSCS and SSCS chambers. The injector diameter of the two combustion systems used in the test was 0.27 mm, the number of nozzles was 8 and the needle valve opening pressure was 210 bar. The nozzle angle of the DSCS was 145°. The nozzle angles of the upper and lower holes of the SSCS were 165° and 105°, respectively, as shown in Fig. 8. The combustion and emission performance of the SSCS under different speeds was tested in a real-world single-cylinder engine. The test conditions are shown in Table 2. The power, torque, fuel consumption,
Table 2 Test conditions. Speed r/min
Injection advance angle °CA
Intake pressure kPa
Power/kW
1300 1500 1800 2100
10 11 13 14
210 230 230 230
28 36 44 50
inlet pressure, inlet temperature, cylinder head temperature and exhaust temperature were tested five times, and the results were averaged. The pressure was averaged over 100 combustion cycles. The NOx and soot emission was tested three times.
2.2. Simulation research 2.2.1. Lower carbon chemistry A skeletal kinetic mechanism comprised of 57 species and 176 reactions was applied for PRF (primary reference fuels) oxidation [11]. The ignition delay and key species were validated with the measured results in shock tubes and counter-flow diffusion flames. Fig. 7. DSSC and SSCS chambers. 3
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 9. Reaction pathway diagram.
Fig. 11. Ignition delay timing at equivalence ratios equal to 0.5.
Fig. 10. Oxidation effect on soot number density.
2.2.2. PAH chemistry The skeletal PAH formation mechanism was reduced using DRGEP (direct relation graph error propagation) and sensitivity analysis methods according to the detailed mechanism developed by Slavinskaya et al. [12]. The mechanism included 13 species and 33 reactions. The reaction pathway diagram is shown in Fig. 9. The mechanism describes the formation process from A1 to A4. 2.2.3. Soot model A new soot model using KIVA-3V R2 code and integrated with a reduced heptane/PAH (polycyclic aromatic hydrocarbons) mechanism was developed and used to simulate soot behavior in the SSCS under different speeds. The effect of PAHs and polyene on soot inception was considered in the model. An A1 adsorption model was used to describe the surface growth process, and the effect of oxidation on number
Fig. 12. Ignition delay timing at equivalence ratios equal to 1.0.
4
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 14. Mole fraction of important species of Flame B.
Fig. 13. Mole fraction of important species of Flame A.
density was also considered. The model is described below: (1) Soot inception The experiment results show that PAHs and polyene are critical intermediate species for the generation of soot particles. Diacetylene (C4 H2 ) and naphthalene (A2 ) were presumed to have an equal effect on the soot particle nucleation process in Tao’s soot model [13], but the effect of PAHs on soot inception was not considered in Tao’s model. Pyrene (A 4 ) was the only species used to calculate the soot inception process in a model developed by Rolf D. Reitz [14]. Considering the abovementioned shortcomings, the model proposed herein considers the inception reaction related to both polyene and aromatic species. The reaction rate was proportional toC4 H2 , A2 and A 4 concentration, as shown in Eq. (1). ω̇1
C4 H2 → 4C(pre) + H2 ω̇ 2
C10 H8 (A2) → 10C(pre) ω̇3
) [C H ] + 4H ω̇ = 1.0 × 10 × exp ( ) [A ] + 5H ω̇ = 5.0 × 10 × exp ( ) [A ]
C16 H10 (A 4) → 16C(pre)
ω̇ 1 = 1.0 × 107 × exp
2
2
3
- 5000 RT
- 5000 RT
7
2
(
9
- 3974 RT
4
2
2
4
Fig. 15. Computational grid at TDC of DSCS.
⎫ ⎪ ⎪ ⎬ ⎪ ⎪ ⎭ (1)
where ω̇ is the reaction rate, [C4 H2] indicates the concentration of C4 H2 in mole/cm3 . Henceforth, [ ] indicates the concentration of species. R is the gas constant, and T is temperature.
Fig. 16. Computational grid at TDC of SSC. 5
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 17. The comparisons of pressure and heat release rate at 1300 r/min.
Fig. 20. The comparisons of pressure and heat release rate at 2100 r/min.
Fig. 18. The comparisons of pressure and heat release rate at 1500 r/min. Fig. 21. The comparisons of soot emission.
Fig. 19. The comparisons of pressure and heat release rate at 1800 r/min.
Fig. 22. Error threshold of soot emission.
(2) C2H2-assisted surface growth
ω̇4
C(pre) + C2 H2 → 3C(s) + H2
Established research indicates that surface growth contributes considerably to soot particle mass growth. A detailed model developed by Harris and Weiner has shown that the surface growth rate is first-order in the acetylene concentration [15,16]. In this study, the acetylene adsorption model was used to describe this process. The process was proportional to the C2 H2 concentration and the soot particle surface area. TheC2 H2 -assisted surface growth is shown as Eq. (2).
ω̇4 = 9.0 × 10 4 × exp( S=
ds =
(
−12100 )[C2 H2 ] RT
S
π·ds2 Ns 6MWC ys πNs ρs
)
1 3
(2)
S is the soot surface area, ds is the particle size, Ns is the soot number density, MWC is the molecular weight of carbon, ys is the soot mass fraction, ρs is the soot density, and 1.8g/ cm3 was used in this study [17].
6
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 26. Incipient soot particle distribution at 1500 r/min.
Fig. 23. BSFC and thermal efficiency.
Fig. 27. Incipient soot particle distribution at 1800 r/min.
Fig. 24. Soot and NOx at different speeds.
Fig. 28. Incipient soot particle distribution at 2100 r/min.
(3) PAH-assisted surface growth PAH-assisted surface growth was used in a detailed soot model developed by Frenklach and Wang [10,18]. An A1 adsorption model was used to describe the surface growth process in Bin Pang’s model. In this study, the PAH-assisted surface growth is shown as Eq. (3). Fig. 25. Incipient soot particle distribution at 1300 r/min.
ω5̇
C(pre) + A1 → 7C(s) + 3H2 (4) Surface oxidation 7
ω̇5 = 1.03 × 10 4 × exp(
−6159 )[A1] S RT
(3)
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 29. Soot mass distribution at 1300 r/min.
Fig. 32. Soot mass distribution at 2100 r/min.
In this step, the semi-empirical model-Nagle and StricklandConstable (NSC) oxidation model was applied as part of the oxidation model [19,20], as shown in Eq. (4). ω̇6
1
C(s) + 2 O2 → CO ω̇ 6 =
12 ⎛ MWC
⎝
x=
(
kA P O2 1 + k Z P O2
)x + k P
B O2
P O2 P O2 + (k T / k B )
{
kA = 3.0exp( −15800/ T )
kB = 8.0 × 10−3exp( −7640/ T ) kT = 1.51 ×
(1 − x ) ⎞ S ⎠
105exp( −49800/ T )
kZ = 27.0exp(3000/ T )
{
g cm2 s atm
{ {
}
g
} }
cm2 s atm g
cm2 s atm
g cm2 s atm
}
(4)
PO2 is the partial pressure of oxygen. (5) Soot oxidation
Fig. 30. Soot mass distribution at 1500 r/min.
Many experiment results have shown that the Hydroxyl (OH) radical also significantly affects the oxidation process of soot particles. In this model, soot oxidized by the OH radical was also considered, as shown in Eq. (5). ω̇ 7
C(s) + OH → CO +
1 H2 2
ω̇ 7 = γOH ×
3nOH ⎛ 8RT ⎞ S NA ⎝ πMOH ⎠ ⎜
⎟
(6)
γOH is the OH collision efficiency (0.13 in this study), NA is the Avogadro constant, nOH is the OH number density, and MOH is the mole fraction. (6) Soot particle coagulation In this step, the soot mass remained almost the same; however, the number density changed significantly. The collision frequency in the present model used the Pratsinis and Kazakov’s expression [21]. kfm knc
ω̇co =
kfm + knc
Fig. 31. Soot mass distribution at 1800 r/min.
kfm = 4α knc =
8kB T μ
6kB Tds ρs
(1 + 1.257kn )
kn = 2l/ ds
(6)
α is the Van der Waals factor (2.0 in this study), kn is the Knudsen number, kB is the Boltzmann constant, and l is the mean free path for a gas molecule. (7) Soot precursor oxidation
8
Fuel 257 (2019) 115955
H. Zhou, et al.
Crank angle
DSCS
SSCS
DSCS
SSCS
1300 r/min
1300 r/min
1500 r/min
1500 r/min
360
365
370 Crank angle
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
360
365
370
Fig. 33. Soot number distribution of the two combustion systems under different speeds.
1) RG _O ≥ 0 .
The soot precursor’s oxidation process was described according to Tao and Bi’s model. ω̇8
C(pre) + OH → CO +
1 H2 2
ω̇ 8 = 1.0 × 109 × exp(
In this situation, the soot surface growth was faster than soot oxidation, such that the total soot mass increased. The soot molar concentration was calculated by Eq. (12).
−39740 )[C(pre) ] [OH ] RT (7)
N n (i 4) = N n − 1 (i 4) + (ω̇ pre − ω̇co) × Δt
(8) The effect of oxidation on number density
dm (i 4) dt
(12)
According to the process described above, the soot mass concentration was calculated by Eq. (8).
2) RG _O < 0 and
dm (soot) = ω̇ pre × MWInc + (ω̇gr − ω̇ox ) × MWc dt
In this situation, the soot oxidation was faster than the soot surface growth, such that the total soot mass decreased. The soot molar concentration was calculated by Eq. (13).
(8)
In one computational cell, the increase of soot mass between soot particle surface growth and oxidation was given by Eq. (9).
RG _O = (ω̇gr − ω̇ox ) × MWc
< 0.
N n (i 4) = N n − 1 (i 4) − ω̇co × Δt
(13)
(9) 3) RG _O < 0 ,
The incipient soot particles and mature soot particles were found initially for each timestep in one computational cell at the current time, as shown in Fig. 10. The mean particle size and molecular weight was given by Eqs. (10) and (11), respectively.
dm (i 4) dt
≥ 0 and dn (i 4) ≥ 1.28nm .
In this situation, soot oxidation was faster than surface growth, but the total mass increased. This was due to an increase of incipient soot particles. The soot molar concentration was calculated by Eq. (14).
1/3
6mn (i 4) ⎞ dn (i 4) = ⎜⎛ ⎟ n (i 4) ρ πN s⎠ ⎝
mn (i 4) MW n (i 4) = n N (i 4)
mn (i 4)
N n (i 4) = N n − 1 (i 4) + (ω̇ pre +
(10)
(11)
4) RG _O < 0 ,
N n (i 4)
is the soot mass concentration, and is the soot molar concentration. Considering the oxidation effect on soot number, four simulation situations are discussed below:
dmn (i 4) dt
RG _O × ω̇ pre − ω̇co ) × Δt MWInc
(14)
≥ 0 and dn (i 4) < 1.28nm .
In this situation, the molar concentrations of both the incipient and mature soot particles decreased due to the oxidation effect. The soot molar concentration was calculated by Eq. (15). 9
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
SSCS
DSCS
SSCS
1300 r/min
1300 r/min
1500 r/min
1500 r/min
Crank angle
365
370
375
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
Crank angle
365
370
375
Fig. 34. Soot formation of the two combustion systems under different speeds.
degree center). To calculate the fuel parcel injection dynamics, the 'blob' model was used. For calculating the low Mach-number turbulent effect on transportation and flow field, the RNG k-ε model was used. The Taylor analogy breakup (TAB) model was used for breakup of the liquid fuel, and the O’Rourke model was used for the collision simulation of spray droplets [23–25]. The 3D CFD simulation was based on the KIVA-3 V release 2 code (see Figs. 17–21). Comparisons of pressure, heat release rate (HRR) and soot emission between the simulation and experimental results are shown below. The simulation condition is shown in Table 2. The errors of pressure and HRR were approximately 0.03% and 0.42%, respectively. The error threshold of soot emission is shown in Fig. 22, and the error was less than 10%. It was observed that the simulation results and experiment data agree well.
N n (i 4) RG _O ⎞ = ⎜⎛1 + ⎟ ω̇ pre Δt × MWInc + N n − 1 (i 4) MW n − 1 (i 4) ⎠ ⎝ × (ω̇ pre Δt + N n − 1 (i 4)) − ω̇co Δt
(15)
3. Model validation 3.1. Validating the reduction mechanism Figs. 11 and 12 compare the ignition delay timing at equivalence ratios equal to 0.5 and 1.0. It was observed that the simulation results and experiment data agree well, which means that the reaction mechanism proposed herein accurately predicts the ignition delay of nheptane oxidation. Figs. 13 and 14 show the mole fraction of key species. The experimental data was taken from Oßwald [22]. It was observed that the simulation results and experiment data agree well, especially the aromatic species, which are the key species in soot formation.
4. Results and discussion 4.1. Combustion and emission performance of SSCS under different speeds Figs. 23 and 24 show the combustion performance and emission characteristics of the DSCS and SSCS under different speeds in a singlecylinder engine. It can be observed that the brake-specific fuel consumption (BSFC) was lower and the indicated thermal efficiency was higher in the SSCS than in the DSCS at various engine speeds. At 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. The NOx emission in the SSCS was higher than in the DSCS
3.2. Validating the combustion and soot emission model In this study, a 90° sector mesh was developed and simulated for the DSCS and the SSCS. The inlet and exhaust processes were not considered in the calculation. The computation interval was taken from the inlet valve closing to the exhaust valve opening (239.5–460°CA). Figs. 15 and 16 show the grid of the combustion chamber at TDC (top 10
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
SSCS
DSCS
SSCS
1500 r/min
1500 r/min
Crank angle 1300 r/min
1300 r/min
365
370
375
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
Crank angle
365
370
375
Fig. 35. Soot oxidation of the two combustion systems under different speeds.
365
CA
Fig. 36. Equivalence ratio distribution.
the first step of soot formation. The incipient soot particle mass has a small impact on the total soot mass, but it provides the foundation of the soot surface and condensation. More incipient soot particles were generated in the DSCS, which created better conditions for soot formation. Figs. 29–32 show soot mass at different speeds. It can be observed that the soot mass increased first and then decreased. During the combustion process, the soot mass in the SSCS was less than that in the DSCS. Fig. 33 shows the soot number on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that significant soot was produced at the early stage of combustion, and then the soot number decreased, while the soot number in the DSCS was still higher than in the SSCS during combustion. Fig. 34 shows the surface adsorption of soot on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that more surface adsorption formed at the early stage of combustion, and it then
under different speeds. However, the higher NOx emission can be reduced by after-treatment. Since the performance of the DSCS has been verified, it can be concluded that the SSCS, which has better combustion and emission performance under different speeds, has strong application prospects. 4.2. Soot formation and oxidation characteristics in the SSCS under different speeds Figs. 25–28 show the incipient soot particles of the two combustion systems under different speeds. It can be observed that most incipient soot particles were produced at the early stage of combustion. The incipient soot particles of the DSCS were distributed in the outer chamber. At 380°CA, there was still a significant number of incipient soot particles in the chamber. For the SSCS, the incipient soot particles were distributed near the first circular ridge and decreased quickly. At 380 °CA, the incipient soot particles were minimal. Soot nucleation is 11
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 40. Cylinder temperature at 1500 r/min.
Fig. 37. The equivalent ratio of 0.66 to 2.
Fig. 41. Cylinder temperature at 1800 r/min.
Fig. 38. The equivalent ratio greater than 2.
Fig. 42. Cylinder temperature at 2100 r/min.
4.3. Mechanisms of soot formation and soot oxidation in the SSCS 4.3.1. Soot formation in the SSCS Fig. 36 shows the equivalence ratio distribution at 365° CA. It can be observed that the area of equivalence ratios greater than 2 was larger in the DSCS, and the main distribution was in the outer chamber. Kitamura's research shows that the regions with an equivalence ratio greater than 2 are more likely to generate soot, so more incipient soot particles were produced in the DSCS. Reitz found that the equivalence ratio of the combustion is in the range of 0.66 to 2. Kitamura’s research shows that soot is easily produced in areas where the equivalence ratio is greater than 2. Fig. 37 shows the equivalence ratio of 0.66 to 2, and Fig. 38 shows the equivalence ratio greater than 2. It can be observed that the equivalence ratio in the range of 0.66 to 2 was higher in the SSCS than in the DSCS, and the equivalence ratio greater than 2 was lower in the SSCS than in the DCSC, indicating that the SSCS better supports the fuel/air mixture, which reduces soot formation.
Fig. 39. Cylinder temperature at 1300 r/min.
decreased. In the DSCS, the surface adsorption of soot was distributed in the outer chamber. In the SSCS, the surface adsorption was distributed near the first circular ridge and decreased quickly. At 375 °CA, there was still more surface adsorption of soot in the DSCS than in the SSCS, which means more soot formed in the DSCS during combustion. Fig. 35 shows the surface oxidation of soot on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that the soot oxidation increased first and then decreased quickly.
4.3.2. Soot oxidation in the SSCS Figs. 39–42 show the experimental cylinder temperatures of the two combustion systems at different speeds. It can be observed that the 12
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
365
CA
370
CA
375
CA
SSCS
period and ended at the time of maximum temperature. The afterburning period followed the controlled combustion period and ended at the time when the cumulative heat release reached 98% of the maximum cumulative heat release. It was observed that the controlled combustion period ended sooner in the SSCS than in the DSCS. At 1800 r/min, the crank angle at the end of the controlled combustion was 24.4°CA, 1.6°CA earlier than in the DSCS, which indicates that the SSCS improves the fuel/air mixture and accelerates the main combustion process. The combustion duration was much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. In summary of the above analysis, the equivalence ratios were smaller and the fuel/air mixture was more homogenous in the SSCS than in the DSCS, so less incipient soot particles were produced. The combustion temperature was higher and the area of OH distribution was larger. This higher temperature helped soot oxidation, so the oxidation rate was faster in the SSCS than in the DSCS. In addition, the combustion duration was much shorter, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. Due to the lower soot formation rate and higher soot oxidation rate, the soot mass was lower in the SSCS than in the DSCS. 5. Conclusion
Fig. 43. OH distribution of the two combustion systems.
This study analyzed the combustion and emission performance of the SSCS under different speeds in a real-world single-cylinder engine. Then, a new phenomenological model was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The results are as follows: (1) The brake-specific fuel consumption (BSFC) was lower and the indicated thermal efficiency was higher in the SSCS than in the DSCS at different engine speeds. At 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. (2) The equivalence ratios were smaller and the fuel/air mixture was more homogenous in the SSCS than in the DSCS, so less incipient soot particles were produced. (3) The combustion temperature was higher in the SSCS than in the DSCS. This higher temperature sped up soot oxidation. (4) The combustion duration was much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. (5) Due to the lower soot formation rate and higher soot oxidation rate, the soot mass was lower in the SSCS than in the DSCS.
Fig. 44. Combustion phase of the two combustion systems.
difference between the two combustion systems was minimal at the early stage of combustion. However, at 375°CA, the cylinder temperature in the SSCS was much higher than in the DSCS. A higher temperature helps soot oxidation, so the oxidation rate was faster in the SSCS. Fig. 43 shows the OH distribution of the two combustion systems. It can be observed that the area of the OH distribution was larger in the SSCS than in the DSCS. Because the OH radical significantly affects the oxidation process of soot particles, soot in the SSCS was more likely to be oxidized, so less soot was produced. Fig. 44 shows the combustion phase of the two systems at different speeds. The combustion process was divided into four periods: 1) ignition delay, 2) rapid combustion, 3) controlled combustion and 4) after-burning. The ignition delay period started when the needle lift was greater than zero and ended at the separation point of the cylinder pressure from the motoring pressure. The rapid combustion period followed the ignition delay period and ended at the trough of the HRR. The controlled combustion period followed the rapid combustion
References [1] Heinz Burtscher. Physical characterization of particulate emissions from diesel engines: a review. J Aerosol Sci 2005;36(7):896–932. [2] Smith Owen I. Fundamentals of soot formation in flames with application to diesel engine particulate emissions. Prog Energy Combust Sci 1981;7(4):275–91. [3] Wang Yinhui, Zheng Rong, Qin Yanhong, et al. The impact of fuel compositions on the particulate emissions of direct injection gasoline engine. Fuel 2016;166:543–52. [4] Tse H, Leung CW, Cheung CS. Investigation on the combustion characteristics and particulate emissions from a diesel engine fueled with diesel-biodiesel-ethanol blends. Energy 2015;83:343–50. [5] Zhi-Hui Zhang, Rajasekhar Balasubramanian. Influence of butanol addition to diesel–biodiesel blend on engine performance and particulate emissions of a stationary diesel engine. Elsevier; 2014. p. 530–6. [6] XiangRong Li, Haiqin Zhou, LiWang Su, et al. Combustion and emission characteristics of a lateral swirl combustion system for DI diesel engines under low excess air ratio conditions. Fuel 2016;184:672–80. [7] Ganesh D, Nagarajan G. Homogeneous charge compression ignition (HCCI) combustion of diesel fuel with external mixture formation. Energy 2010;35(1):148–57. [8] Hiroyuki Hiroyasu, Toshikazu Kadota, Masataka Arai. Development and use of a
13
Fuel 257 (2019) 115955
H. Zhou, et al.
[9] [10]
[11]
[12] [13]
[14]
[15] [16]
[17] Jie Hou, Fuwu Yan, Lee Timothy H, et al. Computational investigation on soot mechanism of diesel and diesel/n-butanol blend in constant volume chamber with various ambient temperatures. Energy Fuels 2016;31(1):916–31. [18] Michael Frenklach, Hai Wang. Detailed mechanism and modeling of soot particle formation. Springer; 1994. p. 165–92. [19] Neoh KG, Howard JB, Sarofim AF. Soot oxidation in flames. Springer; 1981. p. 261–82. [20] Walls JR, Strickland-Constable RF. Oxidation of carbon between 1000–2400 C. Carbon 1964;1(3):333–8. [21] Andrei Kazakov, Michael Frenklach. Dynamic modeling of soot particle coagulation and aggregation: implementation with the method of moments and application to high-pressure laminar premixed flames. Combust Flame 1998;114(3–4):484–501. [22] Angew Chem Int Ed 2010;49(21):3572–97. https://doi.org/10.1002/anie. 200905335. [23] Mingi Choi, Jingeun Song, Sungwook Park. Modeling of the fuel injection and combustion process in a CNG direct injection engine. Fuel 2016;179:168–78. [24] Joonho Jeon, Tae Lee Jong, Il Kwon Sang, et al. Combustion performance, flame, and soot characteristics of gasoline–diesel pre-blended fuel in an optical compression-ignition engine. Energy Convers Manage 2016;116:174–83. [25] Joonho Jeon, Sungwook Park. Effects of pilot injection strategies on the flame temperature and soot distributions in an optical CI engine fueled with biodiesel and conventional diesel. Appl Energy 2015;160:581–91.
spray combustion modeling to predict diesel engine efficiency and pollutant emissions: part 1 combustion modeling. Bull JSME 1983;26(214):569–75. Michael Frenklach, Hai Wang. Detailed modeling of soot particle nucleation and growth. Elsevier; 1991. p. 1559–66. Hai Wang, Michael Frenklach. A detailed kinetic modeling study of aromatics formation in laminar premixed acetylene and ethylene flames. Combust Flame 1997;110(1–2):173–221. Huang J, Hill PG, Bushe WK, et al. Shock-tube study of methane ignition under engine-relevant conditions: experiments and modeling. Combust Flame 2004;136(1–2):25–42. Slavinskaya NA, Frank P. A modelling study of aromatic soot precursors formation in laminar methane and ethene flames. Combust Flame 2009;156(9):1705–22. Feng Tao, Reitz Rolf D, Foster David E, et al. Nine-step phenomenological diesel soot model validated over a wide range of engine conditions. Int J Therm Sci 2009;48(6):1223–34. Gokul Vishwanathan, Reitz Rolf D. Development of a practical soot modeling approach and its application to low-temperature diesel combustion. Combust Sci Technol 2010;182(8):1050–82. Harris Stephen J, Weiner Anita M. Determination of the rate constant for soot surface growth. Combust Sci Technol 1983;32(5–6):267–75. Harris Stephen J, Weiner Anita M, Blint Richard J. Formation of small aromatic molecules in a sooting ethylene flame. Combust Flame 1988;72(1):91–109.
14
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Full Length Article
Soot formation and oxidation mechanisms in a diesel engine separated swirl combustion system
T
⁎
Haiqin Zhou, Xiangrong Li , Fushui Liu School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Separated swirl combustion system A single-cylinder engine Soot formation Soot oxidation
The separated swirl combustion system (SSCS) is a new combustion system developed to improve fuel efficiency and reduce soot emissions in diesel engines. While soot emissions from the SSCS can be tested in a real-world single-cylinder engine, soot formation and oxidation cannot be; therefore, the mechanisms behind those processes have not yet been researched. To understand the mechanisms of soot formation and oxidation in the SSCS, soot evolution must be investigated using a simulation model. To bridge this gap, this study analyzed the combustion and emission performance of the SSCS under different speeds in a real-world single-cylinder engine. Then, a new phenomenological model was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The experiment results show that at 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. The simulation results show that the DSCS generates more incipient soot particles and soot mass than the SSCS, and surface soot oxidation is faster in the SSCS. The mechanisms analysis shows that the equivalence ratio is smaller in the SSCS than in the DSCS, so fewer incipient soot particles are generated, and the temperature is higher, which speeds up soot oxidation. Furthermore, the combustion duration is much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion and the exhaust valve opening is longer, granting more time for soot oxidation. Due to the decreased soot formation and faster soot oxidation, the soot mass is also lower in the SSCS than in the DSCS.
1. Introduction Given the negative environmental effects of diesel engines, significant research has been devoted to reducing the particulate matter (PM) that diesel engines emit [1–3]. PM is mainly composed of soot, which is produced during incomplete combustion of fuel at high temperatures. Diesel engines are the primary pollutants of soot, and soot accounts for 50–80% of all emission particles [4,5]. Around the world, comprehensive research has been conducted and stricter regulations have been implemented aimed at improving combustion performance and reducing emissions [6,7]. One of the most promising strategies is to optimize the shape of the combustion chamber to realize a more homogeneous fuel/air mixture by better guiding the air flow. The double swirl combustion system (DSCS) is a product of chamber-shape optimization efforts and is shown in Fig. 1. The DSCS design includes a circular ridge on the chamber wall. When the fuel collides with the circular ridge, two swirls are generated in the inner and outer chambers, which reduces the accumulation of fuel on the wall
⁎
and improves air utilization in the central area of the chamber. Experimental and simulation results show that the DSCS effectively reduces fuel consumption and soot emission. Fig. 2 shows a TCD combustion chamber, the design of which includes a cyclic structure on the wall that reduces soot emission by guiding the fuel to diffuse into a larger space. A similar cyclic structure, which improves air efficiency in the squish area of the chamber, is widely used in many diesel engine chambers. The circular ridge of the DSCS chamber improves air utilization in the central area of the chamber. The cyclic structure of the TCD chamber improves air utilization in the squish area of the chamber. To improve air efficiency in both areas of the chamber, the separated swirl combustion system (SSCS) was developed that makes use of the geometric advantages of both the DSCS and TCD chambers. Fig. 3 shows the SSCS chamber, the design of which includes the cyclic structure of the TCD chamber and the circular structure of the DSCS chamber. In the SSCS, there are two circular ridges (the first circular ridge and the second circular ridge), and the entire chamber consists of the inner chamber, the outer chamber and the separated
Corresponding author. E-mail address: [email protected] (X. Li).
https://doi.org/10.1016/j.fuel.2019.115955 Received 19 May 2019; Received in revised form 2 August 2019; Accepted 4 August 2019 Available online 19 August 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 5. The design principle of SSCS.
different sprays collide with the circular ridges in the chamber. When this happens, swirls form, which improves air utilization in the chamber and accelerates the fuel/air mixture process, as shown in Fig. 5. While soot emissions from the SSCS can be tested in a real-world single-cylinder engine, soot formation and oxidation cannot be; therefore, the mechanisms behind those processes have not yet been researched. To understand the mechanisms of soot formation and oxidation in the SSCS, soot evolution must be investigated using a simulation model. Existing soot models can be divided into three categories: 1) simplistic, 2) phenomenological and 3) complicated kinetic. Hiroyasu's simplistic model is most widely used to describe soot formation using two reaction steps [8]. The model can accurately predict soot distribution in high-temperature combustion, but oversimplification of the diesel soot formation processes becomes evident at low temperatures. A detailed kinetic soot model was developed by Frenklach et al. to study soot formation in premixed flames [9,10]. The model can predict the mean number density and soot volume fraction during the combustion process. However, it is computationally costly. To reduce computation time, a phenomenological soot modeling approach with reduced chemistry mechanisms is more useful for 3D computational fluid dynamics (CFD) engine simulations and can reduce the computational cost of simulating spray combustion. In this study, the combustion and emission performance of the SSCS under different speeds was tested in a real-world single-cylinder engine. Then, a new phenomenological soot model using KIVA-3V R2 code and integrated with a reduced n-heptane/PAH mechanism was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The research results are significant for informing the design of diesel engines to reduce soot emissions.
Fig. 1. Double swirl combustion system.
Fig. 2. TCD combustion system.
Fig. 3. SSCS chamber.
2. Analytical method 2.1. Experimental setup The experimental test was carried out on an 1132Z single-cylinder diesel engine. The system diagram is shown in Fig. 6. The main parameters of the single-cylinder engine are shown in Table 1. The Bosch electronic unit pump was used for fuel supply. The diameter and the pre-stroke of the plunger were 12 mm and 9 mm, respectively. The maximum absorption power of the AC electrical dynamometer was 160 kW, the maximum speed was 4500 r/min, the accuracy of the torque was ± 0.2% FS, and the speed accuracy was ± 2 r/min. To accurately measure real-time fuel consumption, a ToCeiL-CMF instantaneous fuel meter with fuel heating and thermostatic control was used. The response time was less than 0.1 s, and the measurement error was less than 0.12% FS. A Kistler 6052 with a maximum measurement pressure of 25 MPa was used to measure the cylinder pressure with an accuracy of 0.1% FSO. In the test, the Kibox transient data acquisition and analysis system was used to collect cylinder pressure, injection pressure, needle valve lift and other relevant information. The Kistler data acquisition box was also used to collect the inlet and outlet temperature and pressure, the fuel temperature and pressure and the cooling water temperature. A HORIBA MEXA-720 NOx analyzer was used to measure the NOx emission with an accuracy of ± 30 ppm (0–1000 ppm), and the AVL 415S smoke meter was used to measure the
Fig. 4. Spray angles.
chamber. The injector used in the SSCS has two types of holes: upper and lower. They are arranged in alternating order, and their angles differ, which renders two distinct sprays, as shown in Fig. 4. The 2
Fuel 257 (2019) 115955
H. Zhou, et al.
ToCeiL-CMF instantaneous fuel meter 1. Fuel injection pressure sensor 2. Needle lift sensor 3. In-cylinder pressure sensor Fuel supply 4. Air flow sensor pump Fuel 5. Intake air pressure sensor return 6. Intake air temperature sensor Water Water 7. Inlet water temperature sensor outlet inlet 8. Outlet water temperature sensor Fuel export 9. Oil temperature sensor VHN-16/8 10. Oil pressure sensor compressor PC1 11. Exhaust air temperature sensor Electronic Intake air 12. Exhaust air pressure sensor unit pump Fuel import
Fuel tank Water tank Water heater Oil tank Oil heater Oil pump
ECU
4
Oil return pump
1 6 Fuel injector
5
2
4
5
8
9
6
7
Data acquisition device
10 11
3 Water pump
Stable pressure Air Stable pressure box heater box
Piston
8 7
9
PC3 11 12 AVL 415S smoke meter
10
XXXX
MEXA-720 NOx analyzer
Exhaust air
Angle encoder Frequency PC4 multiplier
Electric dynamometer
PC3
Test engine
Control module
1 2 3
Kibox combustion analyzer
PC2
Fig. 6. Pedestal diagram of the engine. Table 1 Parameters of the single-cylinder engine. Parameter
value
Compression ratio Cylinder diameter Stroke Connecting rod length The number of nozzles Nozzle diameter
13.5 132 mm 145 mm 262 mm 8 0.27 mm
Fig. 8. The nozzle angles of the SSCS.
soot emission with an accuracy of ± 0.2 FSN. Fig. 7 shows the DSCS and SSCS chambers. The injector diameter of the two combustion systems used in the test was 0.27 mm, the number of nozzles was 8 and the needle valve opening pressure was 210 bar. The nozzle angle of the DSCS was 145°. The nozzle angles of the upper and lower holes of the SSCS were 165° and 105°, respectively, as shown in Fig. 8. The combustion and emission performance of the SSCS under different speeds was tested in a real-world single-cylinder engine. The test conditions are shown in Table 2. The power, torque, fuel consumption,
Table 2 Test conditions. Speed r/min
Injection advance angle °CA
Intake pressure kPa
Power/kW
1300 1500 1800 2100
10 11 13 14
210 230 230 230
28 36 44 50
inlet pressure, inlet temperature, cylinder head temperature and exhaust temperature were tested five times, and the results were averaged. The pressure was averaged over 100 combustion cycles. The NOx and soot emission was tested three times.
2.2. Simulation research 2.2.1. Lower carbon chemistry A skeletal kinetic mechanism comprised of 57 species and 176 reactions was applied for PRF (primary reference fuels) oxidation [11]. The ignition delay and key species were validated with the measured results in shock tubes and counter-flow diffusion flames. Fig. 7. DSSC and SSCS chambers. 3
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 9. Reaction pathway diagram.
Fig. 11. Ignition delay timing at equivalence ratios equal to 0.5.
Fig. 10. Oxidation effect on soot number density.
2.2.2. PAH chemistry The skeletal PAH formation mechanism was reduced using DRGEP (direct relation graph error propagation) and sensitivity analysis methods according to the detailed mechanism developed by Slavinskaya et al. [12]. The mechanism included 13 species and 33 reactions. The reaction pathway diagram is shown in Fig. 9. The mechanism describes the formation process from A1 to A4. 2.2.3. Soot model A new soot model using KIVA-3V R2 code and integrated with a reduced heptane/PAH (polycyclic aromatic hydrocarbons) mechanism was developed and used to simulate soot behavior in the SSCS under different speeds. The effect of PAHs and polyene on soot inception was considered in the model. An A1 adsorption model was used to describe the surface growth process, and the effect of oxidation on number
Fig. 12. Ignition delay timing at equivalence ratios equal to 1.0.
4
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 14. Mole fraction of important species of Flame B.
Fig. 13. Mole fraction of important species of Flame A.
density was also considered. The model is described below: (1) Soot inception The experiment results show that PAHs and polyene are critical intermediate species for the generation of soot particles. Diacetylene (C4 H2 ) and naphthalene (A2 ) were presumed to have an equal effect on the soot particle nucleation process in Tao’s soot model [13], but the effect of PAHs on soot inception was not considered in Tao’s model. Pyrene (A 4 ) was the only species used to calculate the soot inception process in a model developed by Rolf D. Reitz [14]. Considering the abovementioned shortcomings, the model proposed herein considers the inception reaction related to both polyene and aromatic species. The reaction rate was proportional toC4 H2 , A2 and A 4 concentration, as shown in Eq. (1). ω̇1
C4 H2 → 4C(pre) + H2 ω̇ 2
C10 H8 (A2) → 10C(pre) ω̇3
) [C H ] + 4H ω̇ = 1.0 × 10 × exp ( ) [A ] + 5H ω̇ = 5.0 × 10 × exp ( ) [A ]
C16 H10 (A 4) → 16C(pre)
ω̇ 1 = 1.0 × 107 × exp
2
2
3
- 5000 RT
- 5000 RT
7
2
(
9
- 3974 RT
4
2
2
4
Fig. 15. Computational grid at TDC of DSCS.
⎫ ⎪ ⎪ ⎬ ⎪ ⎪ ⎭ (1)
where ω̇ is the reaction rate, [C4 H2] indicates the concentration of C4 H2 in mole/cm3 . Henceforth, [ ] indicates the concentration of species. R is the gas constant, and T is temperature.
Fig. 16. Computational grid at TDC of SSC. 5
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 17. The comparisons of pressure and heat release rate at 1300 r/min.
Fig. 20. The comparisons of pressure and heat release rate at 2100 r/min.
Fig. 18. The comparisons of pressure and heat release rate at 1500 r/min. Fig. 21. The comparisons of soot emission.
Fig. 19. The comparisons of pressure and heat release rate at 1800 r/min.
Fig. 22. Error threshold of soot emission.
(2) C2H2-assisted surface growth
ω̇4
C(pre) + C2 H2 → 3C(s) + H2
Established research indicates that surface growth contributes considerably to soot particle mass growth. A detailed model developed by Harris and Weiner has shown that the surface growth rate is first-order in the acetylene concentration [15,16]. In this study, the acetylene adsorption model was used to describe this process. The process was proportional to the C2 H2 concentration and the soot particle surface area. TheC2 H2 -assisted surface growth is shown as Eq. (2).
ω̇4 = 9.0 × 10 4 × exp( S=
ds =
(
−12100 )[C2 H2 ] RT
S
π·ds2 Ns 6MWC ys πNs ρs
)
1 3
(2)
S is the soot surface area, ds is the particle size, Ns is the soot number density, MWC is the molecular weight of carbon, ys is the soot mass fraction, ρs is the soot density, and 1.8g/ cm3 was used in this study [17].
6
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 26. Incipient soot particle distribution at 1500 r/min.
Fig. 23. BSFC and thermal efficiency.
Fig. 27. Incipient soot particle distribution at 1800 r/min.
Fig. 24. Soot and NOx at different speeds.
Fig. 28. Incipient soot particle distribution at 2100 r/min.
(3) PAH-assisted surface growth PAH-assisted surface growth was used in a detailed soot model developed by Frenklach and Wang [10,18]. An A1 adsorption model was used to describe the surface growth process in Bin Pang’s model. In this study, the PAH-assisted surface growth is shown as Eq. (3). Fig. 25. Incipient soot particle distribution at 1300 r/min.
ω5̇
C(pre) + A1 → 7C(s) + 3H2 (4) Surface oxidation 7
ω̇5 = 1.03 × 10 4 × exp(
−6159 )[A1] S RT
(3)
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 29. Soot mass distribution at 1300 r/min.
Fig. 32. Soot mass distribution at 2100 r/min.
In this step, the semi-empirical model-Nagle and StricklandConstable (NSC) oxidation model was applied as part of the oxidation model [19,20], as shown in Eq. (4). ω̇6
1
C(s) + 2 O2 → CO ω̇ 6 =
12 ⎛ MWC
⎝
x=
(
kA P O2 1 + k Z P O2
)x + k P
B O2
P O2 P O2 + (k T / k B )
{
kA = 3.0exp( −15800/ T )
kB = 8.0 × 10−3exp( −7640/ T ) kT = 1.51 ×
(1 − x ) ⎞ S ⎠
105exp( −49800/ T )
kZ = 27.0exp(3000/ T )
{
g cm2 s atm
{ {
}
g
} }
cm2 s atm g
cm2 s atm
g cm2 s atm
}
(4)
PO2 is the partial pressure of oxygen. (5) Soot oxidation
Fig. 30. Soot mass distribution at 1500 r/min.
Many experiment results have shown that the Hydroxyl (OH) radical also significantly affects the oxidation process of soot particles. In this model, soot oxidized by the OH radical was also considered, as shown in Eq. (5). ω̇ 7
C(s) + OH → CO +
1 H2 2
ω̇ 7 = γOH ×
3nOH ⎛ 8RT ⎞ S NA ⎝ πMOH ⎠ ⎜
⎟
(6)
γOH is the OH collision efficiency (0.13 in this study), NA is the Avogadro constant, nOH is the OH number density, and MOH is the mole fraction. (6) Soot particle coagulation In this step, the soot mass remained almost the same; however, the number density changed significantly. The collision frequency in the present model used the Pratsinis and Kazakov’s expression [21]. kfm knc
ω̇co =
kfm + knc
Fig. 31. Soot mass distribution at 1800 r/min.
kfm = 4α knc =
8kB T μ
6kB Tds ρs
(1 + 1.257kn )
kn = 2l/ ds
(6)
α is the Van der Waals factor (2.0 in this study), kn is the Knudsen number, kB is the Boltzmann constant, and l is the mean free path for a gas molecule. (7) Soot precursor oxidation
8
Fuel 257 (2019) 115955
H. Zhou, et al.
Crank angle
DSCS
SSCS
DSCS
SSCS
1300 r/min
1300 r/min
1500 r/min
1500 r/min
360
365
370 Crank angle
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
360
365
370
Fig. 33. Soot number distribution of the two combustion systems under different speeds.
1) RG _O ≥ 0 .
The soot precursor’s oxidation process was described according to Tao and Bi’s model. ω̇8
C(pre) + OH → CO +
1 H2 2
ω̇ 8 = 1.0 × 109 × exp(
In this situation, the soot surface growth was faster than soot oxidation, such that the total soot mass increased. The soot molar concentration was calculated by Eq. (12).
−39740 )[C(pre) ] [OH ] RT (7)
N n (i 4) = N n − 1 (i 4) + (ω̇ pre − ω̇co) × Δt
(8) The effect of oxidation on number density
dm (i 4) dt
(12)
According to the process described above, the soot mass concentration was calculated by Eq. (8).
2) RG _O < 0 and
dm (soot) = ω̇ pre × MWInc + (ω̇gr − ω̇ox ) × MWc dt
In this situation, the soot oxidation was faster than the soot surface growth, such that the total soot mass decreased. The soot molar concentration was calculated by Eq. (13).
(8)
In one computational cell, the increase of soot mass between soot particle surface growth and oxidation was given by Eq. (9).
RG _O = (ω̇gr − ω̇ox ) × MWc
< 0.
N n (i 4) = N n − 1 (i 4) − ω̇co × Δt
(13)
(9) 3) RG _O < 0 ,
The incipient soot particles and mature soot particles were found initially for each timestep in one computational cell at the current time, as shown in Fig. 10. The mean particle size and molecular weight was given by Eqs. (10) and (11), respectively.
dm (i 4) dt
≥ 0 and dn (i 4) ≥ 1.28nm .
In this situation, soot oxidation was faster than surface growth, but the total mass increased. This was due to an increase of incipient soot particles. The soot molar concentration was calculated by Eq. (14).
1/3
6mn (i 4) ⎞ dn (i 4) = ⎜⎛ ⎟ n (i 4) ρ πN s⎠ ⎝
mn (i 4) MW n (i 4) = n N (i 4)
mn (i 4)
N n (i 4) = N n − 1 (i 4) + (ω̇ pre +
(10)
(11)
4) RG _O < 0 ,
N n (i 4)
is the soot mass concentration, and is the soot molar concentration. Considering the oxidation effect on soot number, four simulation situations are discussed below:
dmn (i 4) dt
RG _O × ω̇ pre − ω̇co ) × Δt MWInc
(14)
≥ 0 and dn (i 4) < 1.28nm .
In this situation, the molar concentrations of both the incipient and mature soot particles decreased due to the oxidation effect. The soot molar concentration was calculated by Eq. (15). 9
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
SSCS
DSCS
SSCS
1300 r/min
1300 r/min
1500 r/min
1500 r/min
Crank angle
365
370
375
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
Crank angle
365
370
375
Fig. 34. Soot formation of the two combustion systems under different speeds.
degree center). To calculate the fuel parcel injection dynamics, the 'blob' model was used. For calculating the low Mach-number turbulent effect on transportation and flow field, the RNG k-ε model was used. The Taylor analogy breakup (TAB) model was used for breakup of the liquid fuel, and the O’Rourke model was used for the collision simulation of spray droplets [23–25]. The 3D CFD simulation was based on the KIVA-3 V release 2 code (see Figs. 17–21). Comparisons of pressure, heat release rate (HRR) and soot emission between the simulation and experimental results are shown below. The simulation condition is shown in Table 2. The errors of pressure and HRR were approximately 0.03% and 0.42%, respectively. The error threshold of soot emission is shown in Fig. 22, and the error was less than 10%. It was observed that the simulation results and experiment data agree well.
N n (i 4) RG _O ⎞ = ⎜⎛1 + ⎟ ω̇ pre Δt × MWInc + N n − 1 (i 4) MW n − 1 (i 4) ⎠ ⎝ × (ω̇ pre Δt + N n − 1 (i 4)) − ω̇co Δt
(15)
3. Model validation 3.1. Validating the reduction mechanism Figs. 11 and 12 compare the ignition delay timing at equivalence ratios equal to 0.5 and 1.0. It was observed that the simulation results and experiment data agree well, which means that the reaction mechanism proposed herein accurately predicts the ignition delay of nheptane oxidation. Figs. 13 and 14 show the mole fraction of key species. The experimental data was taken from Oßwald [22]. It was observed that the simulation results and experiment data agree well, especially the aromatic species, which are the key species in soot formation.
4. Results and discussion 4.1. Combustion and emission performance of SSCS under different speeds Figs. 23 and 24 show the combustion performance and emission characteristics of the DSCS and SSCS under different speeds in a singlecylinder engine. It can be observed that the brake-specific fuel consumption (BSFC) was lower and the indicated thermal efficiency was higher in the SSCS than in the DSCS at various engine speeds. At 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. The NOx emission in the SSCS was higher than in the DSCS
3.2. Validating the combustion and soot emission model In this study, a 90° sector mesh was developed and simulated for the DSCS and the SSCS. The inlet and exhaust processes were not considered in the calculation. The computation interval was taken from the inlet valve closing to the exhaust valve opening (239.5–460°CA). Figs. 15 and 16 show the grid of the combustion chamber at TDC (top 10
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
SSCS
DSCS
SSCS
1500 r/min
1500 r/min
Crank angle 1300 r/min
1300 r/min
365
370
375
DSCS
SSCS
DSCS
SSCS
1800 r/min
1800 r/min
2100 r/min
2100 r/min
Crank angle
365
370
375
Fig. 35. Soot oxidation of the two combustion systems under different speeds.
365
CA
Fig. 36. Equivalence ratio distribution.
the first step of soot formation. The incipient soot particle mass has a small impact on the total soot mass, but it provides the foundation of the soot surface and condensation. More incipient soot particles were generated in the DSCS, which created better conditions for soot formation. Figs. 29–32 show soot mass at different speeds. It can be observed that the soot mass increased first and then decreased. During the combustion process, the soot mass in the SSCS was less than that in the DSCS. Fig. 33 shows the soot number on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that significant soot was produced at the early stage of combustion, and then the soot number decreased, while the soot number in the DSCS was still higher than in the SSCS during combustion. Fig. 34 shows the surface adsorption of soot on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that more surface adsorption formed at the early stage of combustion, and it then
under different speeds. However, the higher NOx emission can be reduced by after-treatment. Since the performance of the DSCS has been verified, it can be concluded that the SSCS, which has better combustion and emission performance under different speeds, has strong application prospects. 4.2. Soot formation and oxidation characteristics in the SSCS under different speeds Figs. 25–28 show the incipient soot particles of the two combustion systems under different speeds. It can be observed that most incipient soot particles were produced at the early stage of combustion. The incipient soot particles of the DSCS were distributed in the outer chamber. At 380°CA, there was still a significant number of incipient soot particles in the chamber. For the SSCS, the incipient soot particles were distributed near the first circular ridge and decreased quickly. At 380 °CA, the incipient soot particles were minimal. Soot nucleation is 11
Fuel 257 (2019) 115955
H. Zhou, et al.
Fig. 40. Cylinder temperature at 1500 r/min.
Fig. 37. The equivalent ratio of 0.66 to 2.
Fig. 41. Cylinder temperature at 1800 r/min.
Fig. 38. The equivalent ratio greater than 2.
Fig. 42. Cylinder temperature at 2100 r/min.
4.3. Mechanisms of soot formation and soot oxidation in the SSCS 4.3.1. Soot formation in the SSCS Fig. 36 shows the equivalence ratio distribution at 365° CA. It can be observed that the area of equivalence ratios greater than 2 was larger in the DSCS, and the main distribution was in the outer chamber. Kitamura's research shows that the regions with an equivalence ratio greater than 2 are more likely to generate soot, so more incipient soot particles were produced in the DSCS. Reitz found that the equivalence ratio of the combustion is in the range of 0.66 to 2. Kitamura’s research shows that soot is easily produced in areas where the equivalence ratio is greater than 2. Fig. 37 shows the equivalence ratio of 0.66 to 2, and Fig. 38 shows the equivalence ratio greater than 2. It can be observed that the equivalence ratio in the range of 0.66 to 2 was higher in the SSCS than in the DSCS, and the equivalence ratio greater than 2 was lower in the SSCS than in the DCSC, indicating that the SSCS better supports the fuel/air mixture, which reduces soot formation.
Fig. 39. Cylinder temperature at 1300 r/min.
decreased. In the DSCS, the surface adsorption of soot was distributed in the outer chamber. In the SSCS, the surface adsorption was distributed near the first circular ridge and decreased quickly. At 375 °CA, there was still more surface adsorption of soot in the DSCS than in the SSCS, which means more soot formed in the DSCS during combustion. Fig. 35 shows the surface oxidation of soot on the iso-surface of equivalence ratios equal to 1 and 2. It can be observed that the soot oxidation increased first and then decreased quickly.
4.3.2. Soot oxidation in the SSCS Figs. 39–42 show the experimental cylinder temperatures of the two combustion systems at different speeds. It can be observed that the 12
Fuel 257 (2019) 115955
H. Zhou, et al.
DSCS
365
CA
370
CA
375
CA
SSCS
period and ended at the time of maximum temperature. The afterburning period followed the controlled combustion period and ended at the time when the cumulative heat release reached 98% of the maximum cumulative heat release. It was observed that the controlled combustion period ended sooner in the SSCS than in the DSCS. At 1800 r/min, the crank angle at the end of the controlled combustion was 24.4°CA, 1.6°CA earlier than in the DSCS, which indicates that the SSCS improves the fuel/air mixture and accelerates the main combustion process. The combustion duration was much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. In summary of the above analysis, the equivalence ratios were smaller and the fuel/air mixture was more homogenous in the SSCS than in the DSCS, so less incipient soot particles were produced. The combustion temperature was higher and the area of OH distribution was larger. This higher temperature helped soot oxidation, so the oxidation rate was faster in the SSCS than in the DSCS. In addition, the combustion duration was much shorter, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. Due to the lower soot formation rate and higher soot oxidation rate, the soot mass was lower in the SSCS than in the DSCS. 5. Conclusion
Fig. 43. OH distribution of the two combustion systems.
This study analyzed the combustion and emission performance of the SSCS under different speeds in a real-world single-cylinder engine. Then, a new phenomenological model was developed and used to simulate soot formation and oxidation and reveal the mechanisms behind those processes. The SSCS with the new model was validated against a double swirl combustion system (DSCS). The results are as follows: (1) The brake-specific fuel consumption (BSFC) was lower and the indicated thermal efficiency was higher in the SSCS than in the DSCS at different engine speeds. At 2100 r/min, the SSCS significantly reduced fuel consumption (about 6.54 g/(kW h)) and soot emission (0.17 FSN) by 2.89% and 6.31%, respectively. (2) The equivalence ratios were smaller and the fuel/air mixture was more homogenous in the SSCS than in the DSCS, so less incipient soot particles were produced. (3) The combustion temperature was higher in the SSCS than in the DSCS. This higher temperature sped up soot oxidation. (4) The combustion duration was much shorter in the SSCS than in the DSCS, which means that the time between the end of combustion to the exhaust valve opening was longer, giving more time for soot particles to oxidize. (5) Due to the lower soot formation rate and higher soot oxidation rate, the soot mass was lower in the SSCS than in the DSCS.
Fig. 44. Combustion phase of the two combustion systems.
difference between the two combustion systems was minimal at the early stage of combustion. However, at 375°CA, the cylinder temperature in the SSCS was much higher than in the DSCS. A higher temperature helps soot oxidation, so the oxidation rate was faster in the SSCS. Fig. 43 shows the OH distribution of the two combustion systems. It can be observed that the area of the OH distribution was larger in the SSCS than in the DSCS. Because the OH radical significantly affects the oxidation process of soot particles, soot in the SSCS was more likely to be oxidized, so less soot was produced. Fig. 44 shows the combustion phase of the two systems at different speeds. The combustion process was divided into four periods: 1) ignition delay, 2) rapid combustion, 3) controlled combustion and 4) after-burning. The ignition delay period started when the needle lift was greater than zero and ended at the separation point of the cylinder pressure from the motoring pressure. The rapid combustion period followed the ignition delay period and ended at the trough of the HRR. The controlled combustion period followed the rapid combustion
References [1] Heinz Burtscher. Physical characterization of particulate emissions from diesel engines: a review. J Aerosol Sci 2005;36(7):896–932. [2] Smith Owen I. Fundamentals of soot formation in flames with application to diesel engine particulate emissions. Prog Energy Combust Sci 1981;7(4):275–91. [3] Wang Yinhui, Zheng Rong, Qin Yanhong, et al. The impact of fuel compositions on the particulate emissions of direct injection gasoline engine. Fuel 2016;166:543–52. [4] Tse H, Leung CW, Cheung CS. Investigation on the combustion characteristics and particulate emissions from a diesel engine fueled with diesel-biodiesel-ethanol blends. Energy 2015;83:343–50. [5] Zhi-Hui Zhang, Rajasekhar Balasubramanian. Influence of butanol addition to diesel–biodiesel blend on engine performance and particulate emissions of a stationary diesel engine. Elsevier; 2014. p. 530–6. [6] XiangRong Li, Haiqin Zhou, LiWang Su, et al. Combustion and emission characteristics of a lateral swirl combustion system for DI diesel engines under low excess air ratio conditions. Fuel 2016;184:672–80. [7] Ganesh D, Nagarajan G. Homogeneous charge compression ignition (HCCI) combustion of diesel fuel with external mixture formation. Energy 2010;35(1):148–57. [8] Hiroyuki Hiroyasu, Toshikazu Kadota, Masataka Arai. Development and use of a
13
Fuel 257 (2019) 115955
H. Zhou, et al.
[9] [10]
[11]
[12] [13]
[14]
[15] [16]
[17] Jie Hou, Fuwu Yan, Lee Timothy H, et al. Computational investigation on soot mechanism of diesel and diesel/n-butanol blend in constant volume chamber with various ambient temperatures. Energy Fuels 2016;31(1):916–31. [18] Michael Frenklach, Hai Wang. Detailed mechanism and modeling of soot particle formation. Springer; 1994. p. 165–92. [19] Neoh KG, Howard JB, Sarofim AF. Soot oxidation in flames. Springer; 1981. p. 261–82. [20] Walls JR, Strickland-Constable RF. Oxidation of carbon between 1000–2400 C. Carbon 1964;1(3):333–8. [21] Andrei Kazakov, Michael Frenklach. Dynamic modeling of soot particle coagulation and aggregation: implementation with the method of moments and application to high-pressure laminar premixed flames. Combust Flame 1998;114(3–4):484–501. [22] Angew Chem Int Ed 2010;49(21):3572–97. https://doi.org/10.1002/anie. 200905335. [23] Mingi Choi, Jingeun Song, Sungwook Park. Modeling of the fuel injection and combustion process in a CNG direct injection engine. Fuel 2016;179:168–78. [24] Joonho Jeon, Tae Lee Jong, Il Kwon Sang, et al. Combustion performance, flame, and soot characteristics of gasoline–diesel pre-blended fuel in an optical compression-ignition engine. Energy Convers Manage 2016;116:174–83. [25] Joonho Jeon, Sungwook Park. Effects of pilot injection strategies on the flame temperature and soot distributions in an optical CI engine fueled with biodiesel and conventional diesel. Appl Energy 2015;160:581–91.
spray combustion modeling to predict diesel engine efficiency and pollutant emissions: part 1 combustion modeling. Bull JSME 1983;26(214):569–75. Michael Frenklach, Hai Wang. Detailed modeling of soot particle nucleation and growth. Elsevier; 1991. p. 1559–66. Hai Wang, Michael Frenklach. A detailed kinetic modeling study of aromatics formation in laminar premixed acetylene and ethylene flames. Combust Flame 1997;110(1–2):173–221. Huang J, Hill PG, Bushe WK, et al. Shock-tube study of methane ignition under engine-relevant conditions: experiments and modeling. Combust Flame 2004;136(1–2):25–42. Slavinskaya NA, Frank P. A modelling study of aromatic soot precursors formation in laminar methane and ethene flames. Combust Flame 2009;156(9):1705–22. Feng Tao, Reitz Rolf D, Foster David E, et al. Nine-step phenomenological diesel soot model validated over a wide range of engine conditions. Int J Therm Sci 2009;48(6):1223–34. Gokul Vishwanathan, Reitz Rolf D. Development of a practical soot modeling approach and its application to low-temperature diesel combustion. Combust Sci Technol 2010;182(8):1050–82. Harris Stephen J, Weiner Anita M. Determination of the rate constant for soot surface growth. Combust Sci Technol 1983;32(5–6):267–75. Harris Stephen J, Weiner Anita M, Blint Richard J. Formation of small aromatic molecules in a sooting ethylene flame. Combust Flame 1988;72(1):91–109.
14