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Article

Filtration Efficiency and Regeneration Behavior in a Catalytic Diesel Particulate Filter with the Use of Diesel/Polyoxymethylene Dimethyl Ether Mixture

by
Hao Chen
1,2,*,
Xin Su
2,
Xiaochen Wang
2,*,
Fengyu Sun
2,
Peng Zhang
2,
Liming Geng
2 and
Haifeng Wang
1
1
Key Laboratory of Shaanxi Province for Development and Application of New Transportation Energy, School of Automobile, Chang’an University, Xi’an 710064, China
2
School of Automobile, Chang’an University, Xi’an 710064, China
*
Authors to whom correspondence should be addressed.
Catalysts 2021, 11(12), 1425; https://doi.org/10.3390/catal11121425
Submission received: 31 October 2021 / Revised: 19 November 2021 / Accepted: 20 November 2021 / Published: 24 November 2021
(This article belongs to the Section Environmental Catalysis)
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Abstract

:
Polyoxymethylene dimethyl ether (PODEn) is a promising diesel additive, especially in particulate matter reduction. However, how PODEn addition affects the filtration efficiency and regeneration process of a catalytic diesel particulate filter (cDPF) is still unknown. Therefore, this experimental work investigated the size-dependent particulate number removal efficiency under various engine loads and exhaust gas recirculation (EGR) ratios when fueling with diesel (D100) and diesel/PODEn mixture (P10). In addition, the regeneration behavior of the cDPF was studied by determining the breakeven temperatures (BETs) for both tested fuels. The results showed that the cDPF had lower removal efficiencies in nucleation mode particles but higher filtration efficiencies in accumulation mode particles. In addition, the overall filtration efficiency for P10 particles was higher than that for D100 particles. Positioning the upstream cDPF, increasing the EGR ratio slightly decreased the number concentration of nucleation mode particles but greatly increased that of accumulation mode particles. However, increasing the EGR ratio decreased the removal efficiency of nanoparticles, and this effect was more apparent for the P10 case. Under the same period of soot loading, the pressure drop of P10 fuel was significantly lower than that of diesel fuel. In addition, a significantly lower BET was observed for the P10 fuel, in comparison with D100 fuel. In conclusion, adopting cDPF is beneficial for fueling with P10 in terms of the overall filtration efficiency in the particulate number and the lower input energy requirement for active regeneration. However, with the addition of EGR, the lower filtration efficiencies of nanoparticles should be concerned, especially fueling with diesel/PODEn mixture.

1. Introduction

Diesel engines are a major source of nitrogen oxides (NOx) and particulate matter (PM) emissions due to the nature of mixing-controlled combustion. As high engine emissions are connected to human health, increasingly stringent regulations are proposed [1,2]. To comply with the current regulations on PM emissions, fuel modification [3,4], engine parameter optimization [5], alternative combustion concepts [6,7], and advanced engine aftertreatments [8] are the main approaches. It is commonly accepted that mixing with oxygenated fuels like alcohols, ethers, and esters can effectively decrease PM emissions [9,10,11,12]. From the perspective of combustion chemistry, less unsaturated hydrocarbons, particularly aromatics, of oxygenated mixture forms fewer soot precursors [13]. In addition, oxygenates increase the concentrations of CO and OH radical in the combustion process, which improves the oxidation of the soot precursors. As regards particle diesel engines, the soot reduction mechanism of oxygenated fuels with various oxygen-containing functional groups differs due to their different influences on fuel evaporation, air entrainment, and the combustion reaction pathway.
Among the oxygenated fuel candidates, polyoxymethylene dimethyl ethers (PODEn) may be one of the promising additives for diesel fuel in terms of PM reductions. Liu et al. [14] figured out that the specific soot emission for P20 (80 vol% diesel and 20 vol% PODEn) was 0.03 g/kW·h at an indicated mean effective pressure (IMEP) of 8 bar, while that for diesel fuel was 1.39 g/kW·h). Another work [15] showed that under the speed of 2400 rpm and a full load condition, the smoke emissions of P10 (90 vol% diesel and 10 vol% PODEn), P20, and P30 (70 vol% diesel and 30 vol% PODEn) decreased by 29.7%, 67.8%, and 82.4%, respectively, in comparison with diesel fuel. The consistent trends that PODEn addition effectively reduced soot and PM emissions can be widely seen in [16,17,18]. In addition, adding PODEn also significantly decreased the total particulate number concentrations (PNCs) as expected. Reported by Zhao et al. [19], under a speed of 1900 rpm and a brake mean effective pressure (BMEP) of 0.41 MPa, the PNCs for diesel, P10, P20, and P30 were 3.027 × 106, 1.623 × 106, 1.257 × 106, and 1.068 × 106 #/cm3, respectively. These trends can be attributed to two aspects. One points to the molecular structure as PODEn not only contains oxygen content but also has no C-C bond. This can suppress the formation of soot precursors. As regards diesel engines, the lower viscosity and distillation temperature of PODEn improved the atomization quality during the mixture preparation phase [20]. However, it is worth noting that the addition of PODEn may increase the number of nucleation mode particles [15,21].
Fueling with diesel/PODEn blended fuels, adjustment of the injection parameters was also performed to optimize the engine-out emissions, especially for PM reduction. At a fixed speed of 1600 rpm and the full load condition, Wang et al. [22] found that increasing the injection pressure from 80 to 100 MPa decreased the number concentrations of accumulation mode particles but increased those of nucleation mode particles, which resulted in a reduction of total PNC. However, Chen et al. [23] claimed that the variations in PNC with the increasing injection pressure may be related to engine loads. Specifically, an elevated injection pressure increased the total PNC at a low load but decreased PNC at a high load. In addition, the injection pressure had a negligible effect on PNC at a medium load. As regards injection timing, Wang et al. [22] found that retarded injection timing resulted in a slight increase in PNC at a full load. Whereas at a medium load, Chen et al. [23] stated that retarded injection timing reduced the PNC for diesel/PODEn blends. It can be seen from the discussions above that adjusting the injection parameters may not be an effective approach for the reduction of PM and PN emissions with the use of diesel/PODEn mixture. Alternatively, using a diesel particulate filter (DPF) may be a good choice.
In modern diesel engines, DPF is an indispensable exhaust aftertreatment to meet current or future regulations on PM emissions. Currently, the most commonly used DPF is wall-flow DPF, which is composed of a honeycomb structure monolith with small pores [24]. When the exhaust gas goes through the porous surface in the DPF, particulates are trapped in the channels. With the accumulation of the trapped particulates, the backpressure increases, which has a negative effect on the engine economy. To maintain a relatively lower backpressure, periodical regeneration is required for the DPF to burn off the trapped soot. Therefore, the DPF performance is evaluated by three parameters including the filtration efficiency, pressure drop, and regeneration [25]. Generally, diesel soot spontaneously burns at temperatures over 600 °C. To lower the temperature required for soot oxidation, catalyst-coated DPFs (i.e., catalytic DPFs) are widely used [26]. Catalytic soot oxidation in cDPF depends not only on the catalyst’s intrinsic activity but also on the quality of the soot–catalyst contact [27]. When fueling with diesel/PODEn mixture, both the particulate size and exhaust atmosphere differ, which further leads to changes in the DPF performance. As the previous studies showed the benefits of using PODEn as a diesel additive in terms of both PM reduction and efficiency improvement, studies on the application of PODEn combined with aftertreatments like DPF are required for further emission reduction.
In previous studies, the effect of fueling with biodiesel on DPF performance has attracted considerable attention. Guo et al. [28] found that at the beginning of the loading process, the filtration efficiency of the DPF for biodiesel particles was lower than that for diesel particles. With the loading of soot particles, the differences in filtration efficiency diminished. Rodríguez-Fernandez et al. [29] showed that biodiesel improved the regeneration process, which was consistent with the higher oxidation reactivity of biodiesel soot. The regeneration process of a DPF needs the combustion or oxidation of the trapped soot. During this process, the break-even temperature (BET), defined as the temperature at which soot accumulation is balanced by soot oxidation on the filter, needs to occur at sufficiently low temperatures [30,31]. In [30,31], the authors reported that the BET was lower for biodiesel than for diesel fuel, which indicated that the use of biodiesel was beneficial to the engines equipped with DPFs in terms of a lower regeneration temperature. In contrast, there is relatively less research on the DPF performance when fueling with diesel/PODEn mixture. Recently, Zhang et al. [32] studied the effect of PODEn addition on the performances of a diesel oxidation catalyst (DOC) and catalytic diesel particulate filter (cDPF) after-treatment system. The results showed that the pressure drop of the cDPF can be greatly reduced by fueling with diesel/PODEn mixture, and thus the active regeneration frequency can be effectively decreased.
However, to the best knowledge of the authors, little research on the impact of PODEn addition on the filtration efficiency of the cDPF has been conducted. From the perspective of the filtration mechanism, the filtration efficiency of the cDPF is greatly governed by parameters like the porosity and porous size distribution. However, the changes in fuel properties alter the primary particle size and other physical properties, and thus the filtration efficiency of the cDPF loaded with diesel/PODEn-derived particles needs to be characterized. In addition, the regeneration processes in the filter with diesel/PODEn mixture were rarely reported. Therefore, this work targeted these gaps by experimentally investigating the filtration efficiency and regeneration behavior in a cDPF with the use of diesel/PODEn mixture. Initially, the particle size distributions before and after cDPF were recorded for diesel fuel and diesel/PODEn mixture under various engine loads and exhaust gas recirculation (EGR) ratios. Thus, the size-dependent particulate number removal efficiency was obtained and then analyzed. Additionally, we presented a comparative study of the effect of PODEn addition on the BET. The obtained results in this work can provide new insights for the filtration and regeneration optimization of the cDPF with the use of the diesel/PODEn blend.

2. Results and Discussion

2.1. The Size-Dependent Particulate Number Removal Efficiency

Figure 1 shows the particulate number and size distributions for both fuels before and after the cDPF under various engine loads. The particulate number gradually increased with increasing engine load for both fuels before the cDPF. As the engine load increases, the air/fuel ratio decreases, and fuel-rich combustion favors soot formation and agglomeration. The particulate number concentrations of P10 were significantly lower than those of D100 for various engine loads. This trend was widely reported in previous studies [19,33]. The main reason for the reduction of PN may be the dilution and oxygen effects of PODEn addition. The dilution effect decreases the aromatics contents in the mixture, which are the precursors of soot formation. While the oxygen effect improves the local fuel-rich regions, leading to the inhibition of soot formation but the promotion of soot oxidation. In addition, thanks to the absence of a C-C bond, the soot-free nature of PODEn decreases the soot formation.
As expected, employing cDPF significantly reduced the particulate number concentrations for both fuels under various engine loads. In addition, the use of cDPF shifted the peak of the highest particulate concentrations towards a smaller size, indicating that it may provide a better filtration efficiency for particles with a large size. This can be confirmed in Figure 2, which showed the size-dependent particulate number removal efficiency for both fuels. In this work, only the filtration efficiency for particles larger than 23 nm was reported. Particulates sub-23 nm were so low that the measurement uncertainty of the SMPS was large. It should be noted that the cDPF used in this work was a clean filter, and its filtration efficiency of the particulate number was relatively low. It can be seen in Figure 3 that the cDPF had lower filtration efficiencies in nucleation mode particle number concentrations but higher filtration efficiencies in accumulation mode particle number concentrations. This trend was in agreement with the observations of Tan et al. [34]. The authors explained this trend from two aspects. Firstly, the particulate filter is predominantly a physical filtration mechanism and the particles with a larger size are more likely to be trapped within it [34,35]. In addition, though most of the nucleation mode particles were trapped, less soot was available for the small soluble organic fraction (SOF) particles to absorb on. This resulted in more independent SOFs, which existed as nucleation mode particles downstream of the cDPF [34]. Therefore, lower filtration efficiencies in nucleation mode particles were observed.
As regards the trend in the change of the filtration efficiency versus the particle size, an overall increase in the filtration efficiency with the particle diameter can be observed for D100 fuel. A similar observation was reported by Orihuela et al. [36], who explained that the interception mechanism dominates over the diffusion one for the measured ranges of soot particles. However, Guo et al. [28] obtained an opposite trend of an overall decreasing filtration efficiency with the particle diameter. The authors attributed this filtration phenomenon to the predominant role of diffusion in the deposition mechanism during deep bed filtration under the experimental condition. Actually, according to Apicella et al. [37], the filtration efficiency for the different dimensional ranges was also related to the engine operating conditions. For the P10 case, the filtration efficiency was first increased but then slightly decreased with the increasing particle diameter and the peaks of the filtration efficiency located around the particle diameter of 200 nm. By comparing Figure 2a,b, it can be seen that the overall filtration efficiency for P10 particles was higher than that for D100 particles. This trend may be attributed to the differences in the fractal dimensions of soot particulates produced by the various tested fuels [28]. As reported by Yang et al. [38], with the addition of PODEn, the soot agglomerates became looser, and accordingly, the fractal dimension was smaller. Under this condition in this work, it can be assumed that diesel/PODEn mixture-derived soot particles with lower fractal dimensions are easier to be intercepted.
It is commonly accepted that the use of oxygenated fuels combined with employing EGR can simultaneously reduce NOx and PM emissions, and thereby improve the NOx–soot trade-off relationship. Therefore, the effect of the EGR ratios on the filtration efficiency of cDPF with the use of P10 fuel was evaluated. Figure 3 shows the particulate number and size distributions for both fuels before and after the cDPF under various EGR ratios. For both test fuels, increasing the EGR ratio slightly decreased the number concentration of nucleation mode particles but greatly increased that of accumulation mode particles. In addition, higher EGR ratios shifted the peak of the highest particle concentrations towards a larger size. Similar observations can be seen in [39,40]. Increasing the EGR ratio lowers the oxygen concentration and results in more local anoxic zones in the combustion chamber, which favors soot formation. With the introduction of EGR, the mean in-cylinder temperature is reduced, leading to incomplete soot oxidation. Both factors increase the amount of soot in the exhaust, and consequently the opportunity for coagulation, accumulation, and condensation of volatile fractions on the particles [41]. In addition, when parts of particle nuclei are reintroduced into the combustion chamber through EGR, these particles can undergo coagulation in the cylinder and surface growth occurs both in the primary reaction zone and in the cooler parts of the combustion chamber [42,43]. This finally increases the concentration of particulates with a larger diameter and shifts the highest particle concentrations towards a larger size.
Figure 4 displays the size-dependent particulate number removal efficiency for both fuels under various EGR ratios. It can be observed that adding EGR had a negative effect on the removal efficiency of nanoparticles (sub-50 nm). Moreover, this effect was more apparent for the P10 case. Introducing EGR reduces the NO2 concentration but not to the same extent as the total NOx concentration reduction, thus resulting in a higher NO2/NOx ratio [44]. This may promote the soot–NO2 interaction in the presence of the catalyst in the cDPF. Consequently, less soot is available for the small SOF particles to absorb on. This results in more independent SOFs, which existed as nucleation mode particles downstream of the cDPF. So, the removal efficiencies of nanoparticles were relatively low. For the P10 case, particulates usually contain higher SOF contents [38]. Therefore, the negative effect of EGR addition on the removal efficiency of nanoparticles was more apparent for P10-derived particles.

2.2. Regeneration Behavior of the cDPF

Figure 5 shows the engine torque, the cDPF inlet temperature, and the cDPF differential pressure versus the test time for both fuels during the BET procedure. As shown in Figure 5, when the engine was operating at the BMEP of 0.14 MPa, the clean filter was accompanied by a low pressure drop and exhaust temperature. Under this condition, increases in the pressure drop for both fuels were observed as the soot oxidation rate was low and the filter accumulated soot particulates. When the BMEP transited from 0.14 to 0.42 MPa, the pressure drop rapidly increased for both fuels. This is partly because of the increasing volumetric flow rate and thus the higher exhaust flow velocity. In addition, under these circumstances, the filtering regime was initially dominated by the rapid clogging of the pore distribution, which is called an intrinsic filtering regime [29]. Once such a regime was terminated, the pressure drops maintained a slight growth for both fuels as time went on, when operating at the BMEP of 0.42 MPa. This indicated further accumulation of PM. The increase of BMEP to 0.70 MPa exhibited a further increase in the exhaust temperature, achieving approximately 400 °C for both fuels. At this temperature, the soot oxidation rate increased, and it exceeded the soot accumulation rate. As the operating time went on, the pressure drop displayed a decreasing trend. When the BMEP further increased to 0.92 MPa, the cDPF inlet temperature reached over 450 °C for both fuels. Under these circumstances, the soot oxidation rates of both fuels were significantly higher than the soot accumulation rates, which led to great reductions in the pressure drop.
In addition to the similarity discussed above, some differences exist for both fuels during the BET procedure. Operating at the BMEP of 0.42 MPa (i.e., the period between 1200 and 2400 s), the pressure drop for the P10 case was 0.1 kPa while that for the D100 case was 0.8 kPa. This can also be confirmed by the results of the slope of the pressure drop versus temperature, as shown in Figure 6. The BET in this work was determined by analyzing the slope in the variation of the pressure drop with respect to the temperature. If the value of the slope of the pressure drop is positive, it is deemed as PM accumulation of cDPF. Instead, if the value of the slope of the pressure drop is negative, it can be assumed that the soot oxidation rate is higher than the soot accumulation rate. Thus, the temperature at which the slope of the pressure drop changes from positive to negative is assumed as the BET.
As seen in Figure 6, a significantly lower BET was observed for the P10 fuel, in comparison with D100 fuel. The main reason for the BET trend for both fuels is the different oxidation reactivity of the collected soot particulates [1]. As reported in [38], determined by the thermogravimetric analyzer, soot particulates generated from P10 exhibited a higher oxidation reactivity than that from D100. The lower reactivity of P10 soot was further related to the more disordered nanostructure. In addition to soot reactivity, changes in the exhaust gas composition and the trapped particulates may be partly attributed to the BET trend. As the reactivity of NO2 towards soot is much higher than that of O2 at low temperatures ranging from 150–350 °C [45], the higher NOx emissions for P10 fuel (shown in our previous work [46]) may enhance the soot oxidation. Furthermore, the lower particulate emissions for P10 fuel (indicated by the lower PN concentration in Figure 2 and the lower pressure drop in Figure 5) promote its BET being reached during the loading process [29].
From the discussions above, for the same period of soot loading, a significantly lower pressure drop for the P10 case can be obtained. This indicates that for engines equipped with cDPF, blending PODEn with diesel fuel can reduce the engine pumping work and thus improve the fuel economy, in terms of the reduction in the backpressure. Combined with the lower PM and PN emissions of P10 fuel, the active regeneration frequency can be effectively reduced. In addition, the lower BET of P10 fuel implies that lower input energy is required for active regeneration.

3. Experimental Methods

3.1. Experimental Setup and Fuels

Experiments were conducted on a four-cylinder common rail diesel engine (Model WP4G154E330), with the main specifications listed in Table 1. An eddy-current dynamometer (Model CW160B) coupled with a control system (Model FST3) was used to measure the engine speed and load. A commercial catalyzed DPF (cDPF) was installed in the exhaust pipeline. The main specifications of the cDPF are presented in Table 2. An aerodynamic particle sizer spectrometer (Model TSI SMPS-3936) was used to record the particle number and size distribution across the cDPF. The inlet temperature of the cDPF was monitored by a K-type thermocouple. The pressure drop of the cDPF was measured by two pressure sensors. Figure 7 plots the schematic of the experimental setup.
In this work, commercial 0# diesel fuel, noted as D100, was used as the baseline. The PODEn was purchased from Shandong Shanghekai Chemical Co., Ltd., China. The PODEn was mainly composed of PODE2, PODE3, PODE4, and other components with the proportions of 12%, 46%, 34%, and 8% by mass, respectively. The PODE was blended with diesel at 10% by volume, which was noted as P10. The physical and chemical properties of both fuels can be seen in our previous studies [19,47].

3.2. Experimental Procedure

To evaluate the filtration efficiency of the cDPF, the particulate number concentration and size distribution were measured upstream and downstream the filter at each operating condition. The filtration efficiency of the cDPF is determined as the ratio between PN removed by the filter and PN entering the filter. The engine was run at a speed of 2000 rpm and loads of 0.14, 0.42, 0.70, and 0.92 MPa brake mean effective pressure (BMEP). Each operating point was run for one minute after stable operation to measure the PN concentrations. Then, the existing PM in cDPF was removed by running at 0.92 MPa BMEP for one hour (the temperature of pre-cDPF was approximately 460 °C for the diesel case). Subsequently, the engine was fixed at a speed of 1600 rpm and a BMEP of 0.56 MPa, varying the EGR rates from 0% to 12% at a step of 4%. The EGR ratio was calculated as Equation (1):
EGR = [ CO 2 ] a m b i e n t − [ CO 2 ] i n t a k e [ CO 2 ] a m b i e n t − [ CO 2 ] e x h a u s t × 100 %
where [CO2]ambient, [CO2]intake, and [CO2]exhaust are the CO2 concentrations of the ambient environment, the intake manifold (after the EGR valve), and the exhaust manifold, respectively. Under each EGR ratio condition, the engine was run for one minute after stable operation to record the PN size distribution. For each type of test fuel, the above procedures were repeated. During the experiments, the injection strategies including the fuel injection timing and pressure were controlled by the original electronic control unit.
The BET test was conducted by the following experimental procedure. Firstly, the engine was run at a speed of 2000 rpm and a load of 0.92 MPa BMEP for one hour to clean the particulate accumulated in the filter. Then, the engine was operated at the condition of n = 1600 rpm, BMEP = 0.42 MPa, and EGR% = 12% for 20 min (the exhaust temperature was below 250 °C for the diesel case), for the purpose of soot loading. Finally, the engine was run at 2000 rpm, from low to high load, to determine the BET. The experimental procedures are described in Table 3. This sequence was repeated for both test fuels.

4. Conclusions

This work investigated the size-dependent filtration efficiency and regeneration behavior of a cDPF when fueling with diesel fuel and diesel/PODEn mixture. As expected, employing cDPF is an effective approach to reducing the particulate numbers for both fuels. Regarding the size-dependent particulate number removal efficiency, the cDPF had lower removal efficiencies in nucleation mode particles but higher filtration efficiencies in accumulation mode particles. This is primarily because the particles with larger sizes are more likely to be trapped within the cDPF under the physical filtration mechanism. In addition, as most of the nanoparticles were trapped, less soot was available for the small SOF particles to absorb on. This resulted in more independent SOFs, which existed as nucleation mode particles downstream of the cDPF. In addition, the overall filtration efficiency for P10 particles was higher than that for D100 particles. This trend may be attributed to the differences in the fractal dimensions of soot particulates. Positioning the upstream cDPF, increasing the EGR ratio slightly decreased the number concentration of nucleation mode particles but greatly increased that of accumulation mode particles. However, increasing the EGR ratio decreased the removal efficiency of nanoparticles, and this effect was more apparent for the P10 case. Under the same period of soot loading, the pressure drop of P10 fuel was significantly lower than that of diesel fuel. In addition, a significantly lower BET was observed for the P10 fuel, in comparison with D100 fuel. The main reason for the BET trend for both fuels is the different oxidation reactivity of the collected soot particulates.
From the discussion above, adopting cDPF is beneficial for fueling with P10 in terms of the overall filtration efficiency in the particulate number and the lower input energy requirement for active regeneration. However, with the addition of EGR, the lower filtration efficiencies of nanoparticles should be concerned, especially fueling with diesel/PODEn mixture. Further work is still needed to compare the filtration efficiency and regeneration behavior of the DPF and cDPF in the presence of diesel oxidation catalyst when fueling with diesel/PODEn mixture. Additionally, the effect of PODEn addition on catalyst performance needs to be evaluated in the future.

Author Contributions

Conceptualization, H.C. and X.W.; methodology, X.S.; software, F.S.; investigation, P.Z.; resources, H.C.; data curation, P.Z.; writing—original draft preparation, X.W.; writing—review and editing, X.W., L.G. and H.W.; project administration, H.C.; funding acquisition, H.C. and L.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Innovation Capability Support Program of Shaanxi (Program No. 2021TD-28), the Youth Innovation Team of Shaanxi Universities, the Key Research and Development Program of Shaanxi Province, China (2021GY-291, 2019ZDLGY15-07), the National Engineering Laboratory for Mobile Source Emission Control Technology (NELMS2017B02), and the Special Fund for Basic Scientific Research of Central Colleges, Chang’an University.

Data Availability Statement

Data is available upon request to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

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Catalysts 11 01425 g001 550
Figure 1. Particulate number and size distributions under various engine loads: (a) D100 fuel, before cDPF; (b) D100 fuel, after cDPF; (c) P10 fuel, before cDPF; and (d) P10 fuel, after cDPF.
Figure 1. Particulate number and size distributions under various engine loads: (a) D100 fuel, before cDPF; (b) D100 fuel, after cDPF; (c) P10 fuel, before cDPF; and (d) P10 fuel, after cDPF.
Catalysts 11 01425 g001
Catalysts 11 01425 g002 550
Figure 2. Size-dependent particulate number removal efficiency under various engine loads for (a) D100 and (b) P10.
Figure 2. Size-dependent particulate number removal efficiency under various engine loads for (a) D100 and (b) P10.
Catalysts 11 01425 g002
Catalysts 11 01425 g003 550
Figure 3. Particulate number and size distributions under various EGR rates: (a) D100 fuel, before cDPF; (b) D100 fuel, after cDPF; (c) P10 fuel, before cDPF; and (d) P10 fuel, after cDPF.
Figure 3. Particulate number and size distributions under various EGR rates: (a) D100 fuel, before cDPF; (b) D100 fuel, after cDPF; (c) P10 fuel, before cDPF; and (d) P10 fuel, after cDPF.
Catalysts 11 01425 g003
Catalysts 11 01425 g004 550
Figure 4. Size-dependent particulate number removal efficiency under various engine loads for (a) D100 and (b) P10.
Figure 4. Size-dependent particulate number removal efficiency under various engine loads for (a) D100 and (b) P10.
Catalysts 11 01425 g004
Catalysts 11 01425 g005 550
Figure 5. Engine torque, cDPF inlet temperature, and ΔP during the BET procedure.
Figure 5. Engine torque, cDPF inlet temperature, and ΔP during the BET procedure.
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Catalysts 11 01425 g006 550
Figure 6. The slope of the pressure drop versus temperature.
Figure 6. The slope of the pressure drop versus temperature.
Catalysts 11 01425 g006
Catalysts 11 01425 g007 550
Figure 7. The schematic of the experimental setup.
Figure 7. The schematic of the experimental setup.
Catalysts 11 01425 g007
Table
Table 1. The main specifications of the diesel engine.
Table 1. The main specifications of the diesel engine.
Engine TypeIn-Line, Four-Cylinder, Turbocharged, Water-Cooling
Bore × stroke [mm]105 × 130
Displacement [L]4.5
Compression ratio18:1
Combustion chamberω type
Max. torque [N·m @ rpm]520 @ 1600–1800
Max. power [kW @ rpm]113 @ 2300
Table
Table 2. The main specifications of the cDPF.
Table 2. The main specifications of the cDPF.
ParameterValue
Substrate materialSiC
Diameter [mm]190.5
Length [mm]177.8
Pore density [cpsi]300
Wall thickness0.23
Catalysts and ratiosPt:Pd = 12:1
Catalyst mass [g/L]0.106
Table
Table 3. Experimental procedure of BET determination.
Table 3. Experimental procedure of BET determination.
StepEngine Speed [rpm]BMEP [MPa]EGR Ratio [%]Operating Duration [min]
120000.92060
216000.421220
320000.14020
420000.42020
520000.70020
620000.92020
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MDPI and ACS Style

Chen, H.; Su, X.; Wang, X.; Sun, F.; Zhang, P.; Geng, L.; Wang, H. Filtration Efficiency and Regeneration Behavior in a Catalytic Diesel Particulate Filter with the Use of Diesel/Polyoxymethylene Dimethyl Ether Mixture. Catalysts 2021, 11, 1425. https://doi.org/10.3390/catal11121425

AMA Style

Chen H, Su X, Wang X, Sun F, Zhang P, Geng L, Wang H. Filtration Efficiency and Regeneration Behavior in a Catalytic Diesel Particulate Filter with the Use of Diesel/Polyoxymethylene Dimethyl Ether Mixture. Catalysts. 2021; 11(12):1425. https://doi.org/10.3390/catal11121425

Chicago/Turabian Style

Chen, Hao, Xin Su, Xiaochen Wang, Fengyu Sun, Peng Zhang, Liming Geng, and Haifeng Wang. 2021. "Filtration Efficiency and Regeneration Behavior in a Catalytic Diesel Particulate Filter with the Use of Diesel/Polyoxymethylene Dimethyl Ether Mixture" Catalysts 11, no. 12: 1425. https://doi.org/10.3390/catal11121425

APA Style

Chen, H., Su, X., Wang, X., Sun, F., Zhang, P., Geng, L., & Wang, H. (2021). Filtration Efficiency and Regeneration Behavior in a Catalytic Diesel Particulate Filter with the Use of Diesel/Polyoxymethylene Dimethyl Ether Mixture. Catalysts, 11(12), 1425. https://doi.org/10.3390/catal11121425

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