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Combustion Noise AnalysisDiesel and Ethanol Engines ^ ^
Grover ZuritaLuled University of Technology
LUIJtAl UNIVERSITY^
OP TECHNOLOGYL
KFB-Meddelande 1997:18
TITEL/TITLECombustion noise analysis. Diesel andethanol enginesFORFATTARE/AUTHORGrover Zuiita, Lulea University ofTechnologySERIE/SERIESKFB-Meddelande 1997:18
ISBNISSN 1401-1271PUBLICERINGSDATUM/DATE PUBLISHEDAugust 1997UTGIVARE/PUBLISHERKFB — Kommunikationsforsknings-beredningen, StockholmKFBs DNR 1992-157
ABSTRACT (Aim, Method, Results)The engine manufactures have to meet more and more stringent regulations on both noise and exhaust emissions in the future requiring extensive optimization of all parameters of the engine. Soft modeling with statistically designed experiment (SDE) and Multivariate Analysis (MVA) can be an aid in this work. The MVA can investigate the relations between all the variables in a single context, and it works by extracting information from data with many variables using them all simultaneously.
The main objective of this work are to investigate how the change of fuel from diesel to ethanol influences the noise emissions, and to evaluate the applicability of multivariate evaluation to predict the noise level outside the engine as well as levels of exhaust emissions. In this work are included Multivariate Analysis Methods (MVA) and Sound Pressure Measurements.
Summarizing the conclusions:The work has demonstrated the importance and applicability of multivariate methods for modeling and minimization. By using multivariate evaluation it was possible to generate good prediction models for noise and some exhaust components.
-The methods can verify that the noise and HC are mostly influenced by speed while NOx emissions depends mostly on load. CO depends also to a large extent on load, but also shows a large interaction effect between load and speed.- Interpretation of the loading plot shows that the sound pressure levels are positively correlated to speed, exhaust gas flow and N02.- The NOx and NO emissions have a strong positive correlation with load.
Combustion noise is determined principally by the frequency content of the cylinder pressure above a few hundred Hertz. An obvious way of creating energy in this upper range of frequency is through a rapid rate of pressure rise in the cylinder. Reducing the rate of the pressure rise is a standard way to reduce the combustion noise.The following Table shows the results in relative values. To present the results of the combustion noise analysis the engine was running at 1200 rpm and 10 % load. The influences of the fuel quality on the combustion process are more sensitive at high speeds and low loads.Eurodiesel shows the lowest rate of pressure rise and it gives lowest combustion noise emissions.
Fuels Rate of Pressure Rise *
dp/d°©Ethanol + 9% Beraid 1.29 bar/°CAEthanol + 7 % Beraid 1.72 bar/°CA
MK1 0.135 bar/°CAEurodiesel 0.12 bar/°CA
MK1+ 15 %Ethanol 0.13 bar/°CAEurodisel + 15% Ethanol 0.18 bar/°CA
Pressure [bar] Cylinder Pressure
Crank shaft Angle °CA
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^KFBKOMMVN1KATIONSFOUSKNINCSiEREDNINGEN
Combustion Noise AnalysisDiesel and Ethanol Engines
Grover ZuritaLulea University of Technology
ACKNOWLEDGMENT
I would like to acknowledge the support from Scania CV, and the financial support from the Swedish Transport and Communications Research Board (KFB)
TABLE OF CONTENTS
Page
1. INTRODUCTION 1
2. THE ENGINE NOISE CHARACTERISTICS 22.1 The combustion noise 22.2 Mechanical noise 32.3 Effect of various parameters on combustion noise 3
3. EXPERIMENTAL SET-UP AND PROCEDURE 4
4. MULTIVARIATE ANALYSIS (MVA) 54.1 Principal component analysis (PCA) 54.2 Partial least squares projections to latent structures (PLS) 64.3 Results and discussions 64.4 Validation of the predictions models 114.5 Discussions 124.6 Conclusions 12
5. SOUND PRESSURE MEASUREMNTS 12
6. REFERENCES 14
7. APPENDIX 16
1
1. INTRODUCTION
The engine manufactures have to meet more and more stringent regulations on both noise and exhaust emissions in the future requiring extensive optimization of all parameters of the engine. Soft modeling with statistically designed experiment (SDE) and Multivariate Analysis (MVA) can be an aid in this work.The direct relationship between the combustion pulse, engine data, noise as well as and exhaust emission data can be accomplished with Principal Component Analysis (PCA) and Partial Least Square (PLS) regression. PLS has also the advantage that it can help in evaluation of inter-correlated predictor variables.Sound Pressure measurements and combustion pulse analysis were also performed in order to compare the noise radiation from the performance of an ethanol and diesel engine fuel and ignition improver (Beraid).
Table 1 shows the engine data and fuels combinations used in the experiments.
Ethanol Engine Diesel Engine FuelEngine Type DSE11E DSC 11-24 Ethanol + 9% BeraidBore 127 mm 127 mm Ethanol + 7 % BeraidStroke 145 mm 145 mm MK1
Compression Ratio 24:1 17:1 EurodieselPower 191 kW 180kW MK1+ 15 % Ethanol
Number of Cylinder 6 6 Eurodisel + 15% Ethanol
2. THE ENGINE NOISE CHARACTERISTICS
The noise generating process due to internal combustion engines is well described in various publications [1,2,3], Nevertheless, some fundamental relationships within this process will he briefly covered below. The noise generation is mainly related to combustion and mechanical impacts.
2.1. The Combustion noise
Noise emission from combustion engines is a product of excitation from the combustion pulse and the structural response of the engine. Noise is a directly related consequence of vibrations in the engine structure that are caused by a rapidly changing pressure in the cylinders, known as “Combustion Noise”. Figure l(a, b) shows a typical cylinder pressure trace in time and frequency domain.
There are several stages in this combustion process, Stone, R. [2] gave a detailed explanation of this process as follows:
2
Cylinder Pre»*urr Spect.ru*
Fig. l(a, b): The cylinder pressure trace (a) and cylinder pressure spectrum (b) [2].
(i) Ignition delay, AB. The fuel is injected into hot air in the cylinder chamber. During this period the fuel is broken up into droplets that are being vaporised, and mixed with air. Chemical reactions will be starting. This stage is the most important, as it is the seat of the so called “knock”.
(i) Rapid or uncontrolled combustion, BC. A very rapid rise in pressure caused by ignition of the fuel/air mixture that was prepared during the
ignitiondelay period.
(iii) Controlled combustion, CD. Combustion occurs at a rate determined by the preparation of fresh air/fuel mixture".
(iv) Final combustion, D. As with controlled combustion the rate of combustion is governed by diffusion until all the fuel or air is utilized.
The ignition delay is considered to be one of the most important parameters in the combustion process since it influences the rate of pressure rise and the peak cylinder pressure respectively. The ignition occurs only when a sufficient quantity of fuel has mixed with the air charge and the temperature and the pressure have exceeded critical values for a specific fuel [2]. The ignition delay period will be shorter if the temperature and pressure of the air charge increases. The fuel quality, injection timing, speed and load also have influence on the ignition delay. With shorter ignition delay there will be lower peak pressure and lower rising rate .
The rapid pressure rise in reciprocating diesel engines is recognized as an audible impulse noise, which is know as "knock". The knock is caused by the spontaneous combustion of a significant volume of fuel/air mixture and produce almost an instantaneous pressure rise locally in the combustion chamber.
When the engine is already full developed, without to exchange neither stiffness or mass in the engine, there is only one possible to reduce the engine noise, which can be obtained through the reduction of the rapidly rate of the pressure rise.
Figure 1 b) shows the cylinder pressure spectrum. The major part of the energy occurs at low frequencies below 100 Hertz, however little of this energy escapes as noise, through the engine structure. Apparently because the engine structure has a
3
low vibration response and an inefficient radiation of sound in this low frequency range. The low frequency part of the combustion noise, mostly propagates and radiates through the exhaust pipes and the muffler. Structurally radiated combustion noise, is determined principally by the frequency content of the cylinder pressure above a few hundred Hertz. An obvious way of reducing the energy in this upper range of frequency is to reduce the rate of pressure rise in the cylinder. Reducing the rate of the pressure rise is thus a standard way to reduce the combustion noise. Figure 1 b) also shows some high frequency peaks, which are assumed to be the combustion chamber resonances. The resonance frequencies depend on the dimensions of the combustion chamber and the wave propagation speed.
2.2. Mechanical Noise
The pressure fluctuations generated in the cylinders by the periodical combustion process are transmitted to the crank drive. From there, the pressure fluctuations are introduced on one hand through the crankshaft bearings into the engine block, where they cause an airborne noise radiation from the engine structure surfaces. On the other hand the pressure fluctuations radiate airborne noise directly from the free end of the crankshaft [2]. The mechanical noises are generated by the clearances in the force transmitting crank drive components, e.g. piston slap, gear transmission vibrations and shocks in the various bearings. Figure 2 shows the piston slap effects.
Fig. 2 : Principle of piston slap occurrence (Scania)
2.3. Effect of various parameters on combustion noise
Effect of injection timing- One important factor for cylinder pressure development is the injection advance. This means the possibility of bringing the moment of injection later in time in relation to the upward moving position of the piston. With increased injection advance the ignition delay increases [1], which will cause the initial pressure rise to became greater and the peak pressure higher.
Effect of the fuel quality- The cetane number of the fuel has a very pronounced effect on the cylinder pressure development and thus the ignition delay [3], Low cetane fuels have longer ignition delays, which leads to a fast and more simultaneous
4
combustion of the fuel, which in turn will lead to a stronger excitation of combustion noise [1].
Effect of load- The main influence of load on noise is that when the load increases there is an increase in mistiming of the injection, which leads to an increase in noise [1], At higher load, there is also a larger amount of fuel that is being burnt which will also lead to an increase in peak cylinder pressure.
Effect of speed- The engine noise increases rapidly with speed because of the rapidly sloping frequency spectra which shifted upwards in frequency as the cycled fundamental frequency increased, giving rise to higher force inputs to the structure in the high frequency range. The cylinder spectra at different speeds increases in frequency in direct proportion to speed.
Effect of turbo charge- The main objective of introducing more air into the cylinder by supercharging is to increase the temperature of the air charge and thus the temperature of the injected air/fuel mixture, by the high pressure. The ignition delay, and thus the combustion noise [1], will then be reduced. The turbo-charging is an effective way of reducing noise at full load. Inter-coolers are, however, normally used in combination with turbo-chargers in order to reduce nitrogen oxides (NOx)emissions. The cooler reduces the air charge temperature and thus increases the combustion noise level.
Effect of the compression ratio- With increasing pressure, the temperature also increases. This leads to a reduction of the ignition delay and a reduction of the high frequency content of the combustion noise. The low frequency content will, however, be increased by the increased overall pressure.
3 EXPERIMENTAL SET-UP AND PROCEDURE
Measurements data acquisition of both cylinder pressure and external noise level was made with a HP 715/75 computer with a maximum sampling frequency of 132 kHz. For the cylinder pressure measurements, an optical sensor was used to give a trigger signal to locate the position of the piston in the cylinder. The cylinder pressure was measured by an AVL QC31C-E transducer. To carry out the cylinder pressure measurements the CADA-X (LMS), Throughput Acquisition and Processing data part was used. The fundamental characteristic of throughput processing is that raw unprocessed time data is stored in a intermediate file and that post processing is carried out afterwards. This means that expansive continues sets of data can be acquired at very fast rates, which is necessary in this type of measurements.
The different components measured in the raw exhaust were total hydrocarbons (HC), carbon monoxide (CO), carbon dioxide (CO2), NOx (nitrogen oxides) and nitrogen oxide (NO). Nitrogen dioxide (NO2) is calculated as the difference betweenNO* and NO. The raw exhaust was pumped through heated lines to the analysis equipment. A flame ionisation detector (FID) was used for HC analysis. CO and CQ? were measured with a
5
nondispersive infrared instrument, one for each compound. Chemiluminescence detection was used for NOx and NO.
Noise Emissions Exhaust Emissions
Quartz Pressure TransducerMicrophone
MicrophoneMicrophone
Optical SensorEngine Data
Load, Speed, Pressure Before Comp., Exhaust Temp, before Catalyst, Fuel flow, Power, Exhaust Emissions and Alpha
Multivariate Analysis Principal Component Analysis (PCA)Partial Least Square Analysis (PLS)
Exhaust Emission Data
Number of Combustion Pulse variables for each observation
Noise Level
LMS (CADA_X)
Combustion Pulse Data
SimcaP
Figure 3: Measurement set-up for noise and exhaust emissions
4. MULTIVARIATE ANALYSIS (MVA)
The MV A methods can be used to investigate the relationships between all variables by extracting information from data with many variables and treat them simultaneously. MV A does not deal with how to structure the problem, which variables to measure or how to collect data. MV A can be applied to any data set but for non designed data the found relationships are correlation rather then ’’cause effect” relationships.
4.1. Principal Component Analysis (PCA)
Every observation (row in the data matrix) is described by a number of variables (columns in the matrix). In geometrical terms, every observation can be represented as a point in a multidimensional space, where the axes are the variables. A principal component (PC) is a straight line through the observation points in the multivariable space. The direction of the line is calculated by minimising the sum of the squared distance to each observation, i. e., the least square method. The contributions of individual variables to the PC are the so called
6
the variable and the PC). Each observation is projected to the PC and the positions of the projected points make up a vector of observation scores. For each PC, a loading vector (p) and a scores vector (t) is obtained. A matrix of residuals (E) is calculated by subtracting tp’ from the original data matrix (X). Next PC is then extracted from E. This iterative extraction of new PCs continues until no more systematic variation remains in the residual matrix. The raw data has then be transformed into a loading matrix (P) and a scores matrix (T), which contain the systematic variable and object information of the data, respectively. Matrix P' is the transpose of matrix P.
X = IX + TP + E (1)
All PCs are orthogonal and every PC explains a maximum of the remaining matrix variance. The results of PCA can easily be graphically interpreted by plotting scores and loadings and relationships between observations and variables can be identified.
4.2. Partial Least Squares projections to latent structures (PLS)
In PLS the components are extracted from one X matrix (descriptor matrix) and from one Y matrix (response matrix). Components are extracted so as to obtain a maximum covariance between theX and Y matrices. As with PCA, the X-scores are orthogonal, and the loadings and scores may easily be graphically interpreted. Since components are extracted for both matrices, scores are for each PLS dimension projected to two separate vectors, t (X scores) and u (Y scores), forming two matrices of scores, T and U. The relationship between theX and Y matrices can be graphically presented by plotting these vectors. The important relationships can be summarised in equation (1) to (3).
Y= 1Y+ UC’ +F (2)
U=T+H (3)
X, T, P and E are defined above. U is the scores which summarises the Y- variables. C expresses the correlation between Y and T. H and F are matrices of residuals. A description of PLS regression methods can be found in the work by Hoskuldsson [5],
A description of PLS regression methods can be found in the work byHoskuldsson [14].
4.3. Results and discussions
PCA, engine data and exhaust emissions data: Figure 4 shows the relationship among observations which are spread in night groups (10/50/100 % Loads and 800/1200/2000 rpm). The first PC describes 46% of the variation of data, the second 20%), and the third 16% (totally 82%'). The spread is data is far less depending on the injection timing(Alpha) than speed and load. The first PC’s is dominated by speed and load.
7
SIMBLA1.M4 (PC). UnTitled, WorksetScores: tfll/tf21
200(1/ 50 % Load
1200/ l(X)%Load
2< X )l I rpm/ 10% Load
NH)/1(H) % Load
•12 *32000/ioo% Load
t[1]Fig. 4: Score (PCA) plot, shows the relationship among observations.
Engine data and Exhaust emissions data.
Figure 5 shows the relationships between the variables for engine and exhaust emissions. Interpretation of the loading plot shows that the sound pressure levels are positively correlated to speed, exhaust flow and NO,.The NO, and NO emissions have a strong positive correlation with load.
Loadings: pm/pT21NOxg/h
•COg/h •C02
P[2] . #HC g/h
•Press..
•Ert_Gas.
•Noise Level dB(A)
Fig. 5: PCA loading plot with loading vector 2(p2) Vs loading vector 1 (p,). model.
8
PLS, Sound Pressure Level: Fig. 6(A, B, C, D, E, F) shows the sound pressure level Vsspeed and load from each fuel combinations (See Table 1).
(A) Ethanol + 9 % BeraidSIM BL A1 plsljud(I -9)M 7 .d B (A), C om p 1
Load (Nm)
9
(C): MK1SIMBLAl plsl9-27M9.dB(A), Comp 1
200 400 600 800 1000Load (Nm)
SIMBLAl UnTitledM10.dB(A), Comp 1
(D): Eurodiesel
(E): MK1 + 15% EthanolSIMBLAl UnTitledM10.dB(A), Comp 1
(F): Eurodiesel +15 % EthanolSIMBLA1 ljud5563M12.dB(A), Comp 2
10
200 400 600 800 1000Load (Nm)
Fig. 6(A, B, C, D, E, F): sound pressure level Vs speed and load from each fuelcombinations (See even Table 1).
Figure 6 shows both coefficients and VIP(variable importance in projection), for the sound model from engine variables and exhaust emissions. The speed has the major importance for the prediction of the sound pressure. Interestingly does not load appear as such, but in this turbocharged engine does load also have an impact on the exhaust gas emissions.
Fig 7 shows No, Vs dB(A) and load.
SIMBLA1 plsavgsquareSpeed=2318.000 Ftess._Cerrp=38.643 6fhTarrp= 1.537 fuel fla/vlgfh=20079ftver=70.300 Exh_Gte_Rcw=684.813
Fig 7 : The NOx model. No,.Vs dB(A) and Load (Nm)
11
4.4. Validation of the prediction models
The models can he validated both internally and externally. The internal validation was performed by splitting the data in two data sets, a training set and a validation set. For external validation a new experimental data set was imported.The model used for validation was from the engine data and exhaust emissions, which proven to be good by both validation methods, and the difference between the observed and the predicted value was around 0.5-2.5 dB(A). See figure 8.
SIMBLA1.M1 (PLS). plsfliud), WorksetdB(A). Comp 3(Cum)
105-1-----------------------------------------------------------------------------------------------------------------------
100-
Observed dB(A)
95-
90-
~!--------- '--------- 1--------- '--------- 1--------- ----------90 95 100 105
Predicted dB(A)
*8 e2653 e56•M»2
56•62*12
•113*21,48 *5*30 ,59
•9 *7 *18•25
•27
Fig. 8 : The validation model for the sound pressure level model
Fig. 9 shows the validation results for Nitrogen Oxides (NOJ from the engine data and exhaust emissions data.
NOx g/h, Comp 3(Cum)100CH-
600-
200-
Fig 9: shows the predictions values for Nitrogen oxides (NOx)
12
4.5 Discussions
In order to increase the accuracy of the combustion pulse measurements. The combustion pulse should be measured related to the crankshaft degree, instead of to time domain.
The future research work will be included in the experiments the facilities to monitoring the engine performance on-line. The purposes of measuring the data on the process (online) its input and environment are to :- Find how the output is affected by the input variables to improve engine performance and minimize exhaust emissions, fuel consumption and noise emissions.- Achieve information allowing a better understanding of the process, relationships
between different parts of the process, varying injection timing, speed, load, etc.- Have information about the “state” of the engine running process, recognizing trends
peculiarities , all to keep the process under proper control.
4.6. Conclusions
It is possible to model both sound level as well the chemical exhaust emissions from both the pressure pulse data and the engine data. In general is the predictivity larger for the engine data then the pressure pulse data.
As could be expected the noise, NO,and HC are mostly influenced by speed while NOx emissions depends mostly on load (See Fig. 4).By multivariate evaluation it was possible to generate accurate prediction models for noise and some exhaust components from the group of engine data and exhaust emissions data. The work has demonstrated the importance and applicability of experimental design and multivariate methods for modeling and minimization
5.1 SOUND PRESSURE MEASUREMENTS
The experimental data set in Table 1 shows six fuels combinations and two engines The effect of the fuel quality- The cetane number of the fuel has a very pronounced effect on the cylinder pressure development affecting the ignition delay [4], Low cetane fuels have longer ignition delays which means that more fuel burn simultaneously, so they can rise to more the combustion noise [1], One important parameter is the fuel quality in the combustion process
The measurements were carried out over three sides of the engine at varying speed 700 to 2000 (rpm) and Max. load.
13
The sound pressure measurement results show that the highest noise emissions are obtained by the combination of Miljoklassl and 15 % Beraid.and Beraid 7%, see Fig.10
Left hand side of the engine
I
—•——Beraid 9%
•—■—— Beraid 7%MK1
---- X—— Eurodiesel
---- X-— MK1+ 15% Eth— — Eurodi+ 15% Eth
Sound Pressure Level - Left hand side
Speed (rpm)
Fig. 10 : Sound Pressure Level. Left hand side of the engine
The highest noise emissions are obtained by Beraid 7% and Beraid 9% in the front side and right side of the engine, see fig. 11 and 12.
Sound Pressure Level - Front side of the engine
Beraid 9% Beraid 7% MK1Eurodiesel MKl+Eth Eurodi+ Eth
Speed (rpm)
Fig. 11 : Sound Pressure Level. Front side of the engine
14
Sound Pressure Level - Right hand side
—* — Beraid 9%— Beraid 7%
MK1
--- X-— Eurodiesel
-— MKl+Eth— Eurodi+ Eth
§ § 8C4 C<1 -sf
- speed (rpm)1 I I
Fig. 12 : Sound Pressure Level. Riht hand side of the engine
REFERENCES
[1] Russel, M.,F.: Combustion noise in automotive diesel engines . Chapter 7, Design and applications in diesel engineering , 1984.
[2] Stone, R.: "Introduction to internal combustion engines". Published by Society of Automotive Engineers Drive (1992).
[3] H.,S., W., N: Design and Applications in Diesel Engineering.(Ellis Horwood 1984)
[4] Russel, M.,F.: Effect of fuel on diesel combustion noise. Inter-Noise 83. Lucas CAV-Limited.
[5] S. Haddad and N. WatsomDesign and Applications in Diesel Engineering (Ellis Horwood, 1984)
[6] G. E. P. Box, Statistics for Experimenters. (John Wiley&Sons 1978)
[7] “Ethanol Fuels with Ignition Improver for Turbocharged Diesel Engines," S Fahlanderand N. Walde: Fourth International Symposium on Alcohol Fuels Technology, Sao Paolo, Brazil, October 5-8, (1980).
[8] N. R. Draper, Applied Regression Analysis. (John Wiley&Sons 1981)
[9] “Effect of fuel on diesel combustion noise" M.F. Russel Inter-Noise, 1111- 1114 (1983)
[10] H.O. Simonsen and J.Chomiak:“Ignition an Combustion Properties of Alcohol Fuelswith Ignition Improvers in Diesel Engines. Swedish Transport and Communication Research Board Report 1992. Dnr 92-69-742
[11] W. Zong and G. Zongying ^‘Experimental Study of Using EGR to Raise the Thermal Ratio of Methanol to Diesel Fuel in Diesel Engine", SAE 931950 (1993).
[12] A. D. Pilley et al, Proc 27th ISATA Conf, Aachen 1994
[13] J. Van, SAE 930600, 1993
[14] Hoskuldsson, A., ”PLS Regression Methods”,228, 1988
15
Chemometrics, 2, 211-
16
APPENDIXnr Speed (rpm) load (%) Fuel
1 1207 117.1 Eth.+9%Beraid2 2012 457.1 Eth.+9%Beraid3 1201 1076 Eth.+9%Beraid4 2011 824.8 Eth.+9%Beraid5 1205 596.1 Eth.+9%Beraid6 800.6 1034 Eth.+9%Beraid7 803.6 574.1 Eth.+9%Beraid8 2014 90.58 Eth.+9%Beraid9 801.9 112.7 Eth.+9%Beraid10 1204 118.3 Eth.+7%Beraid11 2011 458 Eth.+7%Beraid12 1185 1075 Eth.+7%Beraid13 2010 825.6 Eth.+7%Beraid14 1203 597.1 Eth.+7%Beraid15 801.3 1036 Eth.+7%Beraid16 800.4 575.2 Eth.+7%Beraid17 2002 92.18 Eth.+7%Beraid18 801 113.4 Eth.+7%Beraid19 1209 113.8 MK120 2016 455.4 MK121 1210 1072 MK122 2011 658.2 MK123 1209 592.5 MK124 808 1033 MK125 807.9 571.1 MK126 2016 88.09 MK127 806.5 110.1 MK128 1210 116 MK129 2018 455.3 Eurodiesel30 1206 1072 Eurodiesel31 2014 681.2 Eurodiesel32 1211 593.4 Eurodiesel33 809.5 1032 Eurodiesel34 808.2 572.3 Eurodiesel35 2016 88.89 Eurodiesel36 806.5 110 Eurodiesel37 1211 113.8 MK1 +15% Eth.38 1816 444.7 MK1 +15% Eth.39 1210 1043 MK1 +15% Eth.40 1816 801.3 MK1 +15% Eth.41 1210 580.1 MK1 +15% Eth.42 807.4 1013 MK1 +15%. Eth.43 808.3 567.9 MK1 +15% Eth.44 1817 85.61 MK1 +15%, Eth.45 807.9 111.1 MK1 +15%, Eth.46 1212 111.8 Eurodiesel +Eth.47 1816 441.8 Eurodiesel +Eth.48 1209 1034 Eurodisel +Eth.49 1816 795.5 Eurodiesel +Eth.50 1209 572.9 Eurodiesel +Eth.51 808.4 1002 Eurodiesel +Eth.52 808.2 555.4 Eurodiesel +Eth.53 1817 86.05 Eurodiesel +Eth.54 806.9 109.1 Eurodiesel +Eth.
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