Correlation between Pegasor Particle Sensor and Particle Number Counter Application of Pegasor Particle Sensor in Heavy Duty Exhaust

Transcription

1 Correlation between Pegasor Particle Sensor and Particle Number Counter Application of Pegasor Particle Sensor in Heavy Duty Exhaust Dr. Harald Beck, Dr. Dieter Rothe, Christian Tyroller MAN Truck & Bus AG, Nuremberg, Germany The implementation of a particle number limit by Euro VI has lead to the development of an appropriate measurement method. This method affords the sampling from diluted engine exhaust and the usage of a complex sample treatment before measurement in a particle number counter. The commercial setups are cost intensive and more over bulky. For engine development another measurement system should be found. In the following studies a new in line sensor, developed by Pegasor was used in comparison with an AVL APC Advanced and an AVL Micro Soot Sensor.The studies have been performed in order to find similarities between the sensor signals. The tests were carried out with a heavy duty diesel EURO IV engine equipped with a continuously regenerating particle trap. AVL APC 489 D266 LF 31 Euro 4 Number of cylinder: 6 Displacement: 1.5l Power: 44 PS Torque: 21 Nm DPF Pegasor Particle Sensor (Preversion) Figure 1: Schematic test setup. AVL MSS 483 The signal correlation has been investigated during several European Stationary and European Transient Cycles before and behind the particle trap :21:13_ mbar % Pegasor [mv] MSS [mg/m3] APC [P/cm³] REK_1HZ.TIME [s] Figure 2: Signal of PPS, MSS and APC during a transient test cycle.. 1

2 In transient tests the sensor showed a fast response time. The correlation of Pegasor signal to soot mass signal was found to be moderate, the correlation to particle number concentration was found to be good. Pegasor [mv] Integral: Pegasor [mv] :33:34_ mbar % Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,APCxDR_U)) = e Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,Pegasor)) = REK_1HZ.TIME [s] Figure 3: Correlation of PPS to APC during a European Test Cycle. APC [P/cm³] Integral : APC [P/cm³] During the tests the Pegasor Particle Sensor showed a good signal correlation to MSS and APC. The signals were found to be reproducible. Moreover the sensor proved itself to be stable and robust und heavy duty diesel engine conditions.

3 Correlation between Pegasor Particle Sensor and Particle Number Counter Application of Pegasor Particle Sensor in Heavy Duty exhaust Dr. Harald Beck, Dr. Dieter Rothe, Christian Tyroller 16th ETH Conference on Combustion Generated Nanoparticles, June 24th 27th 212 Zurich ETH Zentrum, Main Building, HG E7

4 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 2 >

5 1 Motivation For EURO VI Homologation particle emission limits have to be fulfilled: PN: # kw h -1 (WHTC) and # kw h -1 (WHSC) PM: 1 mg kwh -1 The proposed setup according to UN ECE Regulation 49 is bulky and cost intensive (Invest and life cycle cost) Particle number concentration measurement according to UN ECE Regulation 49 has an impact on particle mass measurement with partial dilution systems Demands from engineers for an alternative system: Its signal should correlate with certification standard system It should be able to measure transient cycles It should be small and robust (raw exhaust application) It shall need little service effort (Cost effect in invest and life cycle), Easy operation (plug and play) should be ensured < 3 >

6 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 4 >

7 2 Peagasor Particle Sensor (1/3) (Sensor Layout) dilution air < 5 >

8 2 Pegasor Particle Sensor (2/3) (Operating principle) I in Sample in Faraday cup Isolated power transfer Aerosol charging Charger power I n = I out -I in I n I out Sample out Electrometer Technique referred to as Escaping Current < 6 >

9 2 Peagasor Particle Sensor (3/3) (Sensor Physical Dimensions) Carrier air Inlet Outlet Main Features Compact design, installed directly to the tailpipe Particles are not collected Sensitive parts protected from exhaust flow => Low maintenance High resolution and sensitivity (1 Hz,.3sec Response Time) < 7 >

10 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 8 >

11 3 Experimental Setup (1/3) (Schematic Overview) AVL APC 489 D266 LF 31 Euro 4 Number of cylinder: 6 Displacement: 1.5l Power: 44 PS Torque: 21 Nm DPF Pegasor Particle Sensor (Preversion) AVL MSS 483 < 9 >

12 Experimental Setup (2/3) (Test cell) Engine Pegasor MSS APC < 1 >

13 Experimental Setup (3/3) (Test programme) Investigation topics: Influence of dilution air pressure on the PPS signal Signal correlation of PPS vs APC and MSS in stationary test cycle (ESC) Signal correlation of PPS vs APC and MSS in transient test cycle (ETC) Correlation in raw exhaust and after diesel particulate filter < 11 >

14 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 12 >

15 4 Influence of dilution air pressure (1/4) (Test programme) :47:53_ mbar 42% Pegasor PPS-Luftdruck [mbar] Air pressure M [Nm] N [U/min] engine speed torque :: 11:2: 11:4: 12:: 12:2: 12:4: 13:: 13:2: 13:4: 14:: Zeit time < 13 >

16 4 Influence of dilution air pressure (2/4) (Signal sequence) :19:16_ mbar 39% Pegasor Pegasor [mv] MSS [mg/m³] 15 APC [P/cm³] :2: 15:4: 16:: 16:2: 16:4: 17:: 17:2: 17:4: 18:: Zeit time < 14 >

17 4 Influence of dilution air pressure (3/4) (PPS vs. MSS) M1 M2 M3 4 PPS/MSS [mv/(mg/m 3 )] y =,65x + 18,811 R 2 =,955 y =,13x + 7,1543 R 2 =,9997 y =,16x + 6,5155 R 2 =, Air pressure Druck [mbar] < 15 >

18 4 Influence of dilution air pressure (4/4) (PPS vs. APC) M1 M2 M3 2,5E-5 PPS/APC [mv/(1/cm 3 )] 2,E-5 1,5E-5 1,E-5 5,E-6 y = 5E-9x + 1E-5 R 2 =,9838 y = 8E-9x + 4E-6 R 2 =,9982 y = 6E-9x + 3E-6 R 2 =,9935,E Air pressure Druck [mbar] < 16 >

19 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 17 >

20 5 Correlation Stationary tests (1/7) (Test programme) :43:1_ mbar 42% N [U/min] M [Nm] :: 1:: 11:: 12:: 13:: 14:: 15:: 16:: Zeit time < 18 >

21 5 Correlation Stationary tests (2/7) (PPS vs. MSS raw exhaust) :37:3_ mbar % _d266lf31_tl_1848.b1.utx.nc (Pegasor,MSSxDR_U): Minimum...: -.11 Maximum...: arith. Mittelwert...: Mittlere Abweichung.: Varianz...: Standard-Abweichung.: Polynom-Ordnung 1: f(x) = p + p1*x +... MSS [mg/m³] 25 2 p = p1 = R= _d266lf31_tl_1848.b1.utx.nc (Pegasor,MSSxDR_U): correlation = Pegasor [mv] < 19 >

22 5 Correlation Stationary tests (3/7) (PPS vs. APC raw exhaust) :37:3_ mbar % _d266lf31_tl_1848.b1.utx.nc (Pegasor,APCxDR_U): Minimum...: -4 Maximum...: 2.34e+7 arith. Mittelwert...: e+6 Mittlere Abweichung.: e+6 Varianz...: e+13 Standard-Abweichung.: e+6 Polynom-Ordnung 1: f(x) = p + p1*x +... APC [P/cm³] p = p1 = R= _d266lf31_tl_1848.b1.utx.nc (Pegasor,APCxDR_U): correlation = Pegasor [mv] < 2 >

23 5 Correlation Stationary tests (4/7) (PPS vs. MSS post DPF) :43:1_ mbar % _d266lf31_tl_1832.b1.utx.nc (Pegasor,MSSxDR_U): Minimum...:.39 Maximum...: arith. Mittelwert...: Mittlere Abweichung.: Varianz...:.4331 Standard-Abweichung.:.2826 MSS [mg/m³] 1. R=.83.5 Polynom-Ordnung 1: f(x) = p + p1*x +... p = p1 = _d266lf31_tl_1832.b1.utx.nc (Pegasor,MSSxDR_U): correlation = Pegasor [mv] < 21 >

24 5 Correlation Stationary tests (5/7) (PPS vs. APC post DPF) :43:1_ mbar % _d266lf31_tl_1832.b1.utx.nc (Pegasor,APCxDR_U): Minimum...: 179 Maximum...: 2.6e+6 arith. Mittelwert...: Mittlere Abweichung.: Varianz...: e+11 Standard-Abweichung.: Polynom-Ordnung 1: f(x) = p + p1*x +... p = p1 = APC [P/cm³] R= _d266lf31_tl_1832.b1.utx.nc (Pegasor,APCxDR_U): correlation = Pegasor [mv] < 22 >

25 5 Correlation Stationary tests (6/7) (PPS vs. MSS) MSS [mg/m3] 3 2,5 2 1,5 1 y =,453x +,572 y =,354x +,3461 y =,255x +,122 Rohabgas raw exhaust nach post DPF Ausgleichsgerade Intermediate, Pegasor [mv] < 23 >

26 5 Correlation Stationary tests (7/7) (PPS vs. APC) 3,5E+6 Rohabgas nach DPF Ausgleichsgerade raw exhaust post DPF Intermediate APC [P/cm3] 3,E+6 2,5E+6 2,E+6 1,5E+6 1,E+6 y = 57961x y = 47567x y = 37173x ,E+5,E Pegasor [mv] < 24 >

27 Agenda 1 Motivation 2 Pegasor Particle Sensor 3 Test setup and Programme 4 Pretest results 5 Stationary Tests and Results 6 Transient Tests and Results 7 Conclusion < 25 >

28 6 Transient test signal (1/5) (PPS vs. MSS raw exhaust) :21:13_ mbar % Pegasor [mv] MSS [mg/m3] APC [P/cm³] REK_1HZ.TIME [s]. 1 < 26 >

29 6 Correlation Transient tests (2/5) (PPS vs. MSS raw exhaust) Pegasor [mv] Integral : Pegasor [mv] :33:34_ mbar % Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,MSSxDR_U)) = Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,Pegasor)) = REK_1HZ.TIME [s] MSS [mg/m3] Integral : MSS [mg/m3] < 27 >

30 6 Correlation Transient tests (3/5) (PPS vs. APC) Pegasor [mv] Integral: Pegasor [mv] :33:34_ mbar % Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,APCxDR_U)) = e+9 Integral( _d266lf31_etc_1958.b1.utx.nc (REK_1HZ_TIME,Pegasor)) = REK_1HZ.TIME [s] APC [P/cm³] Integral : APC [P/cm³] < 28 >

31 6 Correlation Transient tests (4/5) (PPS vs. APC average 6 ETC) Rohabgasformel Raw exhaust Ausgleichsformel Intermediate "nach post DPF"-Formel 3 2 Abweichung [%] Deviation Raw Messung exhaust im Rohabgas measurement Measurement Messung nach after DPF DPF Rohabgasformel Raw exhaust -19,83-22,18 Ausgleichsformel Intermediate -,8-8,35 "nach post DPF"-Formel 18,22 5,49 < 29 >

32 6 Correlation Transient tests (5/5) (PPS vs. MSS average of 6 ETC) Abweichung [%] Deviation Rohabgasformel Raw exhaust Ausgleichsformel Intermediate "nach post DPF"-Formel Raw Messung exhaust im measurement Rohabgas Measurement Messung nach after DPF DPF Rohabgasformel Raw exhaust,65 27,19 Ausgleichsformel Intermediate -23,61-6,8 "nach post DPF"-Formel -47,86-4,79 < 3 >

33 7 Conclusion Pegasor Particle Sensor (PPS) was tested under heavy duty real world conditions. In transient tests the sensor proofed a fast response time With constant dilution air pressure results were found reproducible (For traceability reasons an additional pressure recording is recommended) Under partial load stationary conditions good correlation were found for raw exhaust measurements MSS- (>96%) and APC-Signal (>98%) and for measurements after DPF MSS- (>83%) and APC-Signal (>97%) The correlation equation found under partial load condition were applied on ESC and ETC. The calculated results lead to deviations of less than 1 % compared with reference analytics. < 31 >

34 Time for Questions Dr. Harald Beck Dr. Dieter Rothe Christian Tyroller MAN Truck & Bus AG EMFA Vogelweiherstrasse Nürnberg Tel MAN Truck & Bus AG EMRE Vogelweiherstrasse Nürnberg Tel MAN Truck & Bus AG EMRE Vogelweiherstrasse Nürnberg Tel The authors would like to thank: Juha Tikkanen (Peagasor) Thomas Hamacher (MS4) for the technical support. < 32 >