4.2 Post-DPF (1.5 x T.A.) simulation – Filtration efficiency
4.3.3 Final PM map and results for VeLoDyn’s model (Honda Accord on-road measurements)
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Figure 4.74: 1.5 x T.A. Extra Urban driving cycle
4.3.2 Filtration efficiency for VeLoDyn’s model (Honda Accord on-road
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Figure 4.75: : Pegasor Particle Soot Sensor data compared to VeLoDyn results with PM map from test
#7 for on-road 1.5 x T.A. Urban driving cycle
For the second on-road driving cycle, the Extra Urban the results using the test #7 as NEDC, Artemis Urban and WLTC are very satisfactory (Figure 4.76). The cumulative soot emission per kilometer is around 3 mg/km.
Figure 4.76: Pegasor Particle Soot Sensor data compared to VeLoDyn results with PM map from test
#4 for on-road 1.5 x T.A. Extra Urban driving cycle
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Figure 4.77: Comparison Urban and Extra Urban post-DPF (1.5 x T.A.) soot emission simulation on VeLoDyn and on-road measurement
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5 CONCLUSION
The final conclusion is that the target of this thesis was met. A reliable and relatively accurate simulation model for soot emissions were created. The results were validated for NEDC, Artemis Urban
& Extra Urban, WLTC and on-road driving cycles. For all these cases, the results were quite promising for the final target of creating an OBD model for checking the DPF condition during real world driving conditions. Furthermore, the on-road measurements led to the formation of a great database for soot emissions on real world driving conditions which could be the source for many others thesis in this field.
Taking a closer look in every part:
The first part of this thesis was the on-road measurements with Honda Accord 2.2i-CTDi vehicle. The vehicle’s equipment were the Pegasor Particle Sensor for soot emissions measurement, the ETAS hardware for DPF’s monitoring, the ScanMaster for ECU’s data logging and two resistive soot sensors for use in another project. The routes were designed for covering a great range of driving conditions, from urban to highway conditions.
The second part was the VeLoDyn’s model’s construction for engine-out soot emission simulation. The main aspects of this model were the vehicles characteristics, the driving cycle and the PM map which needed input data from in-laboratory measurements. Three main sources of input data were used: Daimler steady-states, Daimler NEDC steady-states and Honda Accord NEDC steady-states.
As far as the driving cycles, NEDC, Artemis Urban & Road, WLTC, US06, and FTP75 were simulated. The vehicle’s characteristics were for Honda Accord vehicle with 2.2i-CTDi diesel engine.
The primary simulation results were compared to Micro Soot Sensor results from Honda Accord in-laboratory measurements. These measurements were composed of NEDC, Artemis Urban, Artemis Road and WLTC measurements. For the primary simulation process, only NEDC data were used for comparison with MSS results. After a lot of approaches concerning the final synthesis of input data, a model with very good convergence between PPS and MSS were created. The next step was the evaluation of the model on WLTC and Artemis driving cycles. The results were acceptable but shown also that there is need of calibration of the model for better convergence in different driving cycles.
In addition to the above analysis for engine-out emissions, an examination of the filtration efficiency of DPFs during different driving cycles was necessary. Based on Honda Accord’s in-laboratory measurements, it was concluded that for 1.5 x T.A. artificially destroyed DPF, the mean value of the filtration efficiency was constant (82%) and independent from the driving cycle. Incorporating the filtration efficiency on VeLoDyn’s model and comparing the results with MSS measurements on NEDC, Artemis (Urban & Road) and WLTC, it was obvious that the differences were acceptable and were following the engine-out emission tendency.
The last part was the Honda Accord on-road measurement’s simulation. The comparison for soot emissions was done with PPS measurements. The simulation was made for 2 driving cycles: Urban
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and Extra Urban. The first one is similar to Artemis Urban and the other similar to Artemis Road. The simulation was done for post-DPF emissions with the 1.5 x T.A. artificially destroyed DPF and exactly the same settings as NEDC simulation (driving cycle was changed to on-road cycles). The results for Urban and Extra Urban routes shown that VeLoDyn model using the final PM map from NEDC simulation, was sufficient and the results were very close to PPS measurements.
It is obvious that the objective of this thesis was an initial examination of VeLoDyn’s model for soot emissions. There is plenty space for improvements in every part of the simulation:
1. The most important aspect of VeLoDyn’s model is the input PM map. This map was generated from data obtained by three different measurements. For better results it is suggested to repeat these measurements under exactly the same conditions of engine, DPF, measurement equipment etc. in order to minimize the effect of uncertainties.
Furthermore, the generation of the PM map was based in extrapolation from 37 to 385 cells in Matlab. More steady-states of different driving cycles would be extremely helpful for better convergence of measurement and simulation results.
2. Until now only steady-states were considered as input for the PM map. During driving cycles and especially during on-road Urban driving cycle, the transient parts of vehicles speed are the majority. It has not been examined if VeLoDyn takes into account the transient effect. A deep and detailed analysis of this effect is mandatory for improving the model.
3. Simulation for post-DPF soot emissions is highly related to the filtration efficiency of the DPF. For this thesis, a constant value of 82% was used for every driving cycle. A second-by- second analysis of the efficiency using other simulation tools as Axisuite platform (Exothermia SA) could be the next step for better simulation.
4. In order to have a more extended view of soot emissions regardless the filtration efficiency, engine-out on-road measurements could be helpful.
5. The analysis of on-road measurements should be expanded to all measuring dates (here only 2013_12_2_5 was uses for Urban driving cycle). In this case, safer and more reliable results for on-road measurements could be arise.
It is clear that the next target is to incorporate this soot model in the OBD model for checking the condition of DPF (Figure 5.1, see also paragraph 1.14).
Figure 5.1: The OBD model for checking the condition of DPF
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6 REFERENCES
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7 APPENDIX 1
Table: Honda Accord on-road measurement protocol
PC date Route km start km end URBAN EXTRA URBAN
HIGH WAY
CANalyzer File name
CANalyzer log File name
CANalyzer Start time
CANalyzer
End time PEGASOR File name PEGASOR Start time
PEGASOR
End time DPF
22/11/2013 U1 133775 133818 43 0 0 2013-11-22_1can.csv 2013-11-22_1log.txt 15:19:00 17:44:30 2013-11-22_pps1.txt 15:19:05 17:44:31 OTL +20%
22/11/2013 E3 133820 133932 0 112 0 2013-11-22_2can.csv 2013-11-22_2log.txt 18:06:57 19:47:10 2013-11-22_pps2.txt 18:07:02 19:47:12 OTL +20%
22/11/2013 H3 133948 134033 0 0 85 2013-11-22_3can.csv 2013-11-22_3log.txt 20:54:37 21:43:28 2013-11-22_pps3.txt 20:54:47 21:43:30 OTL +20%
23/11/2013 E3 134034 134141 0 107 0 2013-11-23_1can.csv 09:33:56 11:08:53 2013-11-23_pps1_corrected.txt 09:33:59 11:08:55 OTL +20%
26/11/2013 U1 134229 134273 44 0 0 2013-11-26_1can.csv 2013-11-26_1log.txt 16:50:54 18:52:52 2013-11-26_pps1.txt 16:50:58 18:52:53 OTL +20%
27/11/2013 U1 134275 134309 34 0 0 2013-11-27_1can.csv 2013-11-27_1log.txt 11:15:44 12:47:09 2013-11-27_pps1.txt 11:15:49 12:47:11 OTL +20%
27/11/2013 U1 134309 134318 9 0 0 2013-11-27_2can.csv 2013-11-27_2log.txt 12:51:03 13:23:28 2013-11-27_pps2.txt 12:51:07 13:23:29 OTL +20%
27/11/2013 U1 134318 134360 42 0 0 2013-11-27_3can.csv 2013-11-27_3log.txt 14:10:29 16:13:25 2013-11-27_pps3_corrected.txt 14:10:33 16:13:27 OTL +20%
27/11/2013 E6 134360 134402 0 42 0 2013-11-27_4can.csv 2013-11-27_4log.txt 16:27:12 17:06:54 2013-11-27_pps4_corrected.txt 16:27:18 17:06:55 OTL +20%
28/11/2013 U1 134404 134447 43 0 0 2013-11-28_1can.csv 2013-11-28_1log.txt 09:16:58 11:21:59 2013-11-28_pps1.txt 09:17:03 11:22:01 OTL +20%
28/11/2013 U1 134449 134492 43 0 0 2013-11-28_2can.csv 2013-11-28_2log.txt 14:19:22 16:32:52 2013-11-28_pps2.txt 14:19:26 16:32:53 1.5xTA
28/11/2013 U1 134492 134535 43 0 0 2013-11-28_3can.csv 2013-11-28_3log.txt 17:02:27 18:58:31 2013-11-28_pps3.txt 17:02:32 18:58:32 1.5xTA
29/11/2013 U1 134537 134556 19 0 0 2013-11-29_1can.csv 2013-11-29_1log.txt 10:36:16 11:35:13 2013-11-29_pps1.txt 10:36:21 11:35:14 1.5xTA
29/11/2013 U1 134556 134580 24 0 0 2013-11-29_2can.csv 2013-11-29_2log.txt 11:39:05 12:53:32 2013-11-29_pps2.txt 11:39:11 12:53:33 1.5xTA
29/11/2013 E3 134580 134695 0 115 0 2013-11-29_3can.csv 2013-11-29_3log.txt 14:28:13 16:18:28 2013-11-29_pps3.txt 14:28:17 16:18:30 1.5xTA
29/11/2013 H3 134695 134780 0 0 85 2013-11-29_4can.csv 2013-11-29_4log.txt 16:20:11 17:09:27 2013-11-29_pps4.txt 16:20:16 17:09:30 1.5xTA
02/12/2013 U1 134781 134801 20 0 0 2013-12-2_1can.csv 2013-12-2_1log.txt 10:32:56 11:26:11 2013-12-2_pps1.txt 10:32:59 11:26:12 1.5xTA
02/12/2013 U1 134801 134825 24 0 0 2013-12-2_2can.csv 2013-12-2_2log.txt 11:49:00 13:08:04 2013-12-2_pps2.txt 11:49:05 13:08:06 1.5xTA
02/12/2013 E6 134825 134866 0 41 0 2013-12-2_3can.csv 2013-12-2_3log.txt 13:18:07 13:58:41 2013-12-2_pps3.txt 13:18:13 13:58:42 1.5xTA
02/12/2013 E6 134866 134907 0 41 0 2013-12-2_4can.csv 2013-12-2_4log.txt 14:01:00 14:40:50 2013-12-2_pps4.txt 14:01:04 14:40:51 1.5xTA
02/12/2013 U1 134907 134950 43 0 0 2013-12-2_5can.csv 2013-12-2_5log.txt 14:42:17 16:54:17 2013-12-2_pps5.txt 16:42:22 16:54:19 1.5xTA
03/12/2013 E3 134952 135067 0 115 0 2013-12-3_1can.csv 2013-12-3_1log.txt 09:46:52 11:29:53 2013-12-3_pps1.txt 09:46:57 11:29:54 1.5xTA
CANalyzer PEGASOR