1. WLTP – NEDC Correlation Exercise CO2MPAS v1.1.XX validation and Description of main model changes Ispra 1 Feb 2016 Anastasios Kontses (LAT), Stefanos Tsiakmakis, Victor Valverde, Georgios Fontaras, Vincenzo Arcidiacono, Kostis Anagnostopoulos, Biagio Ciuffo (JRC)

2. Summary 2

3. CO2MPAS status (19/01/2016) (cruise batches 1710 cases non filtered) 3 NEDC [gCO2/ km ] UDC [gCO2/ km ] EUDC [gCO2/ km ] Averages1.633.20.65 StdError0.090.170.06 Median1.913.730.98 Mode0.49-1.08-2.77 StdDev3.697.142.61 Variance13.6450.916.82 Kurtosis96.9755.09101.72 Skweness7.145.156.21 Range70.71112.9650.31 Minimum-7.24-18.42-5.1 Maximum63.4794.5445.2 Sum2794.035479.471109.45 Count1710 Confidence level (95%) 0.180.340.12

4. Performance per technology 4 Technology typeTechnology code Base caseBC Gear configuration A GCA Gear configuration B GCB No Start/StopNOSS No Break energy recuperation BERS Variable valve lifting VVL Direct injection/Multipoin t injection DI/MPI Thermal management ThM

5. Statistics per subcycle 5 NEDC error BCGCAGCBNOSSBERSVVL DI/M PI ThM Avera ges 1.731.621.822.32-1.333.031.331.89 StdErr or 0.10.120.150.160.13 0.170.14 Media n 2.231.982.052.57-1.563.321.892.47 StdD ev 1.551.922.32.472.041.41.751.98 Varian ce 2.393.685.276.094.161.963.053.9 Kurtos is 1.11.190.17-0.93-0.273.58-0.84-1.31 Skwe ness -0.94-0.88-0.49-0.230.620.46-0.4-0.23 Range9.5712.2213.219.999.479.927.077.64 Minim um -4.39-7.24-6.51-2.95-5.7-0.31-2.46-2.26 Maxi mum 5.184.986.77.043.779.624.625.38 Sum435395443563-323327144358 Count252243 108 189 Confid ence level (95% ) 0.190.250.290.320.260.270.340.29 UDC error BCGCAGCBNOSSBERSVVL DI/M PI ThM Aver ages 3.333.413.25.22-3.076.283.454.17 StdEr ror 0.210.250.3 0.250.270.210.27 Media n 4.034.453.574.52-3.595.993.584.93 StdD ev 3.363.914.674.713.942.822.193.65 Varia nce 11.315.3121.8522.2215.57.944.813.29 Kurto sis 4.65.494.17-0.670.547.091.77-0.37 Skwe ness -1.76-1.84-0.330.040.971.810.75-0.4 Range23.9130.536.2922.6920.3420.0612.1617.27 Minim um - 11.98 - 18.02 - 17.27 -7.92 - 12.29 1.34-0.71-4.05 Maxi mum 11.9312.4819.0214.778.0521.4111.4613.21 Sum8388287791269-747678372787 Count252243 108 189 Confi dence level (95% ) 0.420.50.6 0.510.540.420.53 EUDC error BCGCAGCBNOSSBERSVVL DI/M PI ThM Avera ges 0.720.510.940.57-0.381.080.030.51 StdErr or 0.110.120.130.120.130.170.240.13 Media n 1.020.681.221.02-0.121.230.481 StdD ev 1.681.912.071.951.991.782.51.76 Varian ce 2.833.664.293.783.953.176.233.11 Kurtos is -0.19-0.47-0.18-0.94-0.83-1.28-1.37-0.68 Skwe ness -0.55-0.17-0.41-0.45-0.290.140.04-0.59 Range7.558.69.938.279.126.438.76.98 Minim um -3.57-3.96-4.62-4.14-5.1-2.11-4.23-3.63 Maxim um 3.984.645.314.134.014.314.483.35 Sum183125229140-92116396 Count252243 108 189 Confid ence level (95%) 0.210.250.270.250.260.340.480.26

6. Initial conclusion comparison (Cruise batch) 6 The latest internal CO2MPAS version performs within expected margins Improved stability Slightly more accurate A series of bugs were corrected (See following slides) Some outliers (errors >30) still occur due to issues in the input data and the convergence of the optimizer Results 100% comparable to O’ Snow release (2/2016)

7. Validation of CO 2 MPAS against measurement and Cruise data  LAT provided support to the JRC for the validation of CO2MPAS against the available measurement data and the baseline Cruise models (reference Cruise models investigated not the models used for the batch runs)  2 CO2MPAS versions used in the analysis V1.0.5 (similar but not equal to last release) and the update of V1.0.5 which is equivalent but not the same to the new O’Snow release (V1.1)  A general summary follows – more detailed information provided further on  These following results are not final, some issues should be additionally corrected e.g. use exact gear shifting profile from target dataset for manual transmission vehicles.  CO 2 MPAS FC model is continuously being updated so the results will be re evaluated. 7

8. CO 2 from all vehicles – Target: Measurement (NEDC) 8 Runs with different versions of CO 2 MPAS with exactly the same inputs Auto Gearbox Manual Gearbox

9. Reality check – CO2MPAS vs Measurement (MTs) NEDC [gCO 2 km −1 ] UDC [gCO 2 km −1 ] EUDC [gCO 2 km −1 ] Averages0.25-0.370.64 StdError2.084.091.31 Median-0.223.591.86 ModeNaN StdDev6.2412.273.93 Variance38.88150.5915.45 Kurtosis2.361.29-1.06 Skweness-0.7-0.82-0.43 Range23.142.8611.56 Minimum-12.67-24.55-5.75 Maximum10.4318.315.81 Sum2.24-3.295.72 Count999 Confidenc e level (95%) 4.168.182.62 9 The purple box represents the 1st and 3rd quartile. The dark purple line is the median. The yellow dot is the mean. the whiskers show the min and max values.

10. Reality check CO2MPAS vs Measurement (ATs) 10 NEDC [gCO 2 km −1 ] UDC [gCO 2 km −1 ] EUDC [gCO 2 km −1 ] Averages-0.54-7.073.13 StdError2.164.051.89 Median-2.44-9.52.34 ModeNaN StdDev5.39.934.62 Variance28.0998.5321.36 Kurtosis1.61-1.130.48 Skweness1.410.65-0.05 Range14.2525.3513.57 Minimum-5.31-17.65-3.85 Maximum8.957.79.72 Sum-3.21-42.4418.76 Count666 Confidenc e level (95%) 4.328.13.78 The purple box represents the 1st and 3rd quartile. The dark purple line is the median. The yellow dot is the mean. the whiskers show the min and max values.

11. Repeatability & Reproducibility 11 Typical Reproducibility issues (working on them) Typical Repeatability issue (test cases created – issue solved when python libraries are the same)

12. Main model changes and issue updates Performed together with LAT a detailed analysis comparing measurement data from their vehicles and the respective simulations with CO2MPAS outputs Specific bugs were identified or confirmed and corrected Some remain open will be handled in next version Following slides provide a detailed account 12

13. Validation of CO 2 MPAS against measurement and Cruise data  Activity outline: 1.Issues found in the preparation of CO 2 MPAS input files 2.Issues found from the comparison between target (measurement/Cruise) and CO 2 MPAS output Engine coolant temperature prediction model Start-Stop model Gear shifting points compared to legislation Prediction of gear shifting points in vehicles with AT GB Calculation of negative engine power Electrical system operation Clutch model Engine switch on/off procedure Idle fuel consumption on vehicles with Torque Converter Deviation between summary and time series CO 2 results Prediction of fuel consumption Cold start effect on fuel consumption 3.Overall CO 2 results 4.Conclusions 13

14. Summary and Conclusions Number of issues found during the preparation of CO 2 MPAS input files: 6  A solution for all of them has already been found and tested in all vehicles. These solutions will be implemented in the next official version of CO 2 MPAS. Number of issues found based on the comparison between target (measurement/Cruise) and CO 2 MPAS output results: 19  10 of them have completely been solved, tested under different test cases and will be implemented in the next official version of CO 2 MPAS.  For 3 of them a final solution has been proposed and the next step is to run different test cases in order to prove their validity.  For the rest issues (most of them are related to the FC calculation), there are a few suggested solutions that should be further investigated and evaluated in order to be incorporated in the next official versions of CO 2 MPAS. The initial target of creating a stable simulation model, especially in the field of power calculation, has been largely achieved. As next steps the following are proposed: o Evaluation of all the proposed solutions for the remaining open issues especially in the power calculation module. o In-depth analysis of the deviations observed in FC model and selection of a final solution for each issue in FC sub-model. o Development of robust and reliable test cases based on all the available data until now. This is of high importance for the final validation process of CO 2 MPAS. o Further development of the existing post-processing tool in the direction of user-customization in order the user to be able to create a report based on his needs. 14

15. Issues found in the preparation of CO 2 MPAS input files 1.Fuel carbon content: CO 2 MPAS input file contains only one value for fuel carbon content but in some cases the values between NEDC and WLTP are different (as derived from measurements).  Cycle-specific fuel carbon content values can be easily added in input file by adding extra rows in the relevant field. 2.Start-Stop first activation time: CO 2 MPAS requests as input only one value of S-S activation time. But in some cases two values are needed to describe correctly the operation in NEDC and WLTP.  The NEDC value should be used as input. The WLTP value is calculated from the time series data provided by the user (engine speed, velocity). 3.Dynamic rolling radius: In CO 2 MPAS input file, only one value of rolling radius is needed. If, for any reason (e.g. different tire pressure), the rolling radius is different between NEDC and WLTP, discrepancies in final results are created.  Cycle-specific dynamic rolling radius values can be easily added in the input file. In addition, a check will be performed internally in order to find if the input value of WLTP is correct. 15

16. Issues found in the preparation of CO 2 MPAS input files 4.Mechanical consumer: In most Cruise models a mechanical consumer (0.5-1 Nm) is used in order to simulate the additional load from engine auxiliaries but this was not requested as an input in CO 2 MPAS.  An additional input should be added in CO 2 MPAS input file in order to take into account this extra load. A default value is set to 0.5 Nm. 5.Input time series length: It is necessary that the length of input signals is 1180s for NEDC and 1800s for WLTP (H-L). Otherwise CO 2 MPAS does not create final results.  A warning flag will be added in CO 2 MPAS in order to inform the user if the length is wrong. 6.Input data for electrical system: Battery SOC balance and window: In some cases these values cannot be accurately determined from measurement data. Thus, the calibration of electrical model and consequently the fuel consumption are affected.  In latest version of CO 2 MPAS these values are not necessary, while time series data of alternator current must be provided as input. Time series data of alternator power : If this signal is not available, then the above-mentioned data and some additional inputs are necessary (start demand, electric load, max battery charging current, alternator charging currents) and should be added to the inputs template file. 16

17. Result analysis Issues found from the comparison between target (measurement/Cruise) and CO 2 MPAS output: 1.Engine coolant temperature prediction model 2.Start-Stop model 3.Gear shifting points compared to legislation 4.Prediction of gear shifting points in vehicles with AT GB 5.Calculation of negative engine power 6.Electrical system operation 7.Clutch model 8.Engine switch on/off procedure 9.Idle fuel consumption on vehicles with Torque Converter 10.Deviation between summary and time series CO 2 results 11.Prediction of fuel consumption 12.Cold start effect on fuel consumption 17 Comments: In all the following CO 2 MPAS models, only WLTP-H was used as input cycle. Although in some cases data from WLTP-L was also available, it was not used for simplicity reasons and it will be used in next steps. In the following slides, CO 2 MPAS results from two different versions are presented (v.1.0.5 and 1.1.0.dev2 – latest unofficial version). The results of the latest version contain all the solutions found for each issue.

18. 1. Engine coolant temperature prediction model Issue #1 found: In some cases CO 2 MPAS fails to follow the target temperature and consequently the fuel consumption during cold start is affected. Reasons (issues in measured coolant temperature data) and possible solutions: Coolant temperature constant although engine is on (during first 20-40s).  Do not take into account this first part. Up and downs (consecutive or not) in coolant temperature (due to the operation of the thermostat or the fan or active radiator grill). Three (or more) distinctive areas with different slope in temperature curve (probably due to thermal management system).  Split the temperature curve in three areas and apply different calibration for each one. Issue #2 found: In some cases there is no cold start effect in the NEDC prediction. Reason and solution: Max temperature in NEDC is less than the target temperature as defined by the WLTP measurement data. In such cases - due to a bug in the code and while the opposite should be observed - CO 2 MPAS runs the cycle as hot.  The bug was identified and resolved. 18

19. 1. Engine coolant temperature prediction model 19 Engine on but temperature constant Consecutive increase- decrease of engine temp. 112233

20. 1. Engine coolant temperature prediction model – CO2MPAS results 20

21. 2. Start-Stop model Issue #1 found: CO 2 MPAS cannot follow the exact operation of S-S identified in measurement or simulation. Reason: Provided gear is not used for the determination of S-S operation. CO 2 MPAS uses only the time and velocity signals (with some additional corrections based on NEDC legislation).  Gear time series are used in the latest CO 2 MPAS version for the correct determination of S-S operation. 21

22. 2. Start-Stop model 22 Issue #2 found: Wrong operation of S-S in CO 2 MPAS compared to the expected operation based on NEDC legislation. Reason: Wrong “translation” of legislation prescription.  NEDC legislation inserted correctly in CO2MPAS *NEDC legislation does not determine the engine switch on/off points but it prescribes the exact gears and clutch operation after and before a standstill. Taking into account that the operation of S-S system in modern vehicles is controlled based on clutch and gear (the engine is switched off when the gear is neutral and the clutch is not pressed, the engine is switched on again when the driver presses the clutch pedal), we can determine the “expected” operation of S-S based on legislation.

23. 3. Gear shifting points compared to legislation Issue found: Gear shifting points in CO 2 MPAS do not follow legislation prescription (mainly in UDC). Reason: Gear upshifting points imported in CO 2 MPAS are 1s later compared to legislation.  Gear shifting points from NEDC legislation inserted correctly in CO 2 MPAS 23

24. 4. Prediction of gear shifting points in vehicles with AT GB Issue #1 found: Gear shifting points of AT GB predicted by CO 2 MPAS (given velocity profile) have some deviations compared to target (measurement or Cruise). This issue affects the engine speed and FC correlation between target and CO 2 MPAS. Issue #2 found: The operation of the S-S system is also affected due to wrong calculation of gear shifting. CO 2 MPAS puts the 1 st gear 1-2s earlier compared to target. 24 R 2 =0.97 Vehicle #Engine Speed R 2 1 (A8)0.89 2 (328)0.97 3 (350)0.92 4 (V40)0.95 Despite the fact that there are some deviations in gear shifting points (1-2s in most cases), the R 2 value is quite satisfactory in all vehicles studied.

25. 5. Calculation of negative engine power Issue #1 found: Extreme overestimation (as an absolute value) of the engine’s negative power (from the wheels) during deceleration periods. Reason: Bug in the extrapolation of the full load curve and power correction function  Bug corrected 25

26. 5. Calculation of negative engine power Issue #2 found: CO 2 MPAS still overestimates the negative power of the engine during deceleration periods. Reason: Wrong motoring curve and no use of brakes in CO 2 MPAS. As a result all the power from the wheels goes directly to the engine without a realistic limitation.  Motoring curve calculation updated and now determined from the friction losses parameters of the engine. 26

27. 5. Calculation of negative engine power 27 Issue #3 found: During idling phases after deceleration, the calculated engine power is still negative and not zero as it should be. This issue affects the operation of fuel cut-off and Brake Energy Regeneration System: Possible Reason: The clutch isn’t disengaged during these phases. 1.Effect on fuel cut-off system: The identified negative engine power leads to FC cut-off when not needed.  As a first step an rpm limit is added to deactivate the cut-off when the engine speed drops below a certain limit (e.g. 100 rpm above idle).  The calculation of engine power should be corrected in order to be zero during idle. 2.Effect on Brake Energy Regeneration System (BERS): The controller of this system identifies negative power even during idling phases and as a result the generator is activated. Thus, the SOC is affected and consequently the charging-discharging periods may be affected. The final results is an effect on fuel consumption.

28. 5. Calculation of negative engine power - Fuel cut-off system 28 CO 2 MPAS engine power negative during idle

29. 5. Calculation of negative engine power - BERS 29 Issue still open

30. 6. Electrical system operation 30 Issue #1 found: Calculated SOC values of CO 2 MPAS above 100% and below 0. Reason: Parameter “Initial SOC NEDC” of CO 2 MPAS input file had wrong unit  Corrected Issue #2 found: In some cases, CO 2 MPAS fails to calculate engine power and thus fuel consumption. Reason: Bug in the alternator power demand calculation function  Corrected Issue #3 found: In some cases of vehicles equipped with BERS, CO 2 MPAS fails to predict the correct BERS strategy in NEDC. Reason: A different strategy is observed between the measurement of NEDC and WLTP. CO 2 MPAS is calibrated based on the one of WLTP, and thus fails to predict correctly the NEDC.  This could be resolved by providing additional inputs relative to the BERS operation (in NEDC) Issue still open

31. 7. Clutch model Issue found: The clutch component of CO2MPAS does not work properly. There is a significant increase of engine speed during gear upshifting. Reason: It seems that the clutch pedal is pressed before the acceleration pedal is released.  Clutch model in CO 2 MPAS corrected 31

32. 8. Engine switch on/off procedure Issue found: During the engine switch-on/off procedure the engine speed is rapidly decreasing/increasing as shown in the following graph. This issue only affects the engine speed correlation between measurement and CO 2 MPAS, with no major effect on the fuel consumption. Reason: It seems that the engine inertia is not taken into account in CO 2 MPAS during these phases. 32 Issue still open

33. 9. Idle fuel consumption on vehicles with Torque Converter Issue found: For AT vehicles with torque converter, idle fuel consumption of CO 2 MPAS is underestimated. Reason: The CO 2 MPAS input “conventional” idle fuel consumption does not include torque converter losses. Due to the operation of the torque converter idling points, as defined by engine speed = idle speed and BMEP = 0, do not exist (except when we have braking). On the contrary, idling points are defined as engine speed = idle speed and BMEP = Torque Converter Idling Power Demand.  A corrected idle Fc should be used, or include torque converter losses in the idling points. 33 Issue still open

34. 10. Deviation between summary and time series CO2 results Issue found: There is a small deviation between CO 2 result in summary file of CO 2 MPAS and the value calculated from series output (max. 0.1 g/km). Reason: This comes from the numeric calculation of the overall CO 2 value in CO 2 MPAS summary file (calculated without the first row of instantaneous data). 34 ExampleCO2 [g/km] Summary file 135.89 Calculation from output data series 135.96 Issue still open

35. 11. Prediction of fuel consumption Issue found: In some steady-state points CO 2 MPAS predicts correctly rpm and engine power but the FC is wrong (this happens both in cold and hot parts of the cycle). Reason: One possible problem is that the fuel consumption model of CO 2 MPAS (8 parameters) is calibrated under transient conditions (WLTP measurement data which contain enrichment due to transient) and then the same model (with “enriched” parameters) is used to predict the fuel consumption under steady-states. 35 Fuel consumption for steady state wrong (contains unnecessary enrichment) CO2MPAS FUEL CONSUMPTION MODEL WLTP data from measurement (contain transient enrichment) CO2MPAS fuel consumption results wrong Calibration based on measurement Fuel consumption for steady state correct (no enrichment for transient) CO2MPAS FUEL CONSUMPTION MODEL WLTP data from Cruise (no enrichment for transient) CO2MPAS fuel consumption results correct Calibration based on Cruise Issue still open

36. 11. Prediction of fuel consumption 36

37. 11. Prediction of fuel consumption 37 In order to validate the above-mentioned assumption the following test was carried out: As a first step CO 2 MPAS was calibrated based on measurement data and the results were extracted. As a second step, CO 2 MPAS was calibrated based on Cruise data which do not contain any enrichment due to transients. As shown in the respective graph, the FC results of the second case were much better although there is still a deviation which should be investigated.

38. 12. Cold start effect on fuel consumption 38 Issue found: CO 2 MPAS overestimates the cold start effect on FC. Engine power and engine speed is almost the same between the two areas highlighted in the following graph but the CO 2 MPAS FC is much different. (engine temp. prediction of CO 2 MPAS is correct in both areas) Issue still open