CLEAR Graz 19.02.2013 Stefan Hausberger, Nikolaus Furian Classification of Emissions from Automobiles in Real Driving Graz 19.02.2013 Stefan Hausberger, Nikolaus Furian

„Risk for legislation“ Introduction Goal for evaluation method: An evaluation method for PEMS tests at passenger cars shall ensure low RDE by good coverage of real driving situations (important for legislation and for meeting air quality targets) enable a fair comparison of measured emissions also for very different driver behaviour (important for industry) PEMS results for mid class EURO 6 car: driving style correlated variability Moderate driving Normal driving Aggressive driving „Risk for legislation“ „Risk for OEM“ HDV: g/kWh LDV: g/km! Low kWh/km “average” kWh/km high kWh/km Introduction Interface Frequency map Data and settings Output

Weighting emission data using a target frequency map Average of emission data over e.g. 3 seconds is computed Resulting average values are assigned, according to engine speed and engine, to an array with the same structure as the target frequency map, Method Interface Frequency map Data and settings Output

Weighting emission data using a target frequency map Average values of the cells in the array are built and weighted with the corresponding frequencies of the target Engine Speed Power Weighted Emission= ⋅0.2+ ⋅0.14+…+ ⋅0.02 Emission Per Distance: Weighted Emission g km = Weighted Emission g h Weighted Speed km h Mean Emission g km = MeanEmission g h Mean Speed km h Method Interface Frequency map Data and settings Output

REDES User Interface Method Interface Frequency map Data and settings Output

Loading target frequency maps (Goal Patterns) Absolute from file: De-normalize from standard map: Standard map may be configurated via XML- settings file <PPattern> <P>-1.8</P> <P>-1.2</P> <P>-0.6</P> … Method Interface Frequency map Data and settings Output

Loading data and calculation Settings Input Data: Settings: Averaging width and boundaries can be set by the user Emission values to be loaded are optional and may be configurated via XML- setting file Method Interface Frequency map Data and settings Output

Goal Pattern Analysis Goal Pattern vs. Driving Pattern File Selection Statistical Analysis Method Interface Frequency map Data and settings Output

Thank you for your attention!

Normalization and/or categorisation of target frequency maps Possible Methods Different “Target Frequency maps“ for different classes of passenger cars (would require a framework to classify passenger cars) Introduction of a normalized power on the X-axis of the target frequency maps Unified and normalized target frequency map would be easier to handle. However, the existence of a fair normalization has to be proven. In the following a promising method is presented: Content Introduction Method Optimisation Sources Application transport time Outlook

Normalization of target frequency maps 𝑃𝑛𝑜𝑟𝑚= 𝑃𝑒𝑚𝑜𝑡 𝑃𝑤 with PW…….power at wheels (v * F) from settings at vehicle type approval at defined velocity and acceleration (e.g. 70 km/h with 0.45 m/s²), 𝑃 𝑤 =𝑣⋅(𝐴+𝐵⋅𝑣+𝐶⋅ 𝑣 2 +𝑆𝑀𝐾⋅𝑎) Small car TUG-Data SMK: 1130kg 1130.00 1250.00 kg A: 110,9 110.90 118.40 N B: 0,409 0.41 N h/km C: 0,02938 0.03 N h²/km² Straßenlast für Normierung v= 70.00 km/h a = 0.45 m/s² --> Pe = 15.40 kW Example for normalized map Application for considered vehicle: De-normalise x-, y-axis from frequency distribution to rpm and kW based on chassis dyno type approval settings Normalisation considers influence of different vehicle specifications Easy to handle P_norm Pe from to Frequency 8.20   126 0% 7.30 112 6.40 99 5.50 85 4.60 71 1% 3.70 57 2% 2.80 43 6% 1.90 29 11% 1.00 15 38% 0.10 1.54 15.40 12% -0.10 -1.54 10% -1.00 -15.40 20% Ok if “normalized frequency distributions” do not differ over vehicle classes! Content Introduction Method Optimisation Sources Application transport time Outlook

Normalization of target frequency maps Analysis of BMW Data: Mini, 320d and X5 Comparison X-axis in kW (left chart) and normalized axis (right chart) Over absolute power the X5 has, as expected, higher frequencies for higher levels of power than the 320d or Mini A normalized power leads to similar histograms (right chart) Particular attention only on high levels of power Further tests suggested! Content Introduction Method Optimisation Sources Application transport time Outlook