# WLTP-06-31e WLTP correction algorithms progress report from TUG (chassis dynamometer corrections) and TNO (coast down corrections) preliminary results.

## Presentation on theme: "WLTP-06-31e WLTP correction algorithms progress report from TUG (chassis dynamometer corrections) and TNO (coast down corrections) preliminary results."— Presentation transcript:

WLTP-06-31e WLTP correction algorithms progress report from TUG (chassis dynamometer corrections) and TNO (coast down corrections) preliminary results ( ) TU Graz: Stefan Hausberger David Leitner TNO: Norbert Ligterink Rob Cuelenaere Pim van Mensch Content of TUG slides not yet discussed with TNO

Chassis dynamometer corrections
January 20, 2014 Chassis dynamometer corrections

Correction algorithms for variations in the WLTP testing
January 20, 2014 Correction algorithms for variations in the WLTP testing Methods drafted for chassis dynamometer test (TUG) Target is, to correct all test results to the target settings. Following deviations are analysed and lead to the listed correction methods: Correct test results for imbalances in battery SOC as drafted in WLTP Set up a vehicle specific Willans linear function (from WLTP subcycles) (k = DCO2/DkWh) from the SOC-corrected WLTC test data as basis for corrections of deviations in positive wheel power). Deviation against target speed: calculate from driven speed profile the actual power at wheels [P(t) = (R0 + R1*v+R2*v² + m*a) * v], Calculate difference in average positive power values

Correction algorithms for variations in WLTP testing
January 20, 2014 Correction algorithms for variations in WLTP testing 4. Correct for deviation from target power: DPwheel = P pos-target – P pos-test Correct for deviation with vehicle based Willans function: DCO2 = DPwheel * k. Divide corrected CO2-value [g/h] by using target cycle distance [km] (not distance driven). 5. Inaccuracy of road load simulation by the chassis dynamometer: make coast down directly after WLTC for proper road load values from chassis dynamometer. Calculate avg. positive power at wheels with chassis dynamometer parameters and with target parameters  DPwheel  DCO2 6. Temperatures from preconditioning and soak: to apply generic influence on FC, seems to be best option for small temperature ranges (linear or logarithmic): Δ𝐹𝐶 % =5.18∗ln( 𝑡 𝑡𝑒𝑠𝑡 𝑡 𝑡𝑎𝑟𝑔𝑒𝑡 ) (for 20°C < ttest < 26°C)

January 20, 2014 Example for results passenger car 1 with diesel engine 6 repetitions WLTC under normal conditions Measured CO2  SOC-corrected  complete correction Note: * tests 2, 3 and 4 were out of WLTP temperature range to test temperature correction * correction for road load settings not applied (no coast down after each test available)

Cumulative application of corrections against measured CO2
January 20, 2014 Example for result passenger car 2 with diesel engine 5 repetitions with wide variations in temperature, SOC at start, driver Stepwise effects of correction functions Corr SOC Corr v-deviations Corr temp. Cumulative application of corrections against measured CO2

5. Temperatures from preconditioning and soak
January 20, 2014 5. Temperatures from preconditioning and soak Δ 𝐶𝑂 2 % =5.18∗ln 𝑡 𝑡𝑒𝑠𝑡 𝑡 𝑡𝑎𝑟𝑔𝑒𝑡 𝐶𝑂 2 𝑐𝑜𝑟𝑟𝑒𝑐𝑡𝑒𝑑 = 𝐶𝑂 2 ∗ 1+ ∆ 𝐶𝑂 2 % 100 This logarithmic function worked very well between 1°C < ttest < 90°C for the vehicles tested yet, so it should be applicable for the WLTC tests. This correction must be the final one to avoid influences of SOC or speed deviations in the CO2-value.

Overview on sequence of corrections
January 20, 2014 Overview on sequence of corrections 1) Measured values in WLTC: CO2 [g], distance [km], DSOC [kWh], Oil temperature at start [°C] instantaneous velocity [km/h] to compute average Pwheel [kW] per phase 2) DSOC correction: apply WLTP option (or detailed approach) DCO2 SOC [g] = kengine x DSOC CO2 SOC_corr [g] = CO2 measured [g] + DCO2 SOC [g] 3) Establish vehicle specific Willans linear equation from CO2 SOC_corr [g/h] and Pwheel [kW] per phase 4) Wheel power correction 4.1) deviation against target speed at times with power > ) deviations in road load settings at chassis dyno vs. target DCO2 [g] = k x DWwheel [kWh] CO2 v_corr [g] = CO2 SOC_corr [g] + DCO2 [g] 5) Distance correction: CO2 d_corr [g/km] = CO2 v_corr [g] / target distance [km] 6) Temperature correction: (different soak temperature): CO2 corr [g/km] = CO2 d_corr [g/km] x (1+ DCO2temp [%]/100)

January 20, 2014 Optional: detailed approach for SOC correction (instead of WLTP method) generate vehicle specific Willans line and calculate gradient of Willans line X-axis: 𝑃 𝑒𝑛𝑔𝑖𝑛𝑒_𝑝ℎ𝑎𝑠𝑒(𝑖) = 𝑃 𝑤ℎ𝑒𝑒𝑙_𝑝ℎ𝑎𝑠𝑒(𝑖) η 𝑝𝑜𝑤𝑒𝑟𝑡𝑟𝑎𝑖𝑛 + ∆𝑃 𝑎𝑙𝑡𝑒𝑟𝑛𝑎𝑡𝑜𝑟_𝑝ℎ𝑎𝑠𝑒(𝑖) η 𝑔𝑒𝑛 ∗η 𝑒𝑛𝑔−𝑔𝑒𝑛 With DPalternator……additional power at alternator due to SOC imbalance Y-axis: average CO2 per phase in [g per s] ~12% for WLTP If 𝑃 𝑤ℎ𝑒𝑒𝑙 ∗ η 𝑝𝑜𝑤𝑒𝑟𝑡𝑟𝑎𝑖𝑛 is lower than Poverrun, the work for battery charging is not CO2 relevant: (regenerative braking in alternator assumed as standard  electric energy is missing at times with positive engine power ) ∆𝑪𝑶𝟐= 𝑾 𝒅𝒊𝒔𝒄𝒉𝒂𝒓𝒈𝒊𝒏𝒈−𝒑𝒉𝒂𝒔𝒆 𝒊 − 𝑾 𝒄𝒉𝒂𝒓𝒈𝒊𝒏𝒈−𝒑𝒉𝒂𝒔𝒆 𝒊 ∗ 𝒕− 𝒕 𝒐𝒗𝒆𝒓𝒓𝒖𝒏 𝒕 𝜼 𝒈𝒆𝒏 ∗𝜼 𝒆𝒏𝒈−𝒈𝒆𝒏 ∗𝒌 𝑊 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔 = 𝑈 (𝑡) ∗ 𝐼 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔_(𝑡) 𝑑𝑡 𝑊 𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔 = 𝑈 (𝑡) ∗ 𝐼 𝑐ℎ𝑎𝑟𝑔𝑖𝑛𝑔_(𝑡) 𝑑𝑡 𝑡=𝑑𝑢𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑝ℎ𝑎𝑠𝑒 𝑡 𝑜𝑣𝑒𝑟𝑟𝑢𝑛 =𝑡𝑖𝑚𝑒 𝑤ℎ𝑒𝑛 𝑃 𝑤ℎ𝑒𝑒𝑙 ∗ η 𝑝𝑜𝑤𝑒𝑟𝑡𝑟𝑎𝑖𝑛 < 𝑃 𝑜𝑣𝑒𝑟𝑟𝑢𝑛 𝑘=𝑔𝑟𝑎𝑑𝑖𝑒𝑛𝑡 𝑜𝑓 𝑊𝑖𝑙𝑙𝑎𝑛𝑠 𝑙𝑖𝑛𝑒 Poverrun

SOC correction effect for vehicle # 1 (diesel engine)
January 20, 2014 SOC correction effect for vehicle # 1 (diesel engine) Comparison of the SOC correction method of WLTP draft with detailed approach. Small differences but detailed method would be much more complex for type approval Simple approach as outlined in WLTP is good option.

Coast down corrections
January 20, 2014 Coast down corrections

January 20, 2014 Current WLTP coast down corrections are validated (no reasons found to augment existing methods) wind correction: (stationary method)  in principle correct, but large: source of uncertainty vehicle weight correction:  physically sound, measured effect is somewhat larger (f1?) tyre temperature correction:  magnitude reproduced, despite doubts on physical soundness air pressure correction:  limitation to f2 somewhat doubtful (role f1?), but effect reproduced road slope:  1/T average yield appropriate correction for sloping tracks tyre pressure correction: is based on a particular tyre pressure  role of f1 (in “f0 + f1*v + f2*v2”) in the WLTP text could be reviewed

January 20, 2014 WP 210 Correction parameters and algorithms for road load determination No Parameter Method Comments R1 rotational inertia correction Weigh the wheels and tyres and use 60% of the weight as rotational inertia, compensate on dynamometer. The rest of the driveline (after transmission) has a limited contribution, effect may vary somewhat with rim sizes and wheel type (secondary effect). Inertia of wheels and tyres (separate tests): WLTP: “3% of unladen mass (UM=1201 kg)”  kg normal wheels: 38.0 kg (56% of wheel weight) 18” wheels: 54.4 kg (64% of wheel weight) theoretical arguments leads to 60% - 70% of wheel weight from coast-down to chassis dynamometer

January 20, 2014 WP 210 Correction parameters and algorithms for road load determination No Parameter Method Comments R2 tyre pressure correction The rolling resistance is corrected for difference between pressures by: f0final = f0test * (Ptest/Pset) Apply per tyre, average the result. Current WLTP text is based on specific case. No Parameter Method Comments R4 tyre label correction f0final = f0test*(RRCclass/RRCtest) Correct the actual tyre labels (Rolling Resistance Coefficients: RRC) back to the setpoint, or “class value” value, if RRCtest < RRCclass. Tyre aspects difficult to recover from vehicle tests: rely on tyre label testing for the appropriate corrections range in a single tyre label more than 10%  still a flexibility, to be corrected for. How to include f1 in rolling resistance corrections is under investigation.

January 20, 2014 WP 210 Correction parameters and algorithms for road load determination No Parameter Method Comments R10 air density correction r/r0 Use air pressure and water vapour pressure. (Water vapour pressure depends on relative humidity and temperature.) Partly included in WLTP, update with humidity. Air viscosity effects are ignored. water vapour 37.7% lighter than dry air humidity effect especially at high temperatures air density r varies slightly with humidity: maximal 37.7% x 7.3% = 2.7% difference of density water vapour content at 40o C P0 = 100 kPa T0 = 293 K r = r0 * (T0/T) * (P/P0) * (1.00 – 0.38 * (RH/100) * (Pvapour/P)) Pvapour[bar] = * /( T[C]) Antoine equation

Open issues, difficult to cover in simple corrections
January 20, 2014 Open issues, difficult to cover in simple corrections test track surface: large effect on rolling resistance (up to 24%) probably more so because of tyre tread and pressure difficult to correct for, road surface characteristics not known tyre pressure variations during coast down testing: (up to 15%) not fully fixed by conditioning (average: up 7% from ambient) can be controlled somewhat by intermediate driving/text execution variation in wind speed and direction during testing: (“gustiness”) wind has large effect  need for back and fro testing (a and b) small remainder of a and b average largely affected by minute-to-minute variations

January 20, 2014 preliminary results current status: final testing, reporting in progress thank you for your attention

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