Over-run Task Force: Improvement of test method accuracy EDEN-group meeting called by Statens vegvesen Vegdirektoratet Oslo, 25th of September 2015 Steven MICHELS Head of Fleet Testing Goodyear S.A.
History of the Over-run test The legislator wanted to characterize road wear caused by studded tires. • Overrun test method has been used since 1986 for determining the road wear of studded tires • Test method was developed by VTT • Many different test samples and materials were tested like cylindrical stones, various metals, asphalt mixture stones glued on epoxy plates • Granite of Kuru was chosen because its quality is very uniform and the crystal size is small. • The matrix-like surface was introduced to imitate the crushed stones used in asphalt mixture. • VTT studies found that the test correlates very well with actual road wear. • The test is done in real life conditions on a wet surface, representative of conditions while studded tires are used 2
Over-run test description 1 2 3 4 5 6 7 8 9a 9b � Repeat steps 1 to 6 3 � Issue report
Trafi study presented at EDEN meeting in 2014 There seems to be: systematic variation in averages systematic variation in deviation Random variation may exceed the confidence limits given in data Repeatability: 5 measurements in autumn 2014 Reproducibility: Individual over-run test results and the related 95% confidence limits in measurements taken in 2013 4 Reference: Variation in over-run test results based on measurements in 2013 – 2014, EDEN expert meeting in Helsinki, 27.11.2014 (Riikka Rajamäki, Trafi)
Mandate & Objective: One of the outcomes of the 2014 EDEN meeting in Helsinki was that Trafi invited all accredited laboratories to join a Task Force with the objective to further develop the accuracy of studded tires road wear testing . � recommendations to be submitted to Trafi by end 2016 5
Members All Laboratories currently accredited by Trafi as recognized experts for Stud Type approval are welcome to join the Task Force. Currently participating in this joint effort: • Tikka Spikes, Continental J Rautiainen, T Becherer • Nokian Tyres plc M Liukkula • BD Testing I Halén • TestWorld M Hilli • Goodyear S Michels • Trafi (observer) M Loponen 6
Potential sources of variation • Interpretation of current test method description & calculations • Repeatability of test itself: Total variation • Testing operation • Test conditions • Driving style Measurement Process variation system variation • Weighing precision • Reproducibility between different accredited laboratories • Stones Reproducibility Repeatability • Geometry • Origin • Influence of vehicle (Other sources might be identified during the test analysis) 7
Approach Increase repeatability • Reduce sources of variation • Increase total wear in order to reduce impact of variation Increase reproducibility • Identify discrepancies between test laboratories • Align recognized experts on test details that have, so far, not yet been described in the test procedure 8
Test plan Stage 1. A1 - Sample geometry: grove depth A2 - Sample geometry: grove width and block size A3 - Stone preparation and weighing Stage 2. B1 - Round Robin test B2 - Vehicle influence (propulsion type: FWD, RWD, 4x4) B3 - Different stone manufacturers B4 - Confirmation of A2 Stage 3. C1 - Influence of sprinkling the entire surface vs. samples only: coming up. Same test tire model used for entire test campaign 9
A1 – grove depth Geometries: Labra-0058 (5 mm grove depth, std dimension) K05 (3 mm grove depth) Labra-0058 K05 10
A1 – grove depth Average mass loss of normal stones was 1,043 g Average mass loss of K05 was 0,844 g ( 23.58% less, will be used as linking ratio later ) The lower wear of K05 was probably caused by the fact that block edges are less fragile when they are supported better. Test A2. Final result (average row wear) [g] 1.20 1.00 0.80 0.60 0.40 0.20 0.00 11 Labra-0058 K05
A2 – influence of test stone geometry Geometries: K05, K01, K03 (all with 3 mm grove depth) Objective is to verify the influence of the total edge length per sample 1 set of K05, 2 sets of K03, 2 sets of K01, 1274 mm total edge length, 1680 mm, 1800 mm, 144 corners 224 corners 360 corners 12
A2 – influence of test stone geometry edge length vs. mass loss 1.60 1.40 Link between mass loss, total edge length and number of 1800 1.20 1.35 corners? 1.00 1680 0.80 1274 0.93 0.60 0.82 Test A2. Final result (average row wear) [g] 0.40 1.80 0.20 0.00 1.60 1200 1300 1400 1500 1600 1700 1800 1900 1.35 1.40 edge length 1.20 number of corners vs. mass loss 1.60 1.00 0.93 360 1.40 0.82 1.35 1.20 0.80 1.00 0.80 0.60 224 144 0.93 0.60 0.82 0.40 0.40 0.20 0.20 0.00 100 150 200 250 300 350 400 0.00 13 K05 K03 K01 # of corners
A3 – Stone preparation and weighing Geometry: K05 Laboratory test - each laboratory performs the initial measurements, sends the stones to Lab E to over-run test. After Over-run test, Lab E sends the stones back to same laboratories to make the final measurements. 14
A3 – Stone preparation and weighing We found out that Lab D did not fill the oven with “dummy” stones, but only the 15 + 5 test stones. This practice was so far not specified in the test method description. The oven capacity should always be fully used. Any free places at the oven should be filled with wet “dummy” stones � Significant potential for increased reprodicibility. Test A3. Final result (average row wear) [g] 1.20 1.00 0.81 0.76 0.80 0.73 0.72 0.71 0.60 0.40 0.20 0.00 A B C D E ABCDE ABCDE Avg: 0.749 g 0.733 g Reproducibility: 0.073 g 0.033 g 15
B1 – Round Robin test Geometry: K05 Vehicle: VW Golf VII 1.4 TSI – manual gearbox 2 samples per laboratory 16
B1 – Round Robin test Lab D is watering the full track � Significant potential for improving reproducibility through test conditions alignment between Labs. This practice was so far not specified in the test method description. Test B1. Final result (average row wear) [g] 1.20 0.96 1.00 0.83 0.75 0.80 0.71 0.60 0.40 0.20 0.00 A B C D ABCD ABCD Measurement system variation: 0.234 g 0.152 g 17 Reproducibility: 0.198 g 0.088 g
B2 – Influence of test vehicle drive axle Geometry: K05 Vehicle type: FWD, RWD, 4x4 Test vehicle was the same during the 3 sessions (Toyota Hilux). Remark: During the 4x4 test, we were lacking K05 stones so only 1 of 5 sets was composed of K05 stones, the other 4 were std stones. Therefore, we applied a correction factor of 1.2358 (found during A1) to the 4 std sets. 18
B2 – Influence of test vehicle drive axle The propulsion type seems to influence the total mass loss. Propulsion type stdev (g) Test B2. Final result (average row wear) [g] 1.20 FWD 0.024 RWD 0.041 0.989 1.00 0.938 4x4 1 sample 0.845 0.831 4x4, using wear 0.028 0.80 ratio found in A2 0.60 0.40 0.20 0.00 19 FWD RWD 4X4 4x4 (A2 ratio)
B3 – Influence of test stone supplier Geometry: Labra-0058 (std stones) Material: Kuru grey granite Suppliers: 2 different suppliers Test vehicle: VW Passat Conditions: wet track Remark: 1 set of samples has been compromised and was therefore excluded from the data set. 20
B3 – Influence of test stone supplier • 4.3% difference between results from samples sourced from Lab A and from Lab B. • Wear appearance after visual inspection seems to be slightly different (size of lost grains). • Influence of test stone suppliers seems to be within normal test variations. Test B3. Final result (average row wear) [g] 1.20 1.099 1.053 1.00 0.80 0.60 0.40 0.20 0.00 21 Lab A Lab B
B4 – Influence of stone geometry Geometries: K01, K03 Confirmation of A2 2 sets of K01, 2 sets of K03, 1800 mm, 1680 mm, 360 corners 224 corners 22
B4 – Influence of stone geometry Link between mass loss, total edge length, number of corners and net surface? Data added to the A2 data set. mass loss vs. edge length Test B4. Final result (average row wear) [g] 1.80 1.60 1.61 1.40 1.60 1800, 1.48 1.20 1.40 1.00 1.20 0.96 0.80 1.00 1680, 0.94 1274, 0.82 0.60 0.80 0.40 0.60 0.20 0.40 0.00 0.20 1200 1300 1400 1500 1600 1700 1800 1900 0.00 K01 K03 edge length mass loss vs. net surface mass loss vs. number of corners 1.60 1.60 360, 1.48 1.40 1.40 2250, 1.48 1.20 1.20 1.00 1.00 0.80 0.80 2812, 0.82 3150, 0.94 224, 0.94 144, 0.82 0.60 0.60 0.40 0.40 0.20 0.20 0.00 0.00 1200 1700 2200 2700 3200 3700 100 150 200 250 300 350 400 23 net surface # of corners
Conclusions, 1/2 • A1: The grove depth of the samples seems to influence the mass loss. • A2: The grove width of the samples seems to influence the mass loss. • A3: Weighing operations seems to be consistent once details were aligned • B1: Reproducibility can be further improved through technical alignment and more specific description of test method. Potential source of variation still to be confirmed, ongoing. • B2: The propulsion system of the vehicle seems to influence the mass loss. • B3: influence of sample sourcing seems to be minor, to be continued. • B4: Confirmation of A2, link between mass loss and geometrical parameters of test samples 24
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