Estimation of wheel-rail friction at

vehicle certification measurementsNordic Seminar on Railway Technology, 2016Márton Pálinkó, Mats Berg, Lars Andersson

Contents

1. Introduction

2. Background

3. Methodology

4. Results

5. Conclusions

6. Further work

2

Introduction

• Increased rail traffic, increased requirements on vehicles

• Wheel-rail friction is an important question at vehicle

certification tests

• The friction should be high according to EN 14363

• The measurement at operation is not possible

• Gives an insight to other phenomena

• Algorithm for estimation (Petrov et al.) applied to test data

• Cooperation between KTH and SNC Lavalin

3

Background - Forces in operation

Steel-on-steel force transmission

Contact area - slip, called creep in rail operation

Creep forces/moment

• Longitudinal (𝑋 = 𝑇𝑥) – Traction/braking, curves

• Lateral (𝑇𝑦) - Curves

• Spin - Curves

4

Background – Coefficient of friction (CoF)

The estimated friction (used):

Friction attributes:

• Limit to the transmittable forces

• Smaller than for road traffic

• Condition – dependent

Creep and spin monitored for correlation

5

Background – Creep equations

The longitudinal creep:

The lateral creep:

The spin:

6

Background - Certification tests

• Dynamic tests according to EN14363

• Different track attributes

• IWT4 technology by SNC Lavalin (Interfleet)

• A total of 3 runs in an S – curve of 150 meter radius

7

Background - Certification tests

Quantities of interest

• Forces (Q, X, Y)

• Lateral contact point position (Lcpp)

• Angle of attack (AoA)

8

Methodology

• Matlab environment

• Low pass filters of 20/10 Hz for forces/AoA and 5/2 Hz Lcpp

• Instantaneous values of coefficient of friction,

total creep and spin

• Statistical analysis for better estimation

• Possibility to put errors into the system – Sensitivity analysis

9

Results – Test 1

• Smoothest behavior - Peaks are observable

• Both parts of the S-curve show normal behavior

Time [s]

Coefficient of friction Total creep Spin

10

Results – Test 1A

Statistical tool:

• Moving average with 5 meter window and 1 meter for deviation

11

Results – Test1A

Coefficient of friction against the total creep

Instantaneous Moving averaged (5m)

Total creep Total creep

Coeffic

ient

of F

riction

12

Results – All tests – Inner wheel

• The overall mean of the moving average for different filters

• CoF – Force and Lcpp dependent

• Constant total creep – mostly dependent on angle of attack

• 20/5 Hz fiter combination is adequate

13

Results – All tests – Inner and outer wheel

• Outer wheel gives lower estimate

• Total creep stays fairly constant

• Increasing coefficient of friction with the tests

14

Results – Sensitivity analysis – Inner wheel

• Angle of attack effects the creep

• Only calculating with the curve gives a big difference

• CoF does not vary significantly – straight cone of the

wheel most of the time instances

15

Results – Sensitivity analysis – Outer wheel

• Significant variation in CoF value – Lcpp error approx. +/- 6 mm

• Effects can be decoupled:

• AoA - linear, Lcpp - proportional to the wheel profile curve -

fairly linear on the tread, nonlinear reaching the flange part

16

Conclusions

17

Conclusions

• In tight curves the friction cannot be estimated on the outer

wheel – minimum

• T/N at small contact angle has to be high

Tight curves

Traction/braking

Irregularities – only for small time interval

• Above a certain spin, the algorithm overestimates the friction

• Around zero spin and around this limit, good estimation

• High creep – not a quality factor in this case

18

Further work

Other available test to be included to prove the conclusions -

With different attributes like:

• Varying curves with radii down to 400 meter

• High speed for higher dynamic effects

• Various tracks with real-life irregularities

Challenge: good estimation of bogie rotation as the angle of

attack is not available

19

Thank you for the attention!

20