Predicting the mobility of tracked forestry machines operating on Nordic forest soil

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Predicting the mobility of tracked forestry machines operating on Nordic forest

soil

Natchammai Revathi Palaniappan, A. Pirnazarov, U. Sellgren, B. Löfgren

Forest Machine Technology Academy, KTH

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Agenda

• Background

• Purpose

• Division of the project task

• Delimitations

• Terminologies

• Field test data

• Comparative study of tracked and wheeled forest machines

• Conclusion

• Future Work

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Background

• Performed as a Master thesis project at KTH

• Cut-To-Length Method

• Two machine solution (harvester and forwarder)

• Development of machines gentler to the ground

• Trial and error method

• Expensive due to changing demands

• Track soil interaction model

• Complex and difficult to model

• Development of empirical models by WES

• Aimed at preserving the productivity of the soil

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Purpose

• To contribute to the existing knowledge in the field of track-soil interaction.

• Study the vehicle performance

• Understand the effects on the environment

• Tracked vehicles vs. wheeled vehicles

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Division of the project task

1. Calculate ground pressure, performance parameters, rut depth for tracked and wheeled vehicles. Compare results.

2. Study the field test data and theoretical model results to find out how efficiently the measured data match with the real data.

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Delimitations

• Entire focus is on soft soil – Uplands Sandy Loam, Rubicon Sandy Loam and North Gower Clayey Loam

• Limited to the use of three types of rigid steel tracks (ECO, EVO and MAGNUM)

• The roots present in the soil bed are not considered for the analysis.

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Terminologies

• Rutting • Ruts are formed due to repeated heavy vehicle passes along the

same path.

• Rutted area becomes too wet due to water logging.

• Soil compaction • Physical degradation of the soil.

• Porosity, permeability and biological activity is reduced.

• Risk of soil erosion.

• Ground bearing capacity • Ability of the soil to carry the pressure exerted on it without

undergoing shear.

• Mobility • Quality or capability of the machine which permits them to move

from place to place. 7

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Field test data analysis

• Performed in Tierp, Sweden in 2011

• Komatsu 860.3

• Three types of tracks – Eco, Evo and Magnum

• Soil composition

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• Ground pressure measurement

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• Soil penetration test

• Cone penetrometer

• Straight and S-curved trails

0.00

0.50

1.00

1.50

0 5 10 15 20

Pe

ne

trar

tio

n r

esis

tan

ce, M

Pa

Penetration depth, cm

Komatsu 860.3, Eco-Magnum, straight (loaded)

1st pass

10th pass

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

0 5 10 15 20 25 30 35 40

Pe

ne

trat

ion

res

ista

nce

, MP

a

Penetration depth, cm

Komatsu 860.3, Eco-Magnum, S curve (loaded)

Curve

Straight

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• Rut depth measurement

• Increases with the increase in load and number of passes.

• Large differences in the rut between S curve and straight path

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

Pass 1 Pass 2 Pass 3 Pass 4 Pass 5 Pass 8 Pass 10

Ru

t d

ep

th, c

m

Number of passes

Komatsu 860.3, Eco-tracks

Straight, loaded

Straight, unloaded

Slalom, loaded

Slalom, unloaded

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Comparative study of tracked and wheeled forest machines

• Ground pressure

• WES mobility models

• Performance parameters

• Rut depth analysis

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• Ground pressure

• Reasonably low values for Nominal Ground pressure (NGP)

• Almost all the models show a lower ground pressure for the tracked vehicles.

0 200 400 600 800

Eco

Evo

Magnum

Ground pressure, kPa

Ground Pressure Models, Tracks

Maclaurin

Littleton

Rowland

NGP

0 100 200 300 400 500 600 700 800

NGP

Rowland, Cross country

Rowland, Conventional

Larminie, Fine grained

Larminie, Coarse grained

Maclaurin

Ground Pressure, kPa

Ground Pressure Models, Tires

Tires

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• WES Mobility model

• Mobility index (MI) and Vehicle Cone Index (VCI)

• VCI – minimum strength of the soil in the critical layer which permits the vehicle to make a specific number of passes.

• A low VCI value for the tracked vehicles indicate that they can traverse on the low strength soils better than the wheeled vehicles.

0 2000 4000 6000 8000

ECO

EVO

Magnum

Tires

kPa

Mobility Index and Vehicle Cone Index

VCI 50 passes

VCI 1pass

MI

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• Based on Bekker’s pressure sinkage model

• Shear displacement

• Tractive effort

• Drawbar pull

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• Shear displacement

0 0.5 1 1.50

0.2

0.4

0.6

0.8

1

1.2

1.4

distance from the front of the contact area,m

shear

dis

pla

cem

ent,

m

SHEAR DISPLACEMENT DUE TO TRACKS

slip-10%

slip-20%

slip-40%

slip-60%

slip-80%

0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

theta, radians

shear

dis

pla

cem

ent,

m

SHEAR DISPLACEMENT DUE TO Tires ON USL

slip-10%

slip-20%

slip-40%

slip-60%

slip-80%

Tracks Tires 16

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• Tractive force

• Tractive force – Force at the contact between tires/tracks and road.

• Traction-Maximum amount of force the tire can apply against the ground.

0

50

100

150

200

250

10 20 40 60 80

Trac

tive

eff

ort

, kN

Slip, %

ECO tracks, Thrust vs Slip

USL

RSL

NGCL

0

5

10

15

20

25

30

35

40

45

50

10 20 40 60 80

Trac

tive

forc

e, k

N

Slip, %

Tires, Thrust vs Slip

USL

RSL

NGCL 17

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• Drawbar Pull

• Pulling ability of the vehicle.

• Drawbar pull at 20 % slip is usually used as a major performance parameter for comparison because the operating efficiency at a slip of 20 % is generally satisfactory.

0 20 40 60 80 100 120

10

20

40

60

80

Drawbar pull, kN

Slip

, %

Drawbar pull on Rubicon Sandy Loam

Tires

Magnum

Evo

Eco

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• Rut depth analysis

• Willoughby and Turnage

• Single pass rut depth models

• Multi-pass rut depth models

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• Willoughby and Turnage model

1 2 3 4 5 6 7 8 9 100

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

Number of passes

sin

kage,m

WES sinkage model, Evo tracks

evo-loaded-measured

evo-loaded-predicted

evo-unloaded-measured

evo-unloaded-predicted

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Predicted values follow the profile of the measured values better in the case of tracked vehicles than wheeled vehicles.

1 2 3 4 5 6 7 8 9 100

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Number of passes

sin

kage,m

WES Sinkage model, tires

tire-loaded-measured

tire-loaded-predicted

tire-unloaded-measured

tire-unloaded-predicted

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• Single pass rut depth models (Straight Loaded)

22 1 2 3 40

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09First wheel pass-Straight loaded

1,2,3,4 - Eco, Evo, Magnum, Tires

Rut

depth

, m

Antilla(1998)

Saarilahti(1997)

Saarilahti & Antilla(1999)

Rantala(2001)

Test data

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• Single pass rut depth models (Straight unloaded)

23 1 2 3 40

0.01

0.02

0.03

0.04

0.05

0.06

0.07First wheel pass-Straight unloaded


Rut

depth

, m

Antilla(1998)

Saarilahti(1997)


Rantala(2001)

Test data

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• Single pass rut depth models (S-curve loaded)

24 1 2 3 4

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09First wheel pass-S-curve loaded


Rut

depth

, m

Antilla(1998)

Saarilahti(1997)


Rantala(2001)

Test data

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• Single pass rut depth models (S-curve unloaded)

25

1 2 30

0.01

0.02

0.03

0.04

0.05

0.06

0.07First wheel pass-S-curve unloaded

1,2,3,4 - Eco, Evo, Tires

Rut

depth

, m

Antilla(1998)

Saarilahti(1997)


Rantala(2001)

Test data

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22 24 26 28 30 32 34 36 380

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08regression analysis for Saarilahti(1997) model

Nci

Rut

depth

in m

7 7.5 8 8.5 9 9.5 100.02

0.025

0.03

0.035

0.04

0.045

0.05

0.055regression analysis for Saarilahti(1997) model

Nci

Rut

depth

in m

a b

a b a b

Antilla (1998) (-0.001) 0.248 (-0.0061) 0.8060 (-0.0187) 0.366

Saarilahti (1997) 0.108 0.76 1.553 1.27 1.003 1.74

Saarilahti & Antilla(1999) 0.023 0.256 (-0.0082) 1.08 (-0.025) 0.491

Rantala (2001) 0.989 1.23 2.08 1.27 1.344 1.741

OriginalSource Model

Tracks

Estimated

Tires

a b

a b a b

Antilla (1998) (-0.001) 0.248 (-0.0061) 0.8060 (-0.0187) 0.366

Saarilahti (1997) 0.108 0.76 1.553 1.27 1.003 1.74

Saarilahti & Antilla(1999) 0.023 0.256 (-0.0082) 1.08 (-0.025) 0.491

Rantala (2001) 0.989 1.23 2.08 1.27 1.344 1.741

OriginalSource Model

Tracks

Estimated

Tires

Tracks Tires

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• Multi-pass rut depth models

• After Abebe’s model

• (Multi-pass coefficient)MPC should lie within 2-3

• For vehicle pass of 1, 2,3…, the wheel pass is 4,8,12…

1

1a

nzz n

0 5 10 15 20 25 30 35 400.04

0.05

0.06

0.07

0.08

0.09

0.1

0.11

0.12

0.13magnum loaded-slalom

Number of wheel passes

Rut

depth

1 2 3 4 5 6 7 8 9 100.04

0.05

0.06

0.07

0.08

0.09

0.1

0.11

0.12

0.13magnum loaded-slalom

Number of vehicle passes

Rut

depth

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Conclusion

• Ground pressure

• Tracks seem to have a lower ground pressure compared to tires

• WES mobility index

• MI and VCI values for tracks are very much lesser than the values for tires.


• Thrust force and drawbar pull is higher for the tracked vehicles in comparison to the wheeled vehicles which indicate that the tracked vehicles operate much better on these types of soils than the wheeled vehicles.

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• Rut depth

• The existing models were developed for specific vehicle conditions and soil conditions. Though the rut depth test data didn’t match very well with the existing models, they didn’t deviate so much either.

• Rut depth values can be related to the WES models.

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Future work

• FEM analysis could be done to see how much the track sinks and how the pressure will be distributed beneath the tracks.

• In depth analysis on the position and size of the grouser could be made.

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Thank you

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