Authors: J . Croes 1 , S. Iqbal 1 , A. Reveillere 2 ,

1. Multidomain modeling approach for energy analysis and redesign of production machinery applied to weaving looms Authors: J. Croes1, S. Iqbal1, A. Reveillere2, D. Coemelck3, B. Pluymers1, W. De roeck1, W. Desmet1 1: KULeuven 2: LMS Imagine 3: Picanol

2. Table of contents • Introduction • Description of the model • Losses in bearings & seals • Losses in cam & follower • Losses in 3D multibody mechanism • Model updating • Analysis • Multidomain modeling for redesign • Conclusions & future work

3. 1. Introduction Description of the system rapier wheel with gripper 3D mechanism cam&follower mechanism gearbox 3D mechanism

4. 1. Introduction System under investigation • High dynamic weaving machine • Strongly coupled modules • Losses in order of magnitude of kW Most dominant loss sources • Friction in bearings, seals, gears, cam&follower • Losses in electric motor Objective • Analysis of loss distribution in the system to improve the overall efficiency Requirements • Component loss models with reasonable level of accuracy • Accurate description of the dynamic behavior of the system

5. 2. Description of the model cosimulation cosimulation

6. 2. Description of the model 1. Losses in bearings & seals Bearing (seal) losses • Modeled as a friction torque in opposite direction of the velocity • Loss is estimated according to Palmgren or SKF model • Bearing loads come from contact in gear teeth, cam & joints • Implemented as an multidimensional loss map • Dedicated development of bearing component

7. 2. Description of the model cosimulation cosimulation

8. 2. Description of the model 2. Losses in cam & follower Cam & follower mechanism • Extension of existing cam rocker model with conjugate part • Linear stiffness behavior at cam & follower contact • Losses implemented and added at the cam shaft • Forces are defined as external variables • Loop is closed inside the submodel follower shaft cam shaft

9. 2. Description of the model 2. Losses in cam & follower Cam & follower mechanism

10. 2. Description of the model cosimulation cosimulation

11. 2. Description of the model 3. Losses in 3D multibody mechanism 3D mechanism • Model 3D kinematics(loads, velocities) • Rotation vectors change in magnitude and orientation • Need for multibody software • AMESim calculates friction torque • Modeled as equivalent inertia

12. 2. Description of the model 3. Losses in 3D multibody mechanism input output shaft AMESim • Post processing motion signals • Action points • Axis definitions • Joint definitions • Mind sign conventions • Discrete nature signals • Communication interval • Computation time • Tolerance • Step size loads, velocities of each shaft loss torque cosim block - radial load 1 - radial load 2 - axial load - velocity loss torque loads, velocities

13. 3. Model updating Use of two configurations to estimate & validate parameters configuration 2 α(2,2) α(2,2) T(1,2) T(1,2) configuration 1 ω(1,1) T(2,1) T(2,1) ω(1,1)

14. 3. Model updating Procedure Simulation Pre- and postprocessingr - Sensitivity analysis - Updating procedure - Runs with different parameters • Dominant parameters/components • - Stiffness & damping of the cam shaft • Bearing loss model • Motor loss map Dynamic behavior Energetic behavior

15. 3. Model updating Dynamic behavior Configuration 1: 500 RPM mean velocity

16. 3. Model updating Dynamic behavior Configuration 1: 600 RPM mean velocity

17. 3. Model updating Dynamic behavior Configuration 2: 500 RPM mean velocity

18. 3. Model updating Dynamic behavior Configuration 2: 600 RPM mean velocity

19. 3. Model updating Power measurements • Properties • Measurements linear regression between different temperatures • Viscosity exponential curve • Slope 34.4W/°C (config 1) vs 53.2W/°C (config 2) • Losses at 48.4° • Configuration 1 2% overestimation losses in the model • Configuration 2 20% underestimation losses in the model • Preliminary conclusions • Temperature (viscosity) has significant influence (lubrication assumption) • Increase of damping decreases the losses • Motor losses contribute to the slope increase

20. 4. Analysis Energetic analysis • Usage of the model to asses energy loss distribution • Gain insight in how dynamics/components influence energetic behavior • Use the model to formulate design guidelines

21. 4. Analysis Flow chart of energy losses

22. 5. Multidomain modeling for redesign • Virtual energy analysis leads to more insight in the most dominant loss sources and the most influential parameters 1: Lubrication properties highly influence the friction losses 2: Dynamic excitation is the main input for mechanical loss models Multidomain analysis allows you to quantify the losses! Provides a basis for experimental testing

23. 5. Multidomain modeling for redesign 1: Lubrication properties highly influence the friction losses Virtual experiments • Increase the oil temperature by 10° • 10% decrease in energy loss Physical experiments: • Increase the oil temperature by 3° • 3,8% decrease in energy loss • Reduce the oil flow by 60% • 10% decrease in power consumption • Increase of oil temperature by 6° • Increase and decrease of bearing temperatures by ±3.5° Lubrication regime can be optimized for energy consumption without jeopardizing performance & lifetime

24. 5. Multidomain modeling for redesign 2: Dynamic excitation is the main input for mechanical loss models Virtual experiments • Decrease equivalent inertia of the gearbox (scales with n²) • Reduces dynamic loads and by extension bearing friction

25. 5. Multidomain modeling for redesign 2: Dynamic excitation is the main input for mechanical loss models Virtual experiments • Increase damping on the main shaft by mounting damping layer • Significant reduction of dynamic forces • Dissipation caused by damper is small compared to the reduction in friction loss in the bearings by decreasing the load

26. 5. Multidomain modeling for redesign 2: Dynamic excitation is the main input for mechanical loss models Virtual experiments • Reassess cam profile • A smaller curvature radius leads to • Decrease in torsional vibrations • Lower rotational velocities at bearings • Decrease in rolling & sliding friction follower shaft cam shaft

27. 5. Multidomain modeling for redesign 2: Dynamic excitation is the main input for mechanical loss models Other virtual experiments can be • Assessing the effect of different bearings • Changing the load distribution to decrease the friction • Apply different topologies for some subsystems • Changing inertia’s & stiffness of specific components • …

28. 5. Conclusions & future work Conclusions • Dynamic and energetic behavior can be modeled using combined 1D/3D approach • Accurate estimation of dynamic behavior is necessary to estimate the losses • Representative loss models are required • Virtual energetic analysis provides good insight in the physical behavior and leads to a better design • Virtual experiments quantify the influence of redesign changes on the energy efficiency

29. 5. Conclusions & future work Future work • Model updating of loss behavior • Usage of the model to do a detailed analysis • Usage of the model to do virtual experiments for redesign