Pinna

PSi Theme 9
Cradle-to-Grave Life Cycle Prediction of Automotive Materials &
Systems in Service: Impact of Ageing on Performance
Sheffield: Dr Christophe Pinna, Prof. David Wagg, Prof. Lenny Koh, Prof. Neil Hopkinson, Prof. Alma Hodzic
PDRAs/PhD students: Dr Payam Soltani, Dr Seyed Ebrahimi, Dr Andrew Timmis,
Dr Allison Beck, Mr Lizhe Wang, Ms Cariad Wright
Manchester: Prof. Costas Soutis (PI), Prof. Xiaorong Zhou, Prof. Phil Withers
PDRAs/PhD students: Dr Clara Frias, Dr Mazher Yar, Dr Ying Wang,
Mr Alejandro Perez Hernandez
JLR lead: Elliot Hemes
1
Programme for Simulation Innovation
Raw material extraction
End of Life
End of Life
Materials
processing
Ageing
models
Manufacturing
Use
Programme for Simulation Innovation
Effect of ageing on customers’ experience
e.g. suspension spring
Material degradation over
time due to corrosion
Change in Spring
stiffness
Change in the dynamic
response of the car
Programme for Simulation Innovation
Modelling ageing
Applied
&&
AppliedLoads
Loads
Environments
Environments
(Probabilistic)
(Probabilistic)
Physics-based
Multi-scale
‘age-aware’ Models
Applied Loads
&
Geometry
& Material
Environments
Data
(Probabilistic)
(Probabilistic)
Applied Loads &
Structural Dynamic
Environments
Response & Reliability
(Probabilistic)
(Probabilistic)
Programme for Simulation Innovation
Three Use Cases
Suspension springs
Engine mounts
Instrument panel
Metals
Elastomers
Polymers
Programme for Simulation Innovation
Spring corrosion characterisation (Yar, Zhou, Wang, Soutis)
Spring compression test
Pits on the surface
Sub-surface pits
Corrosion (optical)
3D X-Ray CT image
Programme for Simulation Innovation
Spring corrosion modelling (Wang, Soutis)
Sub-model
Corrosion products
Corrosion through
the thickness
Fe2+ + 2OH → Fe(OH)2
4Fe(OH)2 + 2H2O + O2 → 4Fe(OH)3
Programme for Simulation Innovation
Engine Mount testing (Soltani, Pinna, Wright, Hopkinson, Hodzic)
Rubber
Cracks in rubber
over time
DMTA
Frequency: 1-100Hz
Elastomer stiffness
Programme for Simulation Innovation
Elastomer modelling (Soltani, Pinna)
Engine mount stiffness variation
due to ageing
Digital
Image
Correlation
Strain measurements
Programme for Simulation Innovation
Dynamic analysis (Soltani, Wagg)
Stiffness
DMTA
Data
(elastomer)
Damping
Instable regions for force and frequency due to ageing
(non-linear variation of stiffness with temperature)
Programme for Simulation Innovation
Life cycle customer prediction (Timmis, Ebrahimi, Koh)
Objectives
• Integrate the quantitative modelling of material
ageing with the subjective and qualitative
aspects of drive experience
Approach
• Life cycle assessment – 3 use cases
• Customer interviews and surveys
Outputs
• New ‘customer orientated’ understanding and
modelling of material ageing
• Advances of ‘life cycle thinking’ as a decision
support tool
Programme for Simulation Innovation
Customer
acceptability
Performance
But…
• What do we define as end of life for our components?
Mechanical failure
Time
Programme for Simulation Innovation
Quantitative
Materials ageing
modelling
(WP1 and WP3)
Qualitative
Life cycle
assessment
(WP5)
Dynamic
modelling
(WP4)
‘Life cycle thinking’ decision support tool
Customer insights
(WP5)
Programme for Simulation Innovation
Acknowledgements
- EPSRC/JLR funding: grant EP/L025752/1
- Jaguar Land Rover PSi team: I. Knight, R. Whear, M. Nielson, N.
Ionas, M. Blagdon, R. Cambray, A. Tarpey, S. Blundell, M.
Walters