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Copyright © ESI Group, 2017. All rights reserved.
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Efficient safeguarding of elevator functionalities through virtual commissioning
ProSTEP iViP Symposium 2017
Bankolé Adjibadji, ThyssenKrupp Elevator Innovation GmbHJörg Arloth, Sales Manager, ESI ITI GmbH
17th May 2017
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Agenda
• Thyssenkrupp AG – Reinventing the elevator concept
• Elevator’s Product Performance Lifecycle
‣ Shorter development process through virtual prototypes• Model-in-the-loop strategy for control development• Hardware-in-the-loop strategy for elevator systems• One model - multiple benefits
‣ Validation of System Models against Field Data
‣ Outlook: Predictive Maintenance
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Rocking 100 years science & technology of elevatorsthyssenkrupp AG – Reinventing the elevator concept
Source: Keynote slides ProSTEP iViP Symposium 2016, Dr. Picard, thyssenkrupp AG
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Copyright © ESI Group, 2017. All rights reserved.
Rocking 100 years science & technology of elevatorsthyssenkrupp AG – Reinventing the elevator concept
Source: Keynote slides ProSTEP iViP Symposium 2016, Dr. Picard, thyssenkrupp AG
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Copyright © ESI Group, 2017. All rights reserved.
Elevator’s Product Performance Lifecycle
Model System Behavior
Model System Behavior
Model Faults and System Performance
Loss
Model Faults and System Performance
Loss
fault in torque generator
Compare Field Data to Faulted System Model
Compare Field Data to Faulted System Model
Diagnose System Fault and Prioritize
Maintenance
Diagnose System Fault and Prioritize
Maintenance
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Copyright © ESI Group, 2017. All rights reserved.
Elevator’s Product Performance Lifecycle
Model System Behavior
Model System Behavior
Model Faults and System Performance
Loss
Model Faults and System Performance
Loss
fault in torque generator
Compare Field Data to Faulted System Model
Compare Field Data to Faulted System Model
Diagnose System Fault and Prioritize
Maintenance
Diagnose System Fault and Prioritize
Maintenance
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Model System Behavior
Model System Behavior
Model Faults and System Performance
Loss
Model Faults and System Performance
Loss
fault in torque generator
Compare Field Data to Faulted System Model
Compare Field Data to Faulted System Model
Diagnose System Fault and Prioritize
Maintenance
Diagnose System Fault and Prioritize
Maintenance
Elevator’s Product Performance Lifecycle
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Shortening the development process through virtual prototypes
Virtual Controller+
Virtual Elevator
‐ detailed models‐ consideration of
multiple effects‐ test of new control
algorithms
‐ real‐time models
‐ test of the real controller (software & hardware)
Real Controller+
Virtual Elevator
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Model-in-the-loop strategy for control developmentShorter development process through virtual prototypes
• Mechanics
• Safety engineering
• Electrical machineand power electronics
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Hardware-in-the-loop strategy for elevator systemsShorter development process through virtual prototypes
HiL SimulationIntegration
AccessDownload
Modeling
Configure
Connect
ImportExport
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One model - multiple benefitsShorter development process through virtual prototypes
• Frontloading‣ Early and efficient specification of control strategies for offline
modelling and functional tests (MiL)
• Collaboration‣ Standardized model exchange based on Functional Mock-up
Interface (FMI)
• Consistency‣ Representation and re-use of existing know-how within an
application specific elevator library incl.• Consideration of physical interactions and safety-critical effects• Reduction of model‘s level of detail to ensure real-time capability
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Data visualization and analysis based on machine learning algorithms
Validation of System Models against Field Data
PPLProduct Performance Lifecycle
Math models
VR/ARData Analytics
IVEImmersive Virtual Engineering
• ROMESA ‐ Robustness and Reliability Simulation of Mechatronic Systems including Aging and Wear (BMBF Förderprojekt, KMU innovativ) ‣ simulation of wear and age – information feed
back for planning of life cycle tests‣ Embedded simulation using FMI for speed up of
virtual life time tests
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Outlook towards Predictive MaintenanceUser story for consistent workflow
• Specification‣ Early, efficient an complete modelling of the systems behavior incl. all physical
interactions and controllers• Virtual testing
‣ Successful integration of FMU into existing real time environment taking all relevant phenomena into account (Co-simulation is numerically stable)
• Fault Analysis‣ Set up scenarios for fault injection and dependability analysis to ensure functional safety
according to ISO 26262 for interaction between controller and physical system.• Predictive Maintenance
‣ Comparison of real vs. ideal or faulted behavior (e.i. field data vs. simulation model) using machine learning algorithms
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Let’s talk about chal lenges and chances!
Jörg ArlothSales Manager ESI ITI ESI ITI GmbH | Schweriner Str. 1 | 01067 Dresden | Germany
Direct: +49 351 260 50 160Celular: +49 173 3194650 Email: [email protected]
