SherpaEngineering

Modelling- Simulation

TYPES OF MODELS

• analytical with knowledge models showing physical aspect and relationships,
• "automatics" with models designed for real time dynamic control, concerned more by the visible behaviour than the internal phenomena (black box).

• the analysis
• the design of the system
• the understanding of the phenomena
• development of models based on physics and addressing several domains such as thermo-fluid, mechanics, electricity, hydraulics
• development of models for digital dynamic control
• development of models describing sequential operations for managing the operating modes
   

SHERPA SERVICES

Development of multi-physics and multi-levels system models, models for dynamic control, models of sensors, actuators, physical models Plant tests analysis and pre-processing, model parameters estimation development of simulators and dedicated tools, user interfaces, data post-processing, steady state simulation, dynamic simulation Re-engineering of models Compilation of models on prototypes or industrial targets     Development of complex models   The way the knowledge is structured and the clearness of the models are important. The system model must be shared out with the different actors of a project. Thus, a multi-levels model is to be developed and it must be object-oriented in such a way a given system can be represented depending on the purpose.

Model parameters identification, plant tests analysis Complex non linear models have lots of parameters which can be sorted : dimensionnal or functionnal constants varaition law static or dynamic Objectives of the plant tests analysis and parameters estimation : Specify all the plant tests to be done Define and apply the methodology for data analysis Estimate the parameters and build the laws Validate the estimated parameters values

Analysis and estimation follow a procedure : Qualitative : validate or modify the structure of the model Quantitative : evaluate the parameters values and validate the numerical estimation Validation : evaluate the predictive capability of the model (sensitivity of the estimated parameters) Simulation and dedicated tools Sherpa builds specific simulation tools for making operations easy and friendly : Parametring the model components Simulation (graphical interface, configuration, exploitation of the simulation results) Plant tests analysis (comparison measured/simulated, data import/export, ...)   Re-engineering of models Integrating models into target machines

APPROACH : METHODOLOGIES & TOOLS

Steps of a modelling project General specifications of the model Analysis of the system and its environment Analysis of the operating conditions Selection of the physical phenomena to be modelled Description of the context iagramme Hierarchical splitting of the signals and multiport Choice of the modelling assumptions Definition of the cuasality Construction of the basic functions Building the components and sub-system library Integration of the model Parametring the model Functional validation of the generic model   Methodologies Multi-ports, Bond-Graph, ...   Tools MATLAB/SIMULINK  : ITISIM EES (thermodynamics) AMESIM

REFERENCES