AMESim ®

OVERVIEW ON MODELING OF THERMO-FLUID SYSTEMS

25 the performances from external factors as air inlet temperature, it also does not allow to assess dynamic responses.

Another aspect to be considered is that Trnsys^® standard libraries are more focused on HVAC systems for building applications rather than for power generating systems, which are the focus of the present work.

Trnsys^®, while being a good tool for assessing the long term overall energy fluxes that involve heating and cooling applications to building systems, does not however appear to be the proper tool when it comes to component design and also the libraries available are not indicated for power systems design, which is the main topic of interest for the present work.

CHAPTER TWO

26

In doing so AMESim^® refers to the set of equations defining the dynamic behaviour of the engineering system and its implementation as computer code that is the model of the system. The model is built up from equations and corresponding code is referred to as submodels. Once all the procedure for creating the model of a physical system is completed, AMESim^® through the use of a proper compiler, produces the executable file of the system and produces a .exe file to run the simulation.

Two compilers may be used with AMESim^®: Microsoft^® Visual C++ and the GCC compiler. GCC is under the GNU general public license.

Fig. 2.6. The structure of an AMESim simulation program.

When a simulation using AMESim^® is performed, computer code is generated which is specific for the engineering system created. At the core of AMESim^® is an integration algorithm, which advances the solution through time. This integration algorithm calls the submodels, which are associated with the components of the system, as shown in Fig. 2.6. These submodels may have been selected by AMESim^® automatically or selected manually by the user. In either cases there will be computer code, which implements the mathematical equations on which the submodel is based. The order in which the submodels are called is not normally the same as the order in which the corresponding components were added to the sketch. The submodels are sorted into an order that is more efficient from a computational point of view.

During a simulation some quantities change with time. Typical examples are the pressure in a pipe and the rotary speed of a load. These quantities are called variables. Sometimes in a particular simulation, they are constant but, since in principle they could vary with time, they are still called variables. Other quantities are always fixed during a simulation run. These are called parameters and these quantities normally indicate a size or dimension of a component. Examples are the diameter of a pipe and mass of a body connected to a spring.

AMESim^® delivers a 1D simulation platform which addresses multiple domains in an integrated simulation process and accurately predicts the multi-disciplinary performance of intelligent systems. The components of the model are described by analytical models representing the hydraulic, pneumatic, electric or mechanical behavior of the system. Dedicated libraries and application-specific solutions eliminate the need for extensive modeling and deliver simulation capabilities to assess the behavior of specific subsystems in multiple physical domains.

Therefore, to create the system simulation model AMESim, the user can access to a large set of validated libraries of pre-defined components from different physical domains such as fluid, thermal, mechanical, electromechanical, powertrain and many others. The software creates a physics based model

OVERVIEW ON MODELING OF THERMO-FLUID SYSTEMS

27 of the system, which does not require a full 3D geometry representation. This approach gives AMESim the capability to simulate the behavior of intelligent systems long before detailed CAD geometry becomes available.

Among the many standard libraries provided, the following embody components that may result of interest for the applications considered in the present work:

Internal Combustion Engine Solutions: this library, developed by French research center IFP, allows users to model and design comprehensive engine systems based on physics-based model components, from air management and combustion up to ECU calibration. These provide a flexible environment for designing and optimizing “virtual” engines and the couplings with subsystems for fuel injection, fuel diversification, thermal management (i.e. for cogeneration purposes), etc. can be studied.

Thermal Management Solutions: provide dedicated component libraries to build and analyze complete thermal management models in a single environment. The solutions enable the processing of real transient, multi-domain simulations and the handling of heat management scenarios. The Thermal Management Solutions give engineers access to detailed models of sub-systems in vehicle thermal management sub-systems (engine cooling sub-systems, air-conditioning, lubrication system, etc.). This enables them to accurately define and size components, and to study the overall system integration and the interactions between subsystems.

Fluids Systems Solutions: Using physics-based simulation, the Fluids Systems Solutions enable engineers to design complete fluids hydraulic and pneumatic systems, from the sources (e.g. the fuel tank) to the consumers (e.g. actuators) up to the fluid network.

Energy Systems: Energy Systems Solutions provide advanced libraries and toolsets to handle specific thermodynamic applications, like aerospace propulsion and pyrotechnics, fuel cells and batteries. The solution come with a set of specific tools and libraries dedicated to thermodynamics, gas mixtures, fluid properties, thermochemistry, and compressible flows.

When custom blocks are required for specific applications AMESet provides a set of tools to extend the standard AMESim^® libraries of components. AMESet in fact is designed to assist users in writing standardized, reusable and easily maintainable libraries of component models that are fully compatible with the existing AMESim^® models and are automatically usable on each supported platform.

Producing new submodels involves writing code that must be in the correct format to allow AMESim^® to call it. AMESim^® submodels must be written either in the programming language Fortran 77 or C. A specific tool is also provided in order to help the user compiling and debugging the source code to meet the AMESim^® syntax requirements.

To be also noted that AMESim^® offers extensive interfaces with third-party software tools for control, real-time simulation, multi-body simulation, process integration and design optimization. Of particular interest for the scope of present Work is the capability of interface AMESim with Matlab scripting language or to Simulink^® for control applications.

For example it is possible to use Matlab^® for the control of simulation experiments of an AMESim^® model. Batch simulations can also be performed from Matlab^® where specific scripts can allow producing series simulations of AMESim^® model with a set of predefined design parameters. Other possible usage includes more advanced sensitivity analysis, optimization of parameters in the simulation model, etc.

CHAPTER TWO

28

The AMESim^® integrators provided can be divided into two types:

variable step, variable order methods with control of errors;

fixed step, fixed order methods with no error control.

Fixed step fixed order methods are much less robust and flexible than the variable step variable order methods. The equations governing the model must be explicit in this case. In other words there must be no constraints or implicit state variables.

Common problems that may arise during simulation of engineering systems are stiffness or due to discontinuities. A stiff problem is one in which there is a time constant which is extremely small compared to the simulation time range.

Another common problem is discontinuities. These are points at which there is a switch from a set of one or more governing equation(s) to another completely different set.

AMESim^® has developed specific procedures to tackle these problems during the integration of the solving differential equations.

Simple Runge-Kutta algorithms commonly adopted are relatively tolerant of discontinuities and can perform well on some problems but they are very unsuitable for stiff problems. However, many simulations are performed on stiff problems rich in discontinuities using these methods. The standard AMESim^® integrator does not give the user a choice of integration algorithm. Instead the characteristics of the equations governing the model are used to select automatically the most appropriate algorithm. If the model contains any implicit variables the differential algebraic equation integration algorithm (DASSL) is used otherwise the ordinary differential equation integration algorithm (LSODA) is used.

AMESim^® is therefore a general, multi-purpose icon based software which encloses some very advanced tools as optimization, linearization, customization and proper solution integration that allow great flexibility and significant simulation potentials.

In Fig. 2.7 The AMESim^® model of a CI ICE is presented. The model has been created by gathering different components representing the different parts of the real engine (turbocharger, manifolds, combustion chamber, injectors, etc ...) coming from the Authors own developed AMESim^® Engine Library (IFP-ENGINE library [17]), which is now part of the AMESim^® environment. This engine-dedicated library allows computing a complete virtual engine with a characteristic time-scale of the order of the crank angle. In each component, a 0D/1D model dedicated to the physical phenomena at stake is used, the aim being to perform simulations with particular respect to the dual mode combustion (conventional and HCCI). For this reason the combustion model is one of the most important sub-models and the 0D sub-model developed in the standard IFP-engine library, based on Chmela’s model, and has been considered with specific additional developments by the Authors; particularly the standard model was modified in order to take into account both auto-ignition delay and pre-mixed/cold flame combustion.

This phenomenological model is a dual mode combustion model, that is to say it is able to represent both HCCI and conventional combustion.

Such a model needs to be calibrated, so its parameters need to be estimated in order to obtain the best behaviour possible of the model when confronted with a wide range of operating conditions. Given the high number of parameters to estimate the calibration procedure is very time consuming and complex. An automatic calibration tool, dedicated to the enhancement of phenomenological modelling of Diesel combustion therefore has been developed capable of dialoguing with the AMESim^® based engine model.

OVERVIEW ON MODELING OF THERMO-FLUID SYSTEMS

29 This example of application of the AMESim^® standard libraries, with custom components where some modifications have been introduced in order to be able to take into proper account of certain phenomena of interest, demonstrates the significant capabilities of the software suggesting therefore that the software might have been an appropriate tool, alternative to Matlab^®/Simulink^® for the development of the energy systems models proposed within the present work.

Fig. 2.7. Turbocharged automotive Diesel engine model in AMESim^® [17].