Table of Contents

Cover

Foreword

1 Role of Simulation in the Design Cycle of Complex Technological Systems

1.1. Approach to the design of complex systems
1.2. Book objectives and content

2 Fundamental Concepts of Lumped Parameter-Based Multi-Physics Modeling

2.1. Definition and modeling levels of mechatronic systems
2.2. Modeling of mechatronic systems with lumped parameters
2.3. Multi-physics modeling of a power window system
2.4. Revision exercises and multiple-choice questions
2.5. Problems

3 Setting Up a Lumped Parameter Model

3.1. Introduction to the notion of adapted model
3.2. Identifying the main effects
3.3. Modeling approaches and selection of adapted models
3.4. Introductory exercises related to setting up models with lumped parameters
3.5. Problems related to the choice of modeling level

4 Numerical Simulation of Multi-Physics Systems

4.1. From mathematical model to numerical model
4.2. From numerical model to computer simulated model
4.3. Simulation: numerical resolution of ODEs
4.4. The main sources of error in modeling and simulation
4.5. Revision exercises
4.6. Problem

5 Dynamic Performance Analysis Tools

5.1. Dynamic performance indicators
5.2. Laplace transform and transfer functions
5.3. Stability of linear dynamic systems
5.4. Analysis of first- and second-order systems. Model reduction
5.5. Revision exercises

6 Mechanical and Electromechanical Power Transmissions

6.1. Introduction
6.2. Variational approaches
6.3. Modeling by direct integration of local laws: bulk and multi-layer ceramics
6.4. Principle of virtual works: amplified actuators
6.5. Energy and co-energy balances: bimetals
6.6. Lagrange equations: Langevin transducers
6.7. Introductory exercises
6.8. Modeling problems

7 Power Transmission by Low-Compressibility Fluids

7.1. Fluid power
7.2. Presentation of a helicopter actuation system
7.3. Minimal fluid modeling according to the phenomena involved
7.4. Modeling of the various physical phenomena
7.5. Modeling of the main hydraulic components
7.6. Simulation of a helicopter actuation system
7.7. Exercises and problems

8 Heat Power Transmission

8.1. Heat exchangers
8.2. Effectiveness-based thermal modeling of heat exchangers. Constant effectiveness
8.3. Estimation of the heat exchanger effectiveness
8.4. Estimation of the global heat transfer coefficient of a heat exchanger
8.5. Estimation of the pressure drops (losses) in the heat exchangers
8.6. Revision exercises and problems

9 Thermal Power Conversion

9.1. Several examples of heat engines
9.2. Behavior of compressible fluids
9.3. Thermodynamics review
9.4. Modeling of the components of heat engines
9.5. Simulation of a thermal power plant
9.6. Revision exercises and problems

References

Index

End User License Agreement

List of Tables

Chapter 2

Table 2.1. Modeling levels
Table 2.2. Elementary effects in 0D/1D modeling
Table 2.3. Variables and elements by physical domains
Table 2.4. Multiple choices corresponding to Figure 2.18
Table 2.5. General characteristics of the scooter and the mechanical components
Table 2.6. Characteristics of direct current permanent magnets motors
Table 2.7. Characteristics of hydraulic components
Table 2.8. Characteristics of various connections

Chapter 3

Table 3.1. Systematic analysis of effects
Table 3.2. Analytical expressions of the parameters for elementary geometries
Table 3.3. Activity index of the models with and without a controller
Table 3.4. Multiple-choice table corresponding to question 1
Table 3.5. Table to be filled corresponding to question 4
Table 3.6. Multiple-choice table corresponding to question 1
Table 3.7. Component analysis
Table 3.8. Propulsion technical data

Chapter 4

Table 4.1. Elements of bond graph formalism
Table 4.2. Example of application of Forward Euler method
Table 4.3. Butcher tableau summarizing the coefficients of the Runge–Kutta metho...
Table 4.4. Butcher tableau for the two previously presented methods
Table 4.5. Values of the coefficients of Adams–Bashforth for various orders p
Table 4.6. Values of the coefficients of Moulton algorithms for various orders p
Table 4.7. Vehicle parameters

Chapter 5

Table 5.1. Gains and phase shift observed for a vehicle suspension
Table 5.2. Laplace transform of common functions
Table 5.3. Typical values of electronic resistances and capacitances
Table 5.4. Operation characteristics of the fluorescent lamp
Table 5.5. Material properties of a wall
Table 5.6. Time constants and corner frequencies of the model in the equation [5...
Table 5.7. Summary of the dynamic performances of three aileron actuators
Table 5.8. Motor technical data

Chapter 6

Table 6.1. Network approaches and variational approaches
Table 6.2. Obtaining electromechanical parameters
Table 6.3. Variables and parameters required for mechanical modeling
Table 6.4. Characteristics of voice coil actuators
Table 6.5. Mechanics form

Chapter 7

Table 7.1. Parameters of the common rail injection system

Chapter 8

Table 8.1. Geometrical characteristics of the studied radiator core
Table 8.2. Thermo-physical properties and operation characteristics of the two f...
Table 8.3. Effectiveness of various heat exchangers
Table 8.4. Nusselt number for a laminar flow and uniform temperature of the wall...
Table 8.5. Thermo-physical properties of water and polypropylene

Chapter 9

Table 9.1. Value of the polytropic index for various processes

List of Illustrations

Chapter 1

Figure 1.1. Digital model and prototype of a personal transporter for didactic p...
Figure 1.2. V-design cycle of complex mechatronic systems
Figure 1.3. Levels of abstraction associated with the V design cycle
Figure 1.4. Modeling of the functional level of a sequence of safety management ...
Figure 1.5. Segway modeling for the validation of preliminary partial sizing bef...
Figure 1.6. Segway model for the validation of control laws
Figure 1.7. Segway modeling at the network level
Figure 1.8. Segway modeling at a geometric level
Figure 1.9. Position of validation and verification activities in the V cycle
Figure 1.10. Examples of network, bond graph, or system models

Chapter 2

Figure 2.1. Evolution of historically mechanical systems
Figure 2.2. Mechatronics fields
Figure 2.3. Mass–spring system: 3D and 0D-1D modeling
Figure 2.4. Mass–spring system under the imposed force. For a color version of t...
Figure 2.5. Mass/ring system under imposed displacement. For a color version of ...
Figure 2.6. Electric circuit and definition of inductor dipole
Figure 2.7. Transformers between various domains. For a color version of the fig...
Figure 2.8. Dissipation and storage in an electric circuit
Figure 2.9. Schematic diagram of the scissor mechanism
Figure 2.10. Kangoo electric window lifter
Figure 2.11. Overall modeling of the power window system
Figure 2.12. Incremental modeling of the direct current motor
Figure 2.13. Incremental modeling of the scissor mechanism. For a color version ...
Figure 2.14. Transient simulation of the power window system
Figure 2.15. Modelica model of a direct current motor of the power window system
Figure 2.16. Modelica model of the power window mechanism
Figure 2.17. Modelica model of the window translational motion
Figure 2.18. Equivalent Modelica model of an electric transformer
Figure 2.19. 16 V super-capacitor module
Figure 2.20. Modeling of the suspension of one-quarter of a vehicle
Figure 2.21. Pressure sensor and electronic interface
Figure 2.22. Wheatstone bridge
Figure 2.23. Instrumentation amplifiers
Figure 2.24.1 Electric scooter
Figure 2.25. Components of the actuation system
Figure 2.26. 3D image of the nozzle
Figure 2.27. Modelica model of the nozzle
Figure 2.28. Typical structure of a Modelica model
Figure 2.29. Hydraulic actuation system
Figure 2.30. Effect of the decoupling capacitor
Figure 2.31. Inductive coupling between two lines
Figure 2.32. Effects of disturbances due to a magnetic field
Figure 2.33. Capacitive coupling
Figure 2.34. 10Base-T twisted cables

Chapter 3

Figure 3.1. Cooling towers of electric power plants
Figure 3.2. Motor-fan group
Figure 3.3. Current in an electric circuit for various waveforms and frequencies
Figure 3.4. From the geometric model to the lumped parameter model
Figure 3.5. Various modeling levels for the motor fan
Figure 3.6. Simulations of various modeling levels (high-speed axis of the reduc...
Figure 3.7. Mechanical modeling of a variable speed motor fan
Figure 3.8. Speed and torque evolution for a progressive rise in speed within 10...
Figure 3.9. Sensors of the activity index
Figure 3.10. Torque/speed for various model levels (with and without driveshaft ...
Figure 3.11. Simplification of the model by design of experiments
Figure 3.12. Setting up an equivalent component
Figure 3.13. Influence of the spectral content of the speed set point
Figure 3.14. MEMS accelerometer
Figure 3.15. Launcher booster nozzle
Figure 3.16.a. EHA flight controls
Figure 3.16.b. Electric elevator power drive
Figure 3.17. Renault Twingo electric power steering
Figure 3.18. Modelica diagram of Twingo electric power steering
Figure 3.19. Modelica diagram for the tie rod–wheel set
Figure 3.20. General diagram of a direct injection system by common rail
Figure 3.21. V150 test train set [ALS 08]. For a color version of the figure, se...
Figure 3.22. Powered bogies of AGV rail motor cars
Figure 3.23. Simplified cross-sectional view of a synchronous motor stator
Figure 3.24. Cross-sectional view of the power steering torque sensor and princi...
Figure 3.25. 2D finite element simulation of the magnetic field of part A of the...
Figure 3.26. Lumped parameter modeling of part A of the sensor
Figure 3.27. Torque sensor modeling
Figure 3.28. Alternator and electric motor for the navy (courtesy of Jeumont Ele...
Figure 3.29. Technological diagram of the propelling set
Figure 3.30. Shaft line between electric motor and propeller

Chapter 4

Figure 4.1. Example of a simple pendulum
Figure 4.2. Example of rectangle approximations of a curve
Figure 4.3. Illustration of the problems related to numerical differentiation
Figure 4.4. State–space representation as a block diagram
Figure 4.5. Network diagram of a second-order RLC low-pass circuit
Figure 4.6. Structure incidence matrix of the RLC circuit presented in Figure 4....
Figure 4.7. Structure incidence matrix in lower triangular form
Figure 4.8. Bond graph representation of power bond and signal arrow
Figure 4.9. Carrousel bond graph [COI 16]
Figure 4.10. Causal bond graph model of RLC filter
Figure 4.11. Bi-causality example, illustration of an R-element
Figure 4.12. Generic result of a numerical simulation
Figure 4.13. Solving y for different time steps using the Forward Euler method
Figure 4.14. Illustration of a second-order Runge–Kutta method, known as the mid...
Figure 4.15. Kinematic viscosity of MIL-PRF-83282 hydraulic fluid
Figure 4.16. Electric circuit to be modeled
Figure 4.17. Electric circuit of associated rectifier and capacitors
Figure 4.18. Rectified circuit under study
Figure 4.19. Wheel model

Chapter 5

Figure 5.1. Definition of dynamic performance criteria
Figure 5.2. Representation of the systems’ frequency behavior. For a color versi...
Figure 5.3. Definition of frequency performance criteria
Figure 5.4. Characteristic of the hydraulic resistance on the fuel backflow
Figure 5.5. Systems’ operating conditions
Figure 5.6. Linearization of a nonlinear function
Figure 5.7. Comparison of the response of the linear and nonlinear models of a c...
Figure 5.8. Frequency response of the common rail system. For a color version of...
Figure 5.9. Common rail injection system
Figure 5.10. Pressure variation for the rapid increase of 1 l/min in the flow ra...
Figure 5.11. System response to rapid flow increase of 1 l/min and . The system...
Figure 5.12. Location of the model poles for a range of variation of the viscous...
Figure 5.13. System’s response to the rapid increase of flow rate by 1 l/min – t...
Figure 5.14. Pole placement provided by Dymola for the common rail system for va...
Figure 5.15. Modeling of the thermal behavior of a furnace
Figure 5.16. Response of a first-order system
Figure 5.17. Signal filtering. For a color version of the figure, see www.iste.c...
Figure 5.18. Bode diagram of the low-pass filter
Figure 5.19. Accelerometer
Figure 5.20. Normalized (dimensionless) settling time for a second-order system
Figure 5.21. Accelerometer response to steps of various amplitudes
Figure 5.22. Fluorescent lamp
Figure 5.23. Bode diagram of ballast in rated operation and in the preheating – ...
Figure 5.24. TGV V150 configuration that has set the world speed record of 574.8...
Figure 5.25. Powered bogies of AGV cars
Figure 5.26. Permanent magnet synchronous motor: winded stator (left) and perman...
Figure 5.27. Two-body thermal model of the stator of a synchronous electric moto...
Figure 5.28. Equivalent circuits of the two-body thermal model of the motor
Figure 5.29. Evolution of the winding heating for an overloaded motor. For a col...
Figure 5.30. Wall of the building envelope
Figure 5.31. Bode diagram of the thermal wall
Figure 5.32. Components of Airbus A340 (courtesy of Jean-Charles Maré)
Figure 5.33. Transient response of the three actuators
Figure 5.34. Sine wave excitation and the response of the three actuators to thi...
Figure 5.35. Bode diagrams for three aileron actuators
Figure 5.36. Types of trains with magnetic levitation
Figure 5.37. Presentation of an onboard power supply network based on HVDC techn...
Figure 5.38. Simplified distributed power network of an aircraft
Figure 5.39. Evolution of voltage across the load during a voltage drop below 54...
Figure 5.40. Piezoelectric injector9 (amended from Philippe Boursin)
Figure 5.41. Needle control piston
Figure 5.42. A towboat pulling a barge
Figure 5.43. Illustration of the aliasing phenomenon
Figure 5.44. Operation principle of an electromagnetic radar
Figure 5.45. Drop forging machine

Chapter 6

Figure 6.1. Modeling methods and study cases (courtesy of Physik Instrumente [PI...
Figure 6.2. Mass–spring system with two degrees of freedom
Figure 6.3. Electrostatic interaction between two plates
Figure 6.4. Energies and co-energies
Figure 6.5. Stress/strain curve for a tensile test of a ductile material
Figure 6.6. Polarization effect
Figure 6.7. Various types of coupling
Figure 6.8. Displacement/Force characteristic for a given voltage
Figure 6.9. Multi-layered ceramics
Figure 6.10. Bulk ceramic modeled under Modelica
Figure 6.11. Component tests
Figure 6.12. Amplification mechanism [PI 18]
Figure 6.13. Modelica model of the amplified actuator
Figure 6.14. Comsol simulation of the amplified actuator [COM 18]
Figure 6.15. Bimorph actuator
Figure 6.16. Strain of a bimorph actuator
Figure 6.17. Geometry of the transducer to be modeled
Figure 6.18. Ultrasound bonding principle. For a color version of the figure, se...
Figure 6.19. Diagram of a half-Langevin
Figure 6.20. First resonance in extension-compression of the Langevin transducer
Figure 6.21. Langevin transducer with sonotrode
Figure 6.22. Modeling of the ultrasonic bonding process
Figure 6.23. Simplified geometry of a scissor lift mechanism
Figure 6.24. Simulation of the two configurations
Figure 6.25. Operation principle of the power-off brake
Figure 6.26. Dimensions of the magnetic circuit
Figure 6.27. Finite element and Modelica modeling of the power-off brake
Figure 6.28. Example of personal transporter and simplified diagram for its mech...
Figure 6.29. Classic steering system
Figure 6.30. Kinematics of the rack – tie rods – wheel pivots assembly
Figure 6.31. FSM

Chapter 7

Figure 7.1. Hydraulic systems of an H215 helicopter [EUR 04]
Figure 7.2. Function-based word bond graph of the actuation system
Figure 7.3. Some properties of MIL-PRF-83282 fluid [SAE 00]
Figure 7.4. Bond graph model of an ideal reservoir
Figure 7.5. Bond graph model of a constant flow pump
Figure 7.6. Bond graph model of a pressure-regulated pump
Figure 7.7. Flow rate/pressure characteristic of the pressure-regulated variable...
Figure 7.8. Modeling of a pressure-regulated variable displacement pump
Figure 7.9. Various pipe models
Figure 7.10. Representation of a hydraulic valve with four ports/three positions
Figure 7.11. Model of a 4/3 valve in the form of a Wheatstone bridge
Figure 7.12. Diagram of a cylinder chamber
Figure 7.13. Modeling of a double-effect cylinder
Figure 7.14. Modelica model of a simplified actuation system
Figure 7.15. Various step responses depending on temperature
Figure 7.16. Various step responses depending on the antagonist load
Figure 7.17. Q–⊿p characteristic for various fluid temperatures
Figure 7.18. Pressure variation during sudden valve closing
Figure 7.19. Flow rate of Moog Series 30 servo valve
Figure 7.20. Flow rate–load characteristic of Moog Series 30 servovalve
Figure 7.21. Servo valve cylinder test model
Figure 7.22. Leakage flow of a Moog Series 30 servo valve
Figure 7.23. Simplified schematic model of the common rail
Figure 7.24. Images of a pressure regulator
Figure 7.25. Schematic model of the pressure regulator

Chapter 8

Figure 8.1. Images of the radiator core
Figure 8.2. Simulation model of a heat exchanger for performance estimation usin...
Figure 8.3. Simulation results with constant effectiveness exchanger model. For ...
Figure 8.4. Distribution of temperatures in an exchanger with concentric tubes. ...
Figure 8.5. Variational approach-based estimation of the heat flow exchanged in ...
Figure 8.6. Variation of exchanger effectiveness with the flow rate of fluids, f...
Figure 8.7. Comparison of simulation results between the exchanger model with co...
Figure 8.8. Heat exchange between the fluids of a heat exchanger with concentric...
Figure 8.9. The Colburn factor and the Darcy friction factor as a function of th...
Figure 8.10. Extension of the exchange surface with fins
Figure 8.11. Variation of the exchanger properties as a function of the flow rat...
Figure 8.12. Comparison of output temperatures obtained using the exchanger mode...
Figure 8.13. Moody diagram (CC BY SA Marc Derumaux)
Figure 8.14. Pressure drop in the radiator for various operating phases. For a c...
Figure 8.15. Configuration of flow in the heat exchanger
Figure 8.16. Double flow MCV and its heat exchanger. For a color version of the ...
Figure 8.17. CMV with the counter-flow plate heat exchanger

Chapter 9

Figure 9.1. Operation principle of heat engines
Figure 9.2. Relationship between three state variables (pressure, temperature, a...
Figure 9.3. Entropic and enthalpic charts for water
Figure 9.4. Illustration of various processes in p-v plane
Figure 9.5. Hirn cycle for a thermal power plant
Figure 9.6. Refrigeration cycle using R-134a fluid
Figure 9.7. Illustration on the h-s diagram of the ideal and real processes in a...
Figure 9.8. Illustration on the h-s diagram of the ideal and real processes in a...
Figure 9.9. Performance mapping of a centrifugal compressor
Figure 9.10. Modelica model of a thermal power plant
Figure 9.11. Results of the simulation of the Hirn cycle
Figure 9.12. Ideal Brayton cycle
Figure 9.13. Technological diagram of the HP

First published 2019 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd
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www.iste.co.uk

John Wiley & Sons, Inc.
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Hoboken, NJ 07030
USA
www.wiley.com

The rights of Marc Budinger, Ion Hazyuk and Clément Coïc to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2019938718

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-78630-378-3

Foreword

It is a fact that the massive use of modeling and numerical simulation is now spreading to all life stages of a technological system. It is an effective way to limit risks, optimize performance, and reduce development time (getting it right the first time). In this logic, the commercial offer of system-level simulation environments continues to grow, to diversify, and to be more accessible to the non-specialist. We would almost believe that the simulation environment used gives us immediate competence to create value and facilitate decision-making in response to engineering needs.

In modeling, the first principles of conservation to adopt a network vision were formulated in the 18th and 19th centuries. The 20th century saw the emergence of the notions of “across” and “through” variables, domain analogies, and then bond graph to provide a methodological framework for the modeling and analysis of energy transfer systems. In the 1960s, electronics gave rise to commercial analog simulation solutions, which largely contributed to the promotion of block-diagram representation. The methods of numerical integration that appeared with Newton, since the end of the 18th century, have continued to develop before and after the advent of digital computers. Modern digital solvers are now able to deal with stiff, discontinuous and algebro-differential problems. They even have a layer of expertise that adapts them permanently and automatically to the mathematical nature of the model to integrate. The programming languages have evolved at the same time to standardize the definition of models and the implementation of solvers. Recent acausal languages like Modelica even support the sorting of non-oriented equation for computation, allowing the symbolic manipulations, and relieving many constraints of assembly or inversion of models. Finally, the libraries of generic models that are offered enable building a model by a series of drags and drops, without even writing a line of code. On these findings, we would indeed be tempted to consider that with a modern simulation business environment, the simulation of a multi-physics technology system no longer presents any difficulty. This is not the case for several reasons.

The initial training of technicians and engineers has long been constrained by its structuring in hermetic silos (mechanics, electrotechnics, fluid mechanics, etc.). At the end of the 1970s, it first aimed to cover the needs related to fine sizing via local modeling (solid finite elements and later computational fluid mechanics, 2D or 3D electromagnetism). It is only in the last two decades that the multidisciplinary system simulation has really developed. However, training and bibliographic resources have mostly remained associated with specific technology areas or software. For its part, the application field of the system simulation is no longer limited only to the study of the dynamic response, particularly for the needs of the control. It extends to growing concerns about performance (power consumption, power requirements, failure response, thermal equilibrium, system integration, etc.). It must and must take advantage of advanced inverse sizing methods, optimization, robust design, and verification/validation.

Considering these new skill needs, the authors propose in this book an applied vision that comes from many years of experience of higher education and research related to the industry. Modeling is treated here in a broad sense: simplification just sufficient for the development of the model, implementation, simulation of the model taking into account the constraints of the solvers, and exploitation of the simulation for the effective creation of value. Through the many topical examples they develop, the authors effectively disseminate good practices and facilitate the acquisition of know-how in multi-physics modeling of technological systems.

Pr. Jean-Charles Maré

INSA Toulouse