The OpenModelica integrated environment for modeling, simulation, and model-based development

OpenModelica is a unique large-scale integrated open-source Modelica- and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica- UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.Fil: Fritzson, Peter. Linköping University; SueciaFil: Pop, Adrian. Linköping University; SueciaFil: Abdelhak, Karim. Fachhochschule Bielefeld; AlemaniaFil: Asghar, Adeel. Linköping University; SueciaFil: Bachmann, Bernhard. Fachhochschule Bielefeld; AlemaniaFil: Braun, Willi. Fachhochschule Bielefeld; AlemaniaFil: Bouskela, Daniel. Electricité de France; FranciaFil: Braun, Robert. Linköping University; SueciaFil: Buffoni, Lena. Linköping University; SueciaFil: Casella, Francesco. Politecnico di Milano; ItaliaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Franke, Rüdiger. Abb Group; AlemaniaFil: Fritzson, Dag. Linköping University; SueciaFil: Gebremedhin, Mahder. Linköping University; SueciaFil: Heuermann, Andreas. Linköping University; SueciaFil: Lie, Bernt. University of South-Eastern Norway; NoruegaFil: Mengist, Alachew. Linköping University; SueciaFil: Mikelsons, Lars. Linköping University; SueciaFil: Moudgalya, Kannan. Indian Institute Of Technology Bombay; IndiaFil: Ochel, Lennart. Linköping University; SueciaFil: Palanisamy, Arunkumar. Linköping University; SueciaFil: Ruge, Vitalij. Fachhochschule Bielefeld; AlemaniaFil: Schamai, Wladimir. Danfoss Power Solutions GmbH & Co; AlemaniaFil: Sjolund, Martin. Linköping University; SueciaFil: Thiele, Bernhard. Linköping University; SueciaFil: Tinnerholm, John. Linköping University; SueciaFil: Ostlund, Per. Linköping University; Sueci

Foundations of Multi-Paradigm Modelling for Cyber-Physical Systems

This open access book coherently gathers well-founded information on the fundamentals of and formalisms for modelling cyber-physical systems (CPS). Highlighting the cross-disciplinary nature of CPS modelling, it also serves as a bridge for anyone entering CPS from related areas of computer science or engineering. Truly complex, engineered systems—known as cyber-physical systems—that integrate physical, software, and network aspects are now on the rise. However, there is no unifying theory nor systematic design methods, techniques or tools for these systems. Individual (mechanical, electrical, network or software) engineering disciplines only offer partial solutions. A technique known as Multi-Paradigm Modelling has recently emerged suggesting to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s), and then weaving the results together to form a representation of the system. If properly applied, it enables, among other global aspects, performance analysis, exhaustive simulation, and verification. This book is the first systematic attempt to bring together these formalisms for anyone starting in the field of CPS who seeks solid modelling foundations and a comprehensive introduction to the distinct existing techniques that are multi-paradigmatic. Though chiefly intended for master and post-graduate level students in computer science and engineering, it can also be used as a reference text for practitioners

Computer algebra techniques in object-oriented mathematical modelling.

This thesis proposes a rigorous object-oriented methodology, supported by computer algebra software, to generate and relate features in a mathematical model. Evidence shows that there is little heuristic or theoretical research into this problem from any of the three principal modelling methodologies: 'case study’, ‘scenario’ and ‘generic’. This thesis comprises two other major strands: applications of computer algebra software and the efficacy of symbolic computation in teaching and learning. Developing the principal algorithms in computer algebra has sometimes been done at the expense of ease of use. Developers have also not concentrated on integrating an algebra engine into other software. A thorough review of quantitative studies in teaching and learning mathematics highlights a serious difficulty in measuring the effect of using computer algebra. This arises because of the disparate nature of learning with and without a computer. This research tackles relationship formulation by casting the problem domain into object-oriented terms and building an appropriate class hierarchy. This capitalises on the fact that specific problems are instances of generic problems involving prototype physical objects. The computer algebra facilitates calculus operations and algebraic manipulation. In conjunction, I develop an object-oriented design methodology applicable to small-scale mathematical modelling. An object model modifies the generic modelling cycle. This allows relationships between features in the mathematical model to be generated automatically. The software is validated by quantifying the benefits of using the object-oriented techniques, and the results are statistically significant. The principal problem domain considered is Newtonian particle mechanics. Although the Newtonian axioms form a firm basis for a mathematical description of interactions between physical objects, applying them within a particular modelling context can cause problems. The goal is to produce an equation of motion. Applications to other contexts are also demonstrated. This research is significant because it formalises feature and equation-generation in a novel way. A new modelling methodology ensures that this crucial stage in the modelling cycle is given priority and automated

An object-oriented modelling method for evolving the hybrid vehicle design space in a systems engineering environment

A combination of environmental awareness, consumer demands and pressure from legislators has led automotive manufacturers to seek for more environmentally friendly alternatives while still meeting the quality, performance and price demands of their customers. This has led to many complex powertrain designs being developed in order to produce vehicles with reduced carbon emissions. In particular, within the last decade most of the major automotive manufactures have either developed or announced plans to develop one or more hybrid vehicle models. This means that to be competitive and o er the best HEV solutions to customers, manufacturers have to assess a multitude of complex design choices in the most e cient way possible. Even though the automotive industry is adept at dealing with the many complexities of modern vehicle development; the magnitude of design choices, the cross coupling of multiple domains, the evolving technologies and the relative lack of experience with respect to conventional vehicle development compounds the complexities within the HEV design space. In order to meet the needs of e cient and exible HEV powertrain modelling within this design space, a parallel is drawn with the development of complex software systems. This parallel is both from a programmatic viewpoint where object-oriented techniques can be used for physical model development with new equation oriented modelling environments, and from a systems methodology perspective where the development approach encourages incremental development in order to minimize risk. This Thesis proposes a modelling method that makes use of these new tools to apply OOM principles to the design and development of HEV powertrain models. Furthermore, it is argued that together with an appropriate systems engineering approach within which the model development activities will occur, the proposed method can provide a more exible and manageable manner of exploring the HEV design space.The exibility of the modelling method is shown by means of two separate case studies, where a hierarchical library of extendable and replaceable models is developed in order to model the di erent powertrains. Ultimately the proposed method leads to an intuitive manner of developing a complex system model through abstraction and incremental development of the abstracted subsystems. Having said this, the correct management of such an e ort within the automotive industry is key for ensuring the reusability of models through enforced procedures for structuring, maintaining, controlling, documenting and protecting the model development. Further, in order to integrate the new methodology into the existing systems and practices it is imperative to develop an e cient means of sharing information between all stakeholders involved. In this respect it is proposed that together with an overall systems modelling activity for tracking stakeholder involvement and providing a central point for sharing data, CAE methods can be employed in order to automate the integration of data.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Generierung vereinfachter Modelle mechatronischer Systeme auf Basis symbolischer Gleichungen

Für die Entwicklung, Regelung und Optimierung technischer Systeme stellt die modellbasierte Simulation ein wichtiges Hilfsmittel dar. Dabei sind in vielen Anwendungen niedrige Simulationszeiten essentiell. Eine Simulation besteht zum einen aus dem Modell des technischen Systems und zum anderen aus einem numerischen Lösungsverfahren. Für eine effiziente Simulation sollte das verwendete Modell so einfach wie möglich sein, um den interessierenden physikalischen Effekt noch abbilden zu können, jedoch nicht einfacher. Die Modellbildung technischer Systeme geschieht häufig in objektorientierten Simulationsumgebungen. Diese erlauben eine komfortable Modellierung per drag & drop mit Hilfe grafischer Benutzeroberflächen. Außerdem ist die Modellbildung weniger fehleranfällig, da die meisten Komponenten vorgefertigten Standard-Bibliotheken entnommen werden können. Darüber hinaus sind die generierten Modelle leicht wiederverwendbar. Diese Vorteile führen insbesondere dazu, dass die Erstellung komplexer Modelle technischer Systeme in objektorientierten Simulationsumgebungen in einfacher Art und Weise geschehen kann. In der Regel werden von einem technischen System während des Entwicklungsprozesses mehrere Modelle benötigt. Die einfache Verfügbarkeit komplexer Modelle legt es nahe, die Modellbildung lediglich für das komplexeste Modell zu betreiben und alle weiteren Modelle durch Modellreduktion aus diesem zu generieren. In dieser Arbeit wird ein geeignetes Modellreduktionsverfahren entwickelt und in eine objektorientierte Simulationsumgebung integriert. Das verwendete Modellreduktionsverfahren basiert darauf, ausgehend von einem vorgegebenen Szenario den Einfluss der in den Modellgleichungen enthaltenen mathematischen Terme zu schätzen. Anhand ihres geschätzten Einflusses auf das Simulationsergebnis werden die Terme anschließend sortiert und manipuliert (beispielsweise linearisiert oder vernachlässigt). Da die Schätzung des Einflusses szenariobasiert ist, hängt die Güte des Modells in einer Simulation von der Ähnlichkeit des Reduktionsszenarios zum Simulationsszenario ab. In dieser Arbeit werden zwei Ansätze vorgestellt, um den Gültigkeitsbereich der reduzierten Modelle zu vergrößern. Darüber hinaus wird ein neues, äußerst effizientes Verfahren zur Schätzung des Einflusses der Terme präsentiert. Ein besonderer Schwerpunkt liegt weiterhin auf der Generierung von Modellen für die Echtzeitsimulation. Für die Echtzeitsimulation muss jeder Integrationsschritt innerhalb einer vorgegebenen Zeitspanne berechnet werden können. Die zur Verfügung stehende Rechenleistung hängt dabei zum einen von der Zielhardware und zum anderen von dem gewünschten Takt ab. In dieser Arbeit wird ein Algorithmus vorgestellt, um ausgehend von einem komplexen Modell ein vereinfachtes Modell zu generieren, welches (falls überhaupt möglich) in Echtzeit auf der Zielhardware in dem gewünschten Echtzeittakt simuliert werden kann. Die Leistungsfähigkeit des Verfahrens wird anhand bekannter Modelle aus der Fahrdynamik eindrucksvoll gezeigt. Darüber hinaus wurde im Rahmen der Arbeit ein komplexes Modell einer Baumaschine generiert und anschließend für Echtzeitsimulationen reduziert. Außerdem dient das Modellreduktionsverfahren als Basis für einen Ansatz zur Erstellung generischer Modelle