Battery, Hybrid and Fuel-Cell Propulsion Systems

The main purpose of the Research is theoretical and experimental evaluation of electric propulsion systems: pure electric ones, fed exclusively by electrochemical energy storage, hybrid electric, in which the power for propulsion comes from different sources, and fuel cell-based vehicles. These studies were carried on through an extended modelling and experimental activity, related to: • Modelling and experimental activities on electrochemical storage systems and super-capacitors, to evaluate their performance and to better individuate the optimal sizing for usage on-board electric and hybrid vehicles. • Design and realisation of a Fuel-Cell based vehicle, starting from the design of the propulsion system, for which dedicated models in Matlab-Simulink® environment were specifically realised, coming to an extended laboratory test activity for all the components, specially for the Fuel-Cell System. • Design of a complete line of electric and hybrid buses, based on the modelling of the propulsion system in collaboration with the manufacturer, through the usage of new object-oriented modelling techniques realised in Dymola-Modelica® environment. After evaluating different energy management strategies, an exhaustive comparison with conventional and electric pure versions has been carried on. The PhD Thesis, after an introduction about innovative propulsion systems, describes in detail all the activities presented, trying to summarise general techniques of design and management for hybrid vehicles

Underwater Glider Modelling And Analysis For Variable Control Parameters

Underwater glider is a type of autonomous underwater vehicle that can glide by controlling their buoyancy and attitude using internal actuators. By changing the vehicle’s buoyancy intermittently, forward motion can be achieved. Deriving the mathematical model directly from the system can be too complicated due to time constraints in prototyping development processes. This thesis presents the early development of the USM underwater glider platform consist of prototype development involves vehicle concept design using SolidworksTM, vehicle simulations by Computational Fluid Dynamics (CFD) and alternative way of modelling known as system identification in order to obtain the underwater glider system model. The appropriate control parameters for underwater glider control were determined by selecting the ballast rate as the input. Three aspects of the dynamics of a glider will be observed, i.e. net buoyancy, depth of the glider and pitching angle. The best three parametric models that are able to estimate the system correctly are chosen, and the fit between measured and estimated outputs is presented in order to get an optimal underwater glider vehicle model for USM underwater glider platform

14th Conference on Dynamical Systems Theory and Applications DSTA 2017 ABSTRACTS

From Preface: This is the fourteen time when the conference “Dynamical Systems – Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and the Ministry of Science and Higher Education. It is a great pleasure that our invitation has been accepted by so many people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcome nearly 250 persons from 38 countries all over the world. They decided to share the results of their research and many years experiences in the discipline of dynamical systems by submitting many very interesting papers. This booklet contains a collection of 375 abstracts, which have gained the acceptance of referees and have been qualified for publication in the conference proceedings [...]

Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology

Mathematical and computer-based models provide the foundation of most methods of engineering design. They are recognised as being especially important in the development of integrated dynamic systems, such as “control-configured” aircraft or in complex robotics applications. These models usually involve combinations of linear or nonlinear ordinary differential equations or difference equations, partial differential equations and algebraic equations. In some cases models may be based on differential algebraic equations. Dynamic models are also important in many other fields of research, including physiology where the highly integrated nature of biological control systems is starting to be more fully understood. Although many models may be developed using physical, chemical, or biological principles in the initial stages, the use of experimentation is important for checking the significance of underlying assumptions or simplifications and also for estimating appropriate sets of parameters. This experimental approach to modelling is also of central importance in establishing the suitability, or otherwise, of a given model for an intended application – the so-called “model validation” problem. System identification, which is the broad term used to describe the processes of experimental modelling, is generally considered to be a mature field and classical methods of identification involve linear discrete-time models within a stochastic framework. The aspects of the research described in this thesis that relate to applications of identification, parameter estimation and optimisation techniques for model development and model validation mainly involve nonlinear continuous time models Experimentally-based models of this kind have been used very successfully in the course of the research described in this thesis very in two areas of physiological research and in a number of different engineering applications. In terms of optimisation problems, the design, experimental tuning and performance evaluation of nonlinear control systems has much in common with the use of optimisation techniques within the model development process and it is therefore helpful to consider these two areas together. The work described in the thesis is strongly applications oriented. Many similarities have been found in applying modelling and control techniques to problems arising in fields that appear very different. For example, the areas of neurophysiology, respiratory gas exchange processes, electro-optic sensor systems, helicopter flight-control, hydro-electric power generation and surface ship or underwater vehicles appear to have little in common. However, closer examination shows that they have many similarities in terms of the types of problem that are presented, both in modelling and in system design. In addition to nonlinear behaviour; most models of these systems involve significant uncertainties or require important simplifications if the model is to be used in a real-time application such as automatic control. One recurring theme, that is important both in the modelling work described and for control applications, is the additional insight that can be gained through the dual use of time-domain and frequency-domain information. One example of this is the importance of coherence information in establishing the existence of linear or nonlinear relationships between variables and this has proved to be valuable in the experimental investigation of neuromuscular systems and in the identification of helicopter models from flight test data. Frequency-domain techniques have also proved useful for the reduction of high-order multi-input multi-output models. Another important theme that has appeared both within the modelling applications and in research on nonlinear control system design methods, relates to the problems of optimisation in cases where the associated response surface has many local optima. Finding the global optimum in practical applications presents major difficulties and much emphasis has been placed on evolutionary methods of optimisation (both genetic algorithms and genetic programming) in providing usable methods for optimisation in design and in complex nonlinear modelling applications that do not involve real-time problems. Another topic, considered both in the context of system modelling and control, is parameter sensitivity analysis and it has been found that insight gained from sensitivity information can be of value not only in the development of system models (e.g. through investigation of model robustness and the design of appropriate test inputs), but also in feedback system design and in controller tuning. A technique has been developed based on sensitivity analysis for the semi-automatic tuning of cascade and feedback controllers for multi-input multi-output feedback control systems. This tuning technique has been applied successfully to several problems. Inverse systems also receive significant attention in the thesis. These systems have provided a basis for theoretical research in the control systems field over the past two decades and some significant applications have been reported, despite the inherent difficulties in the mathematical methods needed for the nonlinear case. Inverse simulation methods, developed initially by others for use in handling-qualities studies for fixed-wing aircraft and helicopters, are shown in the thesis to provide some important potential benefits in control applications compared with classical methods of inversion. New developments in terms of methodology are presented in terms of a novel sensitivity based approach to inverse simulation that has advantages in terms of numerical accuracy and a new search-based optimisation technique based on the Nelder-Mead algorithm that can handle inverse simulation problems involving hard nonlinearities. Engineering applications of inverse simulation are presented, some of which involve helicopter flight control applications while others are concerned with feed-forward controllers for ship steering systems. The methods of search-based optimisation show some important advantages over conventional gradient-based methods, especially in cases where saturation and other nonlinearities are significant. The final discussion section takes the form of a critical evaluation of results obtained using the chosen methods of system identification, parameter estimation and optimisation for the modelling and control applications considered. Areas of success are highlighted and situations are identified where currently available techniques have important limitations. The benefits of an inter-disciplinary and applications-oriented approach to problems of modelling and control are also discussed and the value in terms of cross-fertilisation of ideas resulting from involvement in a wide range of applications is emphasised. Areas for further research are discussed

Technology for large space systems: A special bibliography with indexes (supplement 04)

This bibliography lists 259 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1980 and December 31, 1980. Its purpose is to provide information to the researcher, manager, and designer in technology development and mission design in the area of the Large Space Systems Technology Program. Subject matter is grouped according to systems, interactive analysis and design. Structural concepts, control systems, electronics, advanced materials, assembly concepts, propulsion, solar power satellite systems, and flight experiments