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Decision and control system of a solar powered train Maria Beatriz Namorado Stoffel Feria´ Dissertac¸ao˜ para obter o grau de Mestre em Engenharia Electrotecnica´ e de computadores J ´uri Presidente: Doutor Carlos Filipe Gomes Bispo Orientador: Doutor Joao˜ Fernando Cardoso Silva Sequeira Arguente: Doutor Hugo Filipe Costelha de Castro Vogal: Doutor Horacio´ Joao˜ Matos Fernandes Abril 2012 Reasonable people adapt to the world. Unreasonable people persist in trying to adapt the world to themselves. Therefore, all progress depends on unreasonable people. George Bernard Shaw Acknowledgments I would like to express my appreciation to my advisor Professor Joao˜ Sequeira for his guidance and continuous support through the development of my thesis. All the positive and constructive dis- cussions that we had during these last months motivated me and pushed me into wanting to do better, investigate more and find new solutions so that both of us could feel proud of our work. Abstract This thesis addresses the design and simulation of a Decision and Control System (DCS) for a Solar Powered Train (SPT). An intelligent control approach is followed, namely by modeling the whole infrastructure as a discrete event system, represented by Petri nets (PNs), and designing a supervisory controller for the whole system. The DCS is able to manage all energy consumption devices onboard the train, namely, solar panels, batteries, sensors and computational devices, in order to ensure that the train finishes its missions successfully. The system uses previously acquired information on the topology of the line, e.g., length and slopes, locations of the intermediate stations, dynamics of the train, current solar irra- diance and weather forecasting, and passenger weight to determine boundaries on the train velocity profile. Many factors are also involved, such as panel electrical power output, obstacle detection, electric power consumed by engines and several other devices. The control system must take these factors into account and needs real-time observation of all of these variables, which is accomplished through sensors and data bases that can be accessed by the system. Given the energy requirements of all the devices onboard the train, the energy management system must determine if the proposed mission can be carried out successfully, and determine a corresponding range of admissible velocities for the train. The dynamics of the vehicle is also modeled, under Simulink environment, taking into account the effects of aerodynamic drag, friction of railways, gravitational forces and inertia. The whole system was simulated integrating PNs in a Matlab/Simulink environment, using for this purpose two key toolboxes: Netlab and Quasistatic Simulation (QSS). Netlab allows the interaction between PNs and Simulink simulation environment. QSS models the motion dynamics of a vehicle and all its main components such as engine, battery and gear system. The performance of the sys- tem is illustrated through several simulations in multiple realistic scenarios. iii Keywords Petri nets, solar powered train, supervisory control iv Resumo O objectivo deste trabalho consiste no desenvolvimento de um sistema de decisao˜ e controlo (SDC) para um comboio movido a energia solar. O sistema global, incluindo o comboio e estruturas exteriores, e´ modelado atraves´ de um sistema de eventos discretos, nomeadamente redes de Petri, sendo de seguida desenvolvido um controlador supervisor. O SDC tem a func¸ao˜ de gerir todos os equipamentos relacionados com o consumo e produc¸ao˜ de energia, nomeadamente paineis´ solares, baterias, sensores e computadores, por forma a assegurar que o comboio cumpre com sucesso o objectivo e chega com seguranc¸a ao seu destino. O sistema utiliza informac¸ao˜ a priori sobre a topologia da linha, nomeadamente comprimento e inclinac¸ao˜ de cada troc¸o, localizac¸ao˜ de estac¸oes˜ intermedias,´ irradianciaˆ solar no instante actual, previsao˜ meteorologica´ e peso transportado pelo comboio, por forma a estabelecer limites na veloci- dade do comboio. Os factores envolvidos sao˜ tais como o valor de potenciaˆ fornecido pelos paineis,´ a existenciaˆ de obstaculos´ na linha, a potenciaˆ necessaria´ por parte dos motores e outros equipamen- tos, entre outros. O SDC devera´ ter estes factores em conta e a observac¸ao˜ destas variaveis´ e´ feita em tempo real e atraves´ de sensores e bases de dados interligados com o sistema. Tendo em conta os requisitos energeticos´ de cada dispositivo, desde motores a todos os equipamentos electronicos,´ e tambem´ o objectivo a cumprir por parte do comboio, o SDC determina se este sera´ cumprido com sucesso e um correspondente leque de velocidades atingidas pelo comboio durante a missao.˜ A dinamicaˆ do ve´ıulo e´ modelada em Simulink e tem em conta os efeitos resistentes da aerodinamica,ˆ fricc¸ao,˜ gravidade e inercia.´ O sistema global e´ simulado em Simulink e com integrac¸ao˜ de redes de Petri, utilizando duas toolboxes fundamentais para este efeito: Netlab e QSS. O QSS permite mod- elar a dinamicaˆ do ve´ıculo e dos seus componentes principais tais como o motor, bateria e sistema de mudanc¸as. O Netlab por seu lado permite fazer a interacc¸ao˜ entre Simulink e as redes de Petri. Esta interacc¸ao˜ e´ fundamental uma vez que permite a realizac¸ao˜ de simulac¸oes,˜ estabelecendo uma comunicac¸ao˜ em tempo real entre o Simulink e a rede de Petri. O controlo de supervisao˜ e´ entao˜ aplicado, a´ dinamicaˆ do sistema e atraves´ da rede de Petri desenvolvida. O desempenho do sistema v e do controlador supervisor e´ ilustrado em varias´ simulac¸oes˜ e em multiplos´ cenarios.´ Palavras Chave Redes de Petri, Comboio solar, Supervisao˜ vi Contents 1 Introduction 1 1.1 Background . .2 1.2 Motivation . .2 1.3 Original Contributions . .4 1.4 Thesis Outline . .5 2 State of the Art 7 2.1 Solar Powered Vehicles . .8 2.2 Discrete Events Systems and Supervisory Controllers . 12 3 Vehicle Modeling and Simulation Environment 17 3.1 System Overview . 18 3.2 Vehicle Performance Analysis . 20 3.2.1 Aerodynamic drag force . 21 3.2.2 Rolling resistance . 22 3.2.3 Gravitational force . 22 3.2.4 Inertial force . 22 3.3 Vehicle modeling: QSS toolbox . 23 3.3.1 Quasistatic Approach . 24 3.3.2 Vehicle block . 25 3.3.3 Electric Motor . 26 3.3.4 Battery . 29 3.3.5 Gear System . 30 3.3.6 Application Example . 31 3.4 DES Modeling: Netlab toolbox . 36 3.4.1 Describing the Windows Netlab Interface . 36 3.4.2 Describing the Simulink interface . 37 3.4.3 Example of integration of a Petri Net in Simulink: . 38 4 Petri Net Model and Supervisory Controller 43 4.1 Petri net Model . 44 4.1.1 Train . 45 vii 4.1.1.A Petri net analysis . 46 4.1.2 Battery . 47 4.1.2.A Petri net Analysis . 49 4.1.3 Motor . 50 4.1.3.A Petri net analysis . 51 4.1.4 Cruise speed reference . 52 4.1.4.A Petri net analysis . 53 4.1.5 Overall system . 54 4.2 Supervisory Controller . 55 4.2.1 Synthesis of controller using linear constraints . 55 4.2.2 Synthesis of controller using generalized linear constraints . 56 4.2.3 Constraints involving the firing vector . 57 5 Results and Discussion 61 5.1 Power available . 62 5.2 Simulation Tool Model . 64 5.3 Acceleration Influence . 65 5.4 Deceleration Influence . 66 5.5 Weight Influence . 67 5.6 Gradient Influence . 68 5.7 Battery Requirements . 70 5.8 Obstacle on track scenario . 71 5.9 Cloudy Weather and Power failure scenario . 73 5.10 Three stations path scenario . 75 5.11 Time Restriction - Definition of required cruise velocity . 77 6 Conclusions and Future Work 83 Bibliography 85 Appendix A Appendix A A-1 A.1 Simulation Tool Manual . A-2 A.1.1 Vehicle block . A-3 A.1.2 Simple transmission system block . A-4 A.1.3 Electric motor block . A-5 A.1.4 Battery block . A-6 A.1.5 Location tracking block . A-7 A.1.6 Battery state control . A-8 A.1.7 Battery charging control . A-9 A.1.8 Obstacle detection laser range finder block . A-9 A.1.9 Panel block . A-10 viii A.1.10 Weight sensor block . A-10 A.1.11 Timed Petri net block . A-10 A.1.12 Supervisory controller . A-11 A.1.13 Velocity control block . A-12 ix List of Figures 1.1 Artistic view of Helianto: a) Perspective view; b) Side view. .3 1.2 Block diagram of the overall system. .4 2.1 Racing solar cars: a) Race vehicles heading towards the finish line; b) The winner, Tokai University, Japan of the 2009 World Solar Challenge. c) The Dutch winner of the 2005 World Solar Challenge ..................................8 2.2 Top view of Belgium solar train and tunnel. 12 2.3 Graphical representation of PN elements. 13 2.4 An example of a PN graph. 14 3.1 Block diagram of the overall decision and central system. 19 3.2 Forces acting on a vehicle in motion. 21 3.3 Generic Diagram of Quasistatic Approach. ..
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