{"id":111789,"date":"2018-03-11T10:38:27","date_gmt":"2018-03-11T10:38:27","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/optimitzacio-del-consum-energa%c2%a8tic-en-ferrocarrils-a-partir-del-control-de-les-ca-rregues-auxiliars\/"},"modified":"2018-03-11T10:38:27","modified_gmt":"2018-03-11T10:38:27","slug":"optimitzacio-del-consum-energa%c2%a8tic-en-ferrocarrils-a-partir-del-control-de-les-ca-rregues-auxiliars","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/ingenieria-de-procesos\/optimitzacio-del-consum-energa%c2%a8tic-en-ferrocarrils-a-partir-del-control-de-les-ca-rregues-auxiliars\/","title":{"rendered":"Optimitzaci\u00f3 del consum energ\u00e9tic en ferrocarrils, a partir del control de les c\u00c1\u00a0rregues auxiliars"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Ricard Barba Mart\u00ed <\/strong><\/h2>\n<p>Introduction    the aim is to solve the recovery of waste energy problem, in braking periods on railway  electrical vehicles, by means of a load behaviour analysis, and in particular, in air conditioning  systems (hvac), as higher consumption load (15% of total).     with the control and model introduced, we work on an energy storage system located at the  same hvac unit.     the feasibility of the application is on the urban and sub-urban electric railways, due to the  high depart\/braking cycle frequency and the high consumption.    feasibility and background    the hvac control experiences to search energy efficiency are  based on knowledge of the  heating load. We know almost 75% of the global load, with good accuracy.     all the  simulations still are developed on very simplified  scenarios. True application is  still  difficult to demonstrate.    if we research a storage control during a trip, and its relation with a closed loop thermal system  control, then we have to dispose of a predictive control, in a superior level of the management  hierarchy, joint to the consumption data from the vehicle.    the saving proposal is based on the future and past information availability, in order  to get  profit from the inertia of the system, and also the energy cost cycle.    we set a predictive control at vehicle level, with  constraints, an optimisation function and a  control law. Also some expert rules.    in order to get the energy saving, we need second order systems. Also we have to manage  main non-lineal issues.  formulation of the problem    the calculated variable is the supply airflow temperature and the minimum power, applied to  the model. We use the formulations for the mass and also for the sensible and latent energy.   it\u00c2\u00bfs recommended the fresh air control, based on three concepts: free cooling, heating  recovery, control of passenger occupancy.    we perform energy equations by means of an equivalent representation of the electrical circuit,  as a second order system. As we are working with a semi-insulated system, so the searched  solution using electrical circuits simulation tools, don\u00c2\u00bft work.     the objective function to minimise has two terms, the quadratic differences of temperature and  the energy applied.    strategy of the control    it consists in to apply the minimum energy to the plant, which is calculated from the cost  function, taking in account the prediction of the model and the comfort set point.   the defined amount of reheating power can be minimised also in our control.    it is demonstrated the stability of the system as second order model.    with the application to the tramway case, a lot of subjects have been confirmed using  matlab.   with this tool, we are performing a specific mpc programation.     development of thermal storage system     the proposed storage system takes profit of the solid-liquid phase change heating of wate besides to evaporator coil, with an absorption-evaporation cycle. With  a predictive adaptive  control, it makes the prediction of the required load in the vehicle, so it manages the availabl energy.     during the braking period time, the obtained energy is used to apply mainly on the compresso (of variable speed), achieving the maximum capacity, and generating a  big flow of hot  refrigerant gas. It\u00c2\u00bfs chosen an absorption cycle to absorb the entire compressor dischargin capacity of the flux. During the traction and coasting mode, the thermal machine will try to us the minimum amount of energy to go on running. We use the same lubricant oil as absorbent.   the predictive control will do a monitorisation of the required power, the driving mode, speed status and health of the accumulator, and it will calculate the key variables for the controller o second level: supply airflow temperature and minimum power to apply and the  operatio mode.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Optimitzaci\u00f3 del consum energ\u00e9tic en ferrocarrils, a partir del control de les c\u00c1\u00a0rregues auxiliars<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Optimitzaci\u00f3 del consum energ\u00e9tic en ferrocarrils, a partir del control de les c\u00c1\u00a0rregues auxiliars <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Ricard Barba Mart\u00ed <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de catalunya<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 18\/11\/2011<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Ricardo Bosch Tous<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Jos\u00e9 Antonio Orosa Garc\u00eda <\/li>\n<li>Carlos Verganzones nicol\u00e1s (vocal)<\/li>\n<li>  (vocal)<\/li>\n<li>  (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Ricard Barba Mart\u00ed Introduction the aim is to solve the recovery of waste energy problem, in braking 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