Abstract

When it is carried out any movement of a gate or another mechanism of control of a canal in free surface flow, an answer of the flow can take a lot of time in being noticed in the place of the canal takes place in which it was generated the necessity to increase or to reduce the irrigation demand, for example. Usually, the scheduled perturbations of the flow can be programmed for a future horizon. In this manner, the control action can also be programmed. This work, it shows a feedforward control algorithm that plans the gate trajectories when the demand at offtakes are programmed in a prediction horizon. The Hydraulic Influence Matrix (HIM) or matrix of sensibility of the hydrodynamic conditions in the canals to changes in the parameters of the gate trajectories is a tool that is shown very effective in the control of canals in open loop. The work defines the concept, it presents the form of to calculate and to compile the HIM starting from the complete equations of Saint-Venant in their characteristic form. Later on, it shows up an algorithm in that HIM is used: a feedforward controller algorithm so-called GoRoSo. Known the water demands at offtakes, the algorithm calculates the optimal gate trajectories in advance for a prediction horizon with the objective of keeping constant the water depth at gravity offtakes.

Abstract

Guaranteeing simplicity and safety is a real challenge of Advanced Driver Assistance Systems (ADAS), being these aspects necessary for the development of decision and control stages in highly automated vehicles. Considering that a human-centered design is generally pursued, exploring comfort boundaries in passenger vehicles has a significant importance. This work aims to implement a simple Model Predictive Control (MPC) for longitudinal maneuvers, considering a bare speed planner based on the curvature of a predefined geometrical path. The speed profiles are constrained with a maximum value at any time, in such way that total accelerations are lower than specified constraint limits. A double proportional with curvature bias control was employed as a simple algorithm for lateral maneuvers. The tests were performed within a realistic simulation environment with a virtual vehicle model based on a multi-body formulation. The results of this investigation permits to determine the capabilities of simplified control algorithms in real scenarios, and comprehend how to improve them to be more efficient. Authors want to acknowledge their organization. This project has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737469 (AutoDrive Project). This Joint Undertaking receives support from the European Unions Horizon 2020 research and innovation programme and Germany, Austria, Spain, Italy, Latvia, Belgium, Netherlands, Sweden, Finland, Lithuania, Czech Republic, Romania, Norway. This work was developed at Tecnalia Research & Innovation facilities supporting this research.

Abstract

Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and plug-in hybrid electric vehicles. Since these vehicles are parked when the batteries are being charged, it is possible to use the traction power converter as on-board charger, also allowing to reduce weight, volume and costs of components in the vehicle. In this context, this paper presents a model predictive control algorithm for an on-board fast battery charging that uses the traction power converter of an electric vehicle. Simulation results and system implementation are depicted, and finally, are presented some experimental results obtained with the proposed control system. (undefined) info:eu-repo/semantics/publishedVersion Document type: Part of book or chapter of book

Abstract

This paper presents a model predictive current control applied to a slow electric vehicle (EV) battery charger. Taking into account the similarities between the power converters inside the EV, it is possible to combine the battery charger and the motor driver in a single integrated converter, thus reducing the weight and volume of the proposed solution, and also contributing to reduce the final price of the EV. Due to the bidirectional power flow capability of the integrated power converter, when working as a slow EV battery charger it can operate in grid-to-vehicle (G2V) mode and in vehicle-to-grid (V2G) mode, contributing to make EVs an important assets in the future smart grids. The integrated power converter working as battery charger operates with sinusoidal current and unitary power factor, contributing to improve the power quality of the electrical grid. This paper provides simulation and experimental results that validate the model predictive control algorithm applied to the proposed integrated power converter working as slow EV battery charger. (undefined) info:eu-repo/semantics/publishedVersion Document type: Part of book or chapter of book

Abstract

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores Nowadays, Electric Vehicles are emerging as the most sustainable alternative to support the expected rise in the number of vehicles in circulation around the world, and to reduce the impact of the transportation sector on the environment. However, this is a technology that still has some limitations that restrict its mainstream adoption. Typically, an Electric Vehicle has a motor drive system and an on-board battery charger that allows charging its battery pack almost anywhere, as long as there is an electrical outlet available. However, this is usually a low-power charger in order to optimize the space and weight on-board the vehicle. As a result, this type of charging typically takes a couple of hours. The purpose of this MSc. Thesis was the development of a unified power electronics converter, capable of performing the roles of drive the electrical machine of an Electric Vehicle and also charging its battery pack, so as to optimize the space and weight of the power electronics components on-board the vehicle while also providing a faster charging operation. The first part of this MSc. Thesis consisted in the study of the state of art of the unified hardware solutions proposed, based on the use of the power electronics components of the motor drive system during the battery charging operation, since both operation modes cannot be performed simultaneously, except for regenerative breaking. Also the respective control algorithms that allow perform each operation mode, according with the solution proposed, were studied. The second part consisted in simulating the proposed unified solution and implementing a proof-of-concept prototype. In the proposed solution the battery charger is based on the use of a three-phase Voltage Source Inverter and the windings of a Brushless DC machine. With respect to the control algorithms, for the motor drive mode the Field-Oriented Control was chosen, while for the battery charging mode two control algorithms were chosen (one for single-phase charging and the other for three-phase charging), based on the Model Predictive Control. The obtained results validate the proposed solution. However, in the case of the electrical machine used in this MSc. Thesis, the values of the inductances of its windings compromise its use as an input filter. Atualmente os Veículos Elétricos surgem como a alternativa mais sustentável perante o aumento expectável do número de veículos em circulação no mundo e por forma a reduzir o impacto ambiental do sector do transporte. Contudo, esta é ainda uma tecnologia com algumas limitações, que ainda não permitiram a sua aquisição em maior escala. Tipicamente um Veículo Elétrico possui um sistema de tração e um sistema de carregamento, que permite carregar as suas baterias em praticamente qualquer local, desde que haja disponível uma tomada ligada à rede elétrica. No entanto, este sistema de carregamento tem normalmente uma potência instalada baixa, por forma a otimizar o espaço e peso ocupados no interior do veículo. Como resultado, este tipo de carregamento demora tipicamente algumas horas. Esta Dissertação de Mestrado teve como objetivo o desenvolvimento de um conversor unificado, capaz de controlar a máquina elétrica usada para a tração de um Veículo Elétrico e de carregar as suas baterias, permitindo otimizar ainda mais o espaço e peso ocupados pelos componentes de eletrónica de potência instalados no veículo e possibilitar ainda carregamentos mais rápidos. A primeira parte desta Dissertação consistiu num estudo do estado da arte de sistemas de hardware unificados, baseados na utilização dos componentes de eletrónica de potência do sistema de tração durante o modo de carregamento das baterias, tendo em conta que as duas operações não podem ser realizadas em simultâneo, exceto para travagem regenerativa. Também foram estudados os algoritmos de controlo que permitem executar cada uma das operações, de acordo com a topologia proposta. A segunda parte consistiu na simulação da solução proposta e na implementação de um protótipo para demonstração da funcionalidade. Nesta solução proposta, o sistema de carregamento baseia-se na utilização de um inversor trifásico do tipo Voltage Source Inverter e dos enrolamentos de uma máquina elétrica do tipo Brushless DC. Em relação aos algoritmos de controlo, para o modo de tração foi selecionado o Controlo por Orientação de Campo (Field-Oriented Control), enquanto que para o modo de carregamento foram selecionados dois algoritmos (um para carregamento monofásico e outro para trifásico), baseados no Controlo Preditivo (Model Predictive Control). Os resultados obtidos permitiram validar a solução proposta. Contudo, os baixos valores de indutância da máquina elétrica usada comprometem o seu uso como filtro de entrada.

Abstract

This work regards the design of optimization techniques for the purposes of state estimation and control in the framework of inland waterways, often characterized by negligible bottom slopes and large time delays. The derived control-oriented model allows these issues to be handled in a suitable manner. Then, the analogous moving horizon estimation and model predictive control techniques are applied in a centralized manner to estimate the unmeasurable states and fulfill the operational goals, respectively. Finally, the performance of the methodology is tested in simulation by means of a realistic case study based on part of the inland waterways in the north of France. The results show that the proposed methodology is able to guarantee the navigability condition, as well as the other operational goals. This work has been partially funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the projects DEOCS (ref. MINECO DPI2016-76493) and SCAV (ref. MINECO DPI2017-88403-R). This work has also been partially funded by AGAUR of Generalitat de Catalunya through the Advanced Control Systems (SAC) group grant (2017 SGR 482).

Abstract

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level.

Abstract

The operation of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Tests conducted on flat roads have shown the potential of platooning to reduce the fuel consumption of about 10%. However, platoons are expected to operate on public highways with varying topography alongside other vehicles. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes have a significant impact on feasible and optimal speed profiles. For single vehicles, experiments have shown that optimizing the speed according to the road profile resulted in fuel saving of up to 3.5%. The use of such a look-ahead control framework is expected to lead to large benefits also for platooning. This thesis presents the design of safe and fuel-efficient control of heavy-duty vehicle platoons driving on realistic road profiles. The scenario where the platooning vehicles cooperate to optimize their overall fuel-efficiency is studied together with the scenario where the vehicles do not explicitly cooperate. First, we propose a control architecture that splits the cooperative platooning control problem into two layers. The top layer computes a reference speed profile that ensures fuel-efficient operation of the entire platoon based on dynamic programming. The bottom layer relies on model predictive control to safely track the reference speed. Simulations show the ability of the proposed controller to save up to 12% of fuel for following vehicles compared to existing platoon controllers and to safely react to emergency braking of the leading vehicle. Second, we propose a gear management layer that fits in the cooperative platooning control architecture and explicitly takes the gear selection into account. The underlying optimal control problem aims at minimizing the vehicle fuel consumption and the reference tracking deviations. Simulations indicate how this formulation outperforms existing alternatives, both in terms of fuel-efficiency and tracking error. Third, we address non-cooperative platooning by proposing a vehicle-following controller suitable for fuel-efficient control of heavy-duty vehicles. The proposed controller explores both the benefits given by the short inter-vehicular distance and those given by pulse-and-glide, i.e., alternating traction and coasting phases. A simulation study suggests fuel saving of up to 18% compared to the single vehicle case, and up to 7% compared to when a constant-distance vehicle-following controller is used. Last, we propose a vehicle-following controller aimed at exploiting long preview of the preceding vehicle trajectory by directly manipulating the inputs of low-level vehicle controllers. This is achieved through a model predictive controller that uses a short prediction horizon and includes a terminal state set that incorporates preview information about the preceding vehicle. Experiments indicate the ability of the controller to avoid unnecessary braking, while simulations show behavior similar to the optimal control behavior. "p"QC 20180416