Controle preditivo aplicado à fase de aproximação na formação de comboios veiculares
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Tipo de produção
Dissertação
Data
2022
Autores
Batista, Flávio José Bento
Orientador
Leonardi, Fabrizio
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Citação
BATISTA, Flávio José Bento. Controle preditivo aplicado à fase de aproximação na formação de comboios veiculares. 2022. 137 p. Dissertação (Mestrado em Engenharia Mecânica) - Centro Universitário FEI, São Bernardo do Campo, 2022. Disponível em: https://doi.org/10.31414/EM.2022.D.131520.
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Palavras-chave
controle de cruzeiro adaptativo,controle preditivo
Resumo
A automação veicular, possui diversos desenvolvimentos que compõe o chamado sistema avançado de assistência ao condutor, (ADAS - Advanced Driver Assistance System), e caminham para a direção autônoma. Um elemento crucial à evolução do ADAS, é o controle da dinâmica longitudinal veícular, realizada pelo sistema de controle de cruzeiro adaptativo (ACC - Adaptive Cruise Control), amplamente utilizado em veículos de passeio e comerciais, com intuito de aumentar a segurança, conforto e economia de combustível à viagem. Sua função é, manter determinada velocidade de cruzeiro e, na presença de veículo lento a frente, adaptar sua velocidade, controlando a distância entre os veículos e formar um comboio com segurança, evitando acidentes e erros de condução. Existem três momentos básicos com o ACC, velocidade de cruzeiro (controle de velocidade), comboio formado (controle de distância) e a fase de aproximação de formação de comboio, no qual ocorrem trocas entre estes controladores. A revisão da literatura indica, que esse gerenciamento de controladores pode ser feito de diversas formas, visando requisitos diversos. O presente trabalho, desenvolve um controlador preditivo baseado em modelo (MPC - Model Predictive Control) para um ACC, com requisitos de consumo de combustível, segurança e conforto em viagem, incluídos explicitamente na fase de projeto e não apenas constatados a posteriori, utilizando-se das propriedades do método de Controle Ótimo, intrínsecas ao MPC. Aplicando em sua formulação, as equações levantadas, referentes a consumo, segurança e conforto. Com atenção a fase de aproximação, o MPC proposto, foi simulado e analisado perante outros dois métodos com este foco, obtendo um bom desempenho em consumo, segurança e conforto, respeitando as restrições impostas em projeto e sem negligenciar um requisito em prol de outro. O controlador concebido, também foi posto à prova em outros cenários, com situações comuns de acontecer em uma rodovia. O algoritmo do MPC, foi refinado durante todas estas simulações, obtendo comportamento que satisfez as restrições de projeto na maioria das situações impostas. No entanto, ocorreram eventos de instabilidades para a segurança do sistema veícular, por parte do algoritmo idealizado, expondo frentes de pesquisa para a continuidade deste trabalho. Por fim, os resultados apresentados pelo MPC projetado, foram alcançados, inserindo na fase de projeto os requisitos de consumo, segurança e conforto, obtendo boa performance, quando comparado as técnicas estudadas
Vehicle automation has several developments that make up the so-called advanced driver assistance system (ADAS) and move towards autonomous driving. A crucial element in the evolution of ADAS is the control of vehicular longitudinal dynamics, performed by the adaptive cruise control system (ACC), widely used in passenger and commercial vehicles, in order to increase safety, comfort and fuel economy while traveling. Its function is to maintain a set cruising speed and, in the presence of a slow vehicle ahead, adapt its speed, controlling the distance between vehicles and safely forming a platoon, avoiding accidents, and driving errors. There are three basic moments with the ACC, cruise speed (speed control), formed platoon (distance control) and the platoon formation approaching phase, in which several switching occur between the controls. The literature review indicates that this controller management can be done in different ways, aiming at better consumption, speed in forming a convoy, safety, and comfort. The present work develops a model-based predictive controller (MPC) for an ACC, with fuel consumption, safety, and travel comfort requirements, explicitly included in the design phase and not only verified a posteriori, utilizing the properties of the Optimal Control method, intrinsic to the MPC. Applying in its formulation, the equations raised, referring to consumption, safety, and comfort. With attention to the approaching phase, the proposed MPC was simulated and analyzed before two other methods with this focus, obtaining a good performance in consumption, safety, and comfort, respecting the constraints imposed in the project and without neglecting one requirement in favor of another. The designed controller was also put on tests in other scenarios, with common situations that happen on the highway. The MPC algorithm was refined during all these simulations, obtaining behavior that satisfied the design constraints in most imposed situations. However, there were instability events for the safety of the vehicle system, on the part of the idealized algorithm, exposing research fronts for the continuity of this work. Finally, the results presented by the designed MPC were achieved, including in the design phase the requirements of consumption, safety, and comfort, obtaining good performance, when compared to the studied techniques
Vehicle automation has several developments that make up the so-called advanced driver assistance system (ADAS) and move towards autonomous driving. A crucial element in the evolution of ADAS is the control of vehicular longitudinal dynamics, performed by the adaptive cruise control system (ACC), widely used in passenger and commercial vehicles, in order to increase safety, comfort and fuel economy while traveling. Its function is to maintain a set cruising speed and, in the presence of a slow vehicle ahead, adapt its speed, controlling the distance between vehicles and safely forming a platoon, avoiding accidents, and driving errors. There are three basic moments with the ACC, cruise speed (speed control), formed platoon (distance control) and the platoon formation approaching phase, in which several switching occur between the controls. The literature review indicates that this controller management can be done in different ways, aiming at better consumption, speed in forming a convoy, safety, and comfort. The present work develops a model-based predictive controller (MPC) for an ACC, with fuel consumption, safety, and travel comfort requirements, explicitly included in the design phase and not only verified a posteriori, utilizing the properties of the Optimal Control method, intrinsic to the MPC. Applying in its formulation, the equations raised, referring to consumption, safety, and comfort. With attention to the approaching phase, the proposed MPC was simulated and analyzed before two other methods with this focus, obtaining a good performance in consumption, safety, and comfort, respecting the constraints imposed in the project and without neglecting one requirement in favor of another. The designed controller was also put on tests in other scenarios, with common situations that happen on the highway. The MPC algorithm was refined during all these simulations, obtaining behavior that satisfied the design constraints in most imposed situations. However, there were instability events for the safety of the vehicle system, on the part of the idealized algorithm, exposing research fronts for the continuity of this work. Finally, the results presented by the designed MPC were achieved, including in the design phase the requirements of consumption, safety, and comfort, obtaining good performance, when compared to the studied techniques