Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
Vasconcelos, Rafael de
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| Orientador(a): |
Pimentel, Guilherme Araujo
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Pontifícia Universidade Católica do Rio Grande do Sul
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| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Elétrica
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| Departamento: |
Escola Politécnica
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede2.pucrs.br/tede2/handle/tede/9999
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Resumo: |
Dynamic networks are present in systems from different areas, such as engineering, biology, economics, and model the dynamic connections that occur within the systems. The network model identification is a tool to improve the control and handling of complex systems. In this work, the concept of network identification will be applied in a platoon of autonomous vehicles. The objective of forming a platoon with vehicles is to minimize aerodynamic drag and thus generate fuel savings and decrease pollutant emissions. To achieve significant savings results it is necessary to maintain small spaces between vehicles, and to maintain the smallest spacing safely the use of autonomous vehicles is applied. In this work, two network topologies are presented to describe the vehicle platoon, and the result of the identification by numerical modeling of the transfer functions is presented for each of the topologies. The modeling of vehicles is done in such a way that the aerodynamic drag coefficient of the vehicles is also identified. We conclude that the network topology influences the variance of the identified signals, and the network with greater depth presents better results. |
