Control and supervision of an AGV with energy consumption optimization

• Main Author: Nuno Miguel Teixeira Das Neves Lobo
• Publication Date: 2021
• Format: Master thesis
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://hdl.handle.net/10216/137413
• topic: Engenharia electrotécnica, electrónica e informática; Electrical engineering, Electronic engineering, Information engineering

Autonomous guided vehicles (AGVs) have gained enormous importance and interest in the industry field. These are popular solutions for transport of good and material to different parts of the factories. However, in many factories, warehouses are located apart from the factory floor or in separate buildings, requiring the transport of material goods to be done outdoors. Outdoor environments represent a particular challenge for AGVs. On one hand, these environments causes more wear and tear on vehicle components and the weather in Europe can reach opposite extremes depending on the season and regions. On the other hand, these environments increase safety concerns since other vehicles or pedestrians can circulate in the same space at the same time. In this project, an electric tugger XXL will be transformed into an AGV, which operates in outdoor environment. This vehicle is responsible for transporting goods from the end of the production line to the outside warehouse in a car manufacturing plant. The main objective is to ensure its continuous operation during a 16-hour shift, and guarantee the minimum battery charging actions. In this way, in this dissertation two distinct chapters were approached: for the analysis and study of the energy consumption it was simulated the powertrain of an electric vehicle. In this one it was considered an induction motor whose control method applied was the Field Oriented Control (FOC). Besides the electrical behaviour, also the physical model of the load was simulated as well as the calculation of the consumed electrical energy. For navigation, a solution based on the integration of GPS with INS was studied. Given the temporal constraints, only the GPS solution was tested and the loosely coupled technique was approached as a possible integration solution.