Algoritmo de um controlador lógico fuzzy do motor à combustão interna de um veículo convencional convertido para uma arquitetura elétrica híbrida

Abstract

Electrification is the future of transportation in a society where the environmental impacts caused by the use of fossil fuels are taking catastrophic proportions. In a period shaped by natural resource shortages, rising fuel prices and strict emission laws, many governments are working to ban the production and sale of vehicles powered only by fossil fuels, and requiring vehicles with no fuel and with zero emissions. Because of that, electric and hybrid vehicles are a reality, but for a long time they will coexist with conventional vehicles yet. Actually, an electric or hybrid vehicle costs more than a conventional given the same use. However, it is possible to convert conventional vehicles to a hybrid or full electric vehicle using commercial kits. Regarding convert vehicles, one of the biggest challenges is the management of energy distribution of different sources aiming a strategy of saving fuel and reducing greenhouse emissions. The fuzzy logic controller is the most common among the controllers better known as having a rules-based strategy, and has the advantage of simplicity, requiring low processing capacity and considered a real-time controller. This work presents an algorithm for controlling the internal combustion engine based on fuzzy logic that can be part of global energy management system in conventional vehicle converted to a hybrid electrical architecture. Each controller step is presented including the base of rules, membership functions, inference system, aggregation, and as an output the decision taken to drive the internal combustion engine. A simulation of a hybrid electric vehicle has been used to obtain the input signals of the controller over a standard test cycle known as FTP-75 that simulates a direction in an urban environment. As result the response of each step of the controller is presented as well as the decision taken by the fuzzy logic controller.