Modeling And Simulation Of Constrained Predictive Control Systems To Meet Speed Profiles Using Power And Energy Models

Abstract

Hybrid electric vehicles (HEVs) are a useful alternative for solving the problems inherent to purely electric vehicles. Among the main problems that are solved is their autonomy. The present work implements a vehicle architecture oriented towards power and energy models, with a fuel cell as the main propulsion element and storage elements such as batteries and supercapacitors. This combination allows the efficient use of energy and power densities, given by the capacities of each of the aforementioned elements. The control system to be implemented is a system based on MPC predictive models, with a variation in the cost function that allows us to control the individual functions by weights. The cost function allows to preserve the useful life of the elements, reduce the efforts of the components for operation in regions of greater efficiency and also weigh the economic operation of each of the elements, regulating their use within the system which can be related to the use of fuel, which in the particular case will be hydrogen. Driving profiles developed for urban service buses are used, and a balance of powers is proposed to meet them, considering the forces contrary to movement, the dissipative forces and the mass of each of the elements.