The main objective of the project is to contribute to the improvement of fuel cell based electrical powertrains. This will be carried out in three main directions: the construction of an improved fuel cell compared to the state of the art, the improvement of the control and energy management systems of the PEM fuel cell hybrid systems, and the validation and tuning in three specific applications of practical interest. Given that these objectives are fully multidisciplinary, the project will be structured in three subprojects. In the subproject described here, the efforts will focus on the development of new energy management and control systems, and their validation in three autonomous electric vehicles. One of the vehicles will be an omnidirectional robotic platform that has been developed by the project team. Its current powertrain will be replaced by a hybrid powertrain developed in the project. The omnidirectional autonomous robot is intended to move autonomously being part of a fully automated industrial environment within the framework of Industry 4.0. Fuel cells are nonlinear distributed dynamic systems. This implies that most control engineering methodologies, such as modeling, parametric identification, state observation and design techniques are difficult to apply. For this reason, the models of the PEM fuel cells (PEMFC) will be revisited, emphasizing efficiency and degradation phenomena and the appropriate model order for implementation. These models will be completed with experimental protocols and on-line and off-line parameter estimation algorithms that will lead to automatic model tuning from experimental data. The closed Fuel Cell physical structure and its distributed nature makes impossible to measure all the state variables. In this scenario, state observers can play a decisive role in improving the performance of control systems, especially in the aspects related with degradation, a phenomenon that does not affect the entire fuel cell equally. Therefore, state estimation algorithms will be developed, and the simultaneous estimation of the states and parameters will be analyzed. In addition to improving the control systems, it is expected that these algorithms allow the implementation of fault detection and isolation techniques, which are of great interest in preventive maintenance procedures. Fuel cells are only one component of a hybrid traction system which consists of the fuel cell and an energy storage element (i.e. battery or supercapacitor). Therefore, it is vital to determine the optimal instantaneous power flow and the amount of energy stored. To address these aspects, a hardware/software device will be developed to capture power profiles. Based on these profiles, optimal control and energy management systems will be designed with the objectives of minimizing the consumption and degradation of the different elements. Although the control and energy management algorithms will be implemented in all three prototypes addressed in the project, special emphasis will be given to the omnidirectional autonomous robot. In this context, energy management and path planning techniques will be integrated in order to improve the energy efficiency of the entire system.
Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020
Programa Estatal de I+D+i Orientada a los Retos de la Sociedad