Design and Modelling of the Powertrain of a Hybrid Fuel Cell Electric Vehicle

This paper presents a Fuel Cell Electric Vehicle (FCEV) powertrain development and optimization, aiming to minimize hydrogen consumption. The vehicle is a prototype that run at the Shell Eco-marathon race and its powertrain is composed by a PEM fuel cell, supercapacitors and a DC electric motor. The supercapacitors serve as an energy buffer to satisfy the load peaks requested by the electric motor, allowing a smoother (and closer to a stationary application) working condition for the fuel cell. Thus, the fuel cell can achieve higher efficiency rates and the fuel consumption is minimized. Several models of the powertrain were developed using MATLAB-Simulink and then experimentally validated in laboratory and on the track. The proposed models allow to evaluate two main arrangements between fuel cell and supercapacitors: 1) through a DC/DC converter that sets the FC current to a desired value; 2) using a direct parallel connection between fuel cell and supercapacitors. The results obtained with the direct parallel connection (with the appropriate sizing of the overall capacity) have highlighted a significant efficiency advantage, while the DC/DC converter insertion enables an improved control of the fuel cell current and requires a smaller capacitance. Furthermore, a sizing methodology for the supercapacitors capacitance is proposed for both layouts: with the DC/DC converter it mainly depends on the energy range provided by supercapacitors to the electric motor, while in the direct parallel connection the supercapacitors sizing is outlined by concurrently evaluating the circuit's predicted hydrogen consumption and granting the most suitable conditions to increase the fuel cell performance. Finally, the results obtained from the model were validated by comparing them with experimental data obtained in the laboratory and on the track

Indoor Robot Navigation Using Log-Polar Local Maps

Abstract: In this paper we consider the problem of building a new class of metric maps representing the surroundings of a mobile robot moving in an unstructured indoor environment. Maps are conceived with a metric based on a log-polar space representation: this retina-like representation allows a better definition of objects near the robot, giving less importance to far ones. Information provided at each step by ultrasonic sensors has an uncertainty that is conceptualised as a fuzzy measure and is combined with previous data using Smets transferable believe model. The map building algorithm is integrated in a sensor-based robot navigation system able to recognise some characteristics of the environment. A pattern-matching algorithm, based on Mellin transform, takes advantage on the particular retina-like representation. Copyright c©2003 IFA