The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB R /SimPowerSystems R for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions.

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An accurate battery management strategy is a crucial need in the developing of reliable and viable plug in and hybrid electric vehicles. This on-board algorithm has the advantages to protect the battery from critical operating conditions and improve its lifetime. However, the effectiveness of the battery management strategy mainly depends on the accuracy of its state of charge (SOC). In this context, this paper proposes a novel technique for the SOC estimation based on the unknown input observer and a new differential-algebraic model of a lithium iron phosphate battery. The proposed observer aims to overcome the unknown value of the initial SOC for on-board batteries using only current and terminal voltage measurements. A reduced-order based unknown input observer is developed to estimate the open circuit voltage and the SOC using the OCV-SOC characteristic offline-determined. The unbiasedness of the estimation error is guaranteed by the parameterization of a set of Sylvester constraints. The performance of the proposed observer is verified by simulations and experiments and the accuracy of the obtained results is analyzed and assessed.

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This paper deals with the sizing and control of a fuel cell based hybrid power supply used in vehicular applications. The system consists of a fuel cell, a battery and a pack of ultracapacitors connected to three DC-DC converters. The proposed approach takes into account dynamic constraints and energetic capacity limits of the power sources by considering a filtering based energy management strategy and energetic characteristics of the used technologies. The sizing solutions are computed for two different driving cycles and then the systems are modeled and simulated using MATLAB/SimPowerSystems. The obtained results are given and discussed.

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