Fuel economy using the global optimization of the Fuel Cell Hybrid Power Systems

Abstract The aim of this paper is to compare an optimal and a sub-optimal strategy for the Fuel Cell Hybrid Power Systems based on Maximum Power Point tracking algorithms (with global feature or not) with the basic energy management strategy, namely the static Feed-Forward strategy considered as reference. The fuel economy is used as the unique performance indicator. The gaps in fuel economy for two Real-Time Optimization strategies based on Global Extremum Seeking algorithm and Perturb & Observe algorithm are compared to highlight the advantages of the global optimization strategies. Up to 5 L fuel economy was obtained for optimal strategies compared to sub-optimal ones. Also, the gaps in fuel economy are estimated for the proposed strategies using two levels of the FC current slope. The results of this study obtained for constant load are validated on a variable and unknown profile of the load power as well.

[1]  Anna G. Stefanopoulou,et al.  Control of Fuel Cell Power Systems , 2004 .

[2]  Minggao Ouyang,et al.  Impact of power split configurations on fuel consumption and battery degradation in plug-in hybrid electric city buses , 2017 .

[3]  M. Krstić,et al.  Real-Time Optimization by Extremum-Seeking Control , 2003 .

[4]  Alin Mazare,et al.  Optimization of the proton exchange membrane fuel cell hybrid power system for residential buildings , 2018 .

[5]  Nicu Bizon,et al.  Global Extremum Seeking Control of the power generated by a Photovoltaic Array under Partially Shaded Conditions , 2016 .

[6]  Nicu Bizon,et al.  Global maximum power point tracking based on new extremum seeking control scheme , 2016 .

[7]  J. Ihonen,et al.  Discrete ejector control solution design, characterization, and verification in a 5 kW PEMFC system , 2017 .

[8]  P. Carvalho,et al.  Biogas/photovoltaic hybrid power system for decentralized energy supply of rural areas , 2010 .

[9]  John Andrews,et al.  Theory, modelling and performance measurement of unitised regenerative fuel cells , 2009 .

[10]  Nicu Bizon,et al.  Real-time optimization strategy for fuel cell hybrid power sources with load-following control of the fuel or air flow , 2018 .

[11]  Kodjo Agbossou,et al.  Design of an adaptive EMS for fuel cell vehicles , 2017 .

[12]  Maxime Wack,et al.  Comparison of robust and adaptive second order sliding mode control in PEMFC air-feed systems , 2015 .

[13]  M. Ouyang,et al.  Approximate Pontryagin’s minimum principle applied to the energy management of plug-in hybrid electric vehicles , 2014 .

[14]  P. Thounthong,et al.  Intelligent Model-Based Control of a Standalone Photovoltaic/Fuel Cell Power Plant With Supercapacitor Energy Storage , 2013, IEEE Transactions on Sustainable Energy.

[15]  Pierluigi Siano,et al.  Recent advances and challenges of fuel cell based power system architectures and control – A review , 2017 .

[16]  Kodjo Agbossou,et al.  Optimization-based energy management strategy for a fuel cell/battery hybrid power system , 2016 .

[17]  Liangfei Xu,et al.  Multi-objective energy management optimization and parameter sizing for proton exchange membrane hybrid fuel cell vehicles , 2016 .

[18]  Frano Barbir,et al.  Efficiency and weight trade-off analysis of regenerative fuel cells as energy storage for aerospace applications , 2005 .

[19]  Chao Qin,et al.  A comprehensive review on hybrid power system for PEMFC-HEV: Issues and strategies , 2018, Energy Conversion and Management.

[20]  Abdul-Ghani Olabi,et al.  Development of Bi-polar plate design of PEM fuel cell using CFD techniques , 2017 .

[21]  Phatiphat Thounthong,et al.  Real-time strategies to optimize the fueling of the fuel cell hybrid power source: A review of issues, challenges and a new approach , 2018, Renewable and Sustainable Energy Reviews.

[22]  Maciej Wieczorek,et al.  A mathematical representation of an energy management strategy for hybrid energy storage system in electric vehicle and real time optimization using a genetic algorithm , 2017 .

[23]  Nicu Bizon.  Energy harvesting from the FC stack that operates using the MPP tracking based on modified extremum seeking control , 2013 .

[24]  Kashif Ishaque,et al.  A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition , 2013 .

[25]  John Andrews,et al.  Regenerative fuel cells , 2008 .

[26]  T. Taner.  Energy and exergy analyze of PEM fuel cell: A case study of modeling and simulations , 2018 .

[27]  Pei Zhang,et al.  A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics , 2015 .

[28]  Carlos Vargas,et al.  Optimization of a hybrid renewable system for high feasibility application in non-connected zones , 2015 .

[29]  Mahmoud Moghavvemi,et al.  Energy management strategies in hybrid renewable energy systems: A review , 2016 .

[30]  S.M.T. Bathaee,et al.  Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy , 2018 .

[31]  Jianqiu Li,et al.  Application of Pontryagin's Minimal Principle to the energy management strategy of plugin fuel cell electric vehicles , 2013 .

[32]  Abdelghani Harrag,et al.  Novel neural network IC-based variable step size fuel cell MPPT controller: Performance, efficiency and lifetime improvement , 2017 .

[33]  Carlos Andrés Ramos-Paja,et al.  A perturbation strategy for fuel consumption minimization in polymer electrolyte membrane fuel cells: Analysis, Design and FPGA implementation , 2014 .

[34]  John Andrews,et al.  PEM unitised reversible/regenerative hydrogen fuel cell systems: State of the art and technical challenges , 2017 .

[35]  Yanjun Huang,et al.  Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle , 2016 .

[36]  Nicu Bizon,et al.  Energy optimization of fuel cell system by using global extremum seeking algorithm , 2017 .

[37]  Nicu Bizon,et al.  Performance analysis of the tracking of the global extreme on multimodal patterns using the Asymptotic Perturbed Extremum Seeking Control scheme , 2017 .

[38]  Taek Hyun Oh,et al.  Design specifications of direct borohydride–hydrogen peroxide fuel cell system for space missions , 2016 .

[39]  P. Wilson,et al.  Development of a multi-scheme energy management strategy for a hybrid fuel cell driven passenger ship , 2017 .

[40]  Nicu Bizon,et al.  Global Maximum Power Point Tracking (GMPPT) of Photovoltaic array using the Extremum Seeking Control (ESC): A review and a new GMPPT ESC scheme , 2016 .

[41]  Liangfei Xu,et al.  Optimization for a fuel cell/battery/capacity tram with equivalent consumption minimization strategy , 2017 .

[42]  Nicu Bizon,et al.  Optimal operation of fuel cell/wind turbine hybrid power system under turbulent wind and variable load , 2018 .

[43]  Hongwen He,et al.  Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming , 2017 .

[44]  Chang-Bock Chung,et al.  Modeling and operation optimization of a proton exchange membrane fuel cell system for maximum efficiency , 2016 .

[45]  Sayyad Nojavan,et al.  Performance improvement of a battery/PV/fuel cell/grid hybrid energy system considering load uncertainty modeling using IGDT , 2017 .

[46]  Youngjin Park,et al.  Optimal adaptation of equivalent factor of equivalent consumption minimization strategy for fuel cell hybrid electric vehicles under active state inequality constraints , 2014 .

[47]  Abdul-Ghani Olabi,et al.  Modelling and simulation of Proton Exchange Membrane fuel cell with serpentine bipolar plate using MATLAB , 2017 .

[48]  Nicu Bizon,et al.  Searching of the extreme points on photovoltaic patterns using a new Asymptotic Perturbed Extremum Seeking Control scheme , 2017 .

[49]  Junye Wang,et al.  System integration, durability and reliability of fuel cells: Challenges and solutions , 2017 .

[50]  Nicu Bizon,et al.  Tracking the maximum efficiency point for the FC system based on extremum seeking scheme to control the air flow , 2014 .

[51]  Phatiphat Thounthong,et al.  Designing and modelling of the asymptotic perturbed extremum seeking control scheme for tracking the global extreme , 2017 .

[52]  Tolga Taner,et al.  Optimisation processes of energy efficiency for a drying plant: A case of study for Turkey , 2015 .

[53]  M. Yari,et al.  A comparative advanced exergy analysis for a solid oxide fuel cell using the engineering and modified hybrid methods , 2018, Energy Conversion and Management.

[54]  Ahmed Al-Durra,et al.  A comparative study of extremum seeking methods applied to online energy management strategy of fuel cell hybrid electric vehicles , 2017 .

[55]  Nicu Bizon,et al.  Improving the PEMFC energy efficiency by optimizing the fueling rates based on extremum seeking algorithm , 2014 .