A hierarchical predictive strategy-based hydrogen stoichiometry control for automotive fuel cell power system - Details

author：

Quan, Shengwei (Quan, Shengwei.) ^[1] | Chen, Jinzhou (Chen, Jinzhou.) ^[2] | Wang, Ya-Xiong (Wang, Ya-Xiong.) ^[3] (Scholars：王亚雄) | He, Hongwen (He, Hongwen.) ^[4] | Li, Jianwei (Li, Jianwei.) ^[5]

Indexed by：

EI Scopus

Abstract：

Fuel　cell　vehicles　which　have　the　advantages　of　high　energy　conversion　efficiency　and　no　pollution　are　considered　to　be　an　important　development　direction　for　new　energy　vehicles.　The　output　of　polymer　electrolyte　membrane　fuel　cell　(PEMFC),　as　the　main　energy　source　of　fuel　cell　vehicles,　is　influenced　by　fuel　starvation　due　to　untimely　hydrogen　supply　under　frequently　changing　vehicle　operating　conditions.　Therefore,　it　is　necessary　to　predict　the　vehicle　speed　and　regulate　the　hydrogen　stoichiometry　to　ensure　the　power　of　the　vehicles　and　extend　the　durability　of　the　PEMFC.　In　this　paper,　a　hydrogen　stoichiometry　control　system　for　PEMFCs　is　proposed　based　on　hierarchical　predictive　strategy.　The　first　layer　prediction　uses　the　Markov　chain　to　predict　the　vehicle　speed.　The　PEMFC　current　demand　as　a　function　of　vehicle　speed　is　calculated　by　the　vehicle　dynamics　model　and　the　PEMFC　output　characteristic　model.　The　second　layer　prediction　uses　the　model　predictive　control　(MPC)　method　to　control　the　fuel　cell　anode　supply　system　and　regulate　the　hydrogen　stoichiometry.　The　hierarchical　predictive　control　system　has　a　good　control　effect,　which　can　maintain　the　hydrogen　stoichiometry　above　1.4　during　the　whole　operating　process　of　vehicles.　©　2019　IEEE.

Keyword：

Automotive fuels Conversion efficiency Forecasting Markov chains Model predictive control Polyelectrolytes Predictive analytics Predictive control systems Propulsion Proton exchange membrane fuel cells (PEMFC) Solid electrolytes Stoichiometry Vehicles

Community：

[ 1 ] [Quan, Shengwei]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China
[ 2 ] [Chen, Jinzhou]School of Mechnical Engineering and Automation, Fuzhou University, Fuzhou, China
[ 3 ] [Wang, Ya-Xiong]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China
[ 4 ] [Wang, Ya-Xiong]School of Mechnical Engineering and Automation, Fuzhou University, Fuzhou, China
[ 5 ] [He, Hongwen]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China
[ 6 ] [Li, Jianwei]National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China