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Real‐time optimal energy management for a fuel cell/battery hybrid system
Author(s) -
Chen Hao,
Chen Jian,
Liu Zhiyang,
Lu Huaxin
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2065
Subject(s) - solver , energy management , computer science , battery (electricity) , matlab , hybrid system , quadratic programming , mathematical optimization , state of charge , dynamic programming , fuel efficiency , control theory (sociology) , power (physics) , automotive engineering , energy (signal processing) , engineering , algorithm , control (management) , mathematics , programming language , statistics , physics , quantum mechanics , machine learning , artificial intelligence , operating system
An energy management strategy is proposed for a class of fuel cell/battery hybrid systems. In such hybrid systems, a fuel cell system is the main power source, and a lithium‐ion battery is the auxiliary power source. In order to manage the system power at the next moment in a reasonable way, a load current filter with bounded estimation errors is designed to estimate the load current. Then, a real‐time optimal energy management algorithm is proposed to optimize economy consumption of the hybrid system. By taking current change rate of the fuel cell and the state of charge into consideration and taking reasonable model simplifications, the optimization problem can be described as a quadratic programming problem. Then a general purpose solver is proposed to solve the quadratic programming problem based on the alternating direction method of multipliers. The efficiency of the proposed solver is much faster than computing interior point method or active set method. Simulation results in MATLAB/SIMULINK are carried out to validate the significant effectiveness and efficiency of the proposed management strategy.