Abstract
Fuel cell (FC)/ battery hybrid system power management is a decision making process which controls the power flow between each power sources. Intelligent power management (IPM) is an innovative power handling concept that can actively control the hybrid system power flow according to the load power changes and the battery state of charge variations. In addition to that, the IPM system controls the FC compressor air flow rate in order to supply the required oxygen concentration on demand. The Fuel Cell Current Limit (FCCL) controller decides the FC system operating current and the Adaptive Neuro Fuzzy Inference System (ANFIS) regulates the air flow rate by changing the compressor motor voltage. The FC system optimum compressor motor voltage which maximizes the FC system net power output is a function of the FC current. Therefore, the IPM system adapts the actual compressor motor voltage into the optimum compressor motor voltage. The ANFIS based controller back-propagates the Gaussian membership function estimation parameters such as mean (x <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-j</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ), variance (sigma <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) and the fuzzy output (z) based on error generated by error minimization algorithm. The IPM system online adaptation process minimizes the oxygen concentration loss and maximizes the FC system net power output.
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