Fuel cell optimization modeling method integrated with krill behavior artificial bee colony algorithm

Abstract

The invention discloses a fuel cell optimization modeling method for a fusion krill behavior artificial bee colony algorithm. The fuel cell optimization modeling method comprises the following steps: 1) acquiring fuel cell current input and voltage output sampling data through field operation or an experiment; 2) taking the error sum of squares of voltage estimation output and actual voltage output of a fuel cell model as a target function; 3) by virtue of the inspiration of a krill behavior under the guide effect of other individuals in a population, proposing an employed bee phase position improvement rule, and proposing the fuel cell optimization modeling method for the fusion krill behavior artificial bee colony algorithm; 4) setting algorithm operating parameters; 5) estimating unknown parameters in the fuel cell model by operating the fusion krill behavior artificial bee colony algorithm, obtaining a parameter estimation value of the fuel cell model by minimizing the target function, and substituting the parameter estimation value into the fuel cell model to form a mathematical model. The modeling method disclosed by the invention has the characteristics of high optimization precision and high convergence rate, and is also suitable for modeling of other complex chemical reaction processes.

Description

technical field [0001] The invention relates to an optimization modeling method, in particular to a fuel cell optimization modeling method integrated with a krill behavior artificial bee colony algorithm. Background technique [0002] At present, the contradiction between energy demand and environmental protection has become increasingly prominent, and has become an important issue related to whether the national economy and people's lives can achieve sustainable development. Traditional mineral energy sources such as coal, oil, and natural gas are facing problems such as sharp decline in reserves, serious pollution, and increased mining costs. The development of safe, clean and efficient new energy has become the focus of researchers. [0003] Among all kinds of fuel cells, proton exchange membrane fuel cell (PEMFC) uses hydrogen as fuel because of its high efficiency, safety, environmental friendliness, low operating temperature, fast start-up, high specific power, conven...

AI Technical Summary

Problems solved by technology

However, when the above algorithm solves the proton exchange membrane fuel cell modeling problem, there are still shortcomings such as low optimization accuracy and slow convergence speed.

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