A simulation method and system for hydrogen cycle equipment

Abstract

The embodiment of the invention discloses a hydrogen cycle equipment simulation method and system, and relates to the technical field of fuel cell model simulation. Wherein, the method includes: during the simulation process of the hydrogen circulation system, the switching module collects the operating parameters of the hydrogen circulation system and combines the set circulation strategy to determine the optimal structure of the hydrogen circulation equipment; if the optimal The optimal structure is different from the current structure. According to the optimal structure, the switching module sends a hydrogen mass flow control signal to the ejector and circulation pump to control the ejector and circulation pump to change from the primary The mass flow rate of hydrogen obtained by the flow port and the secondary flow port is switched to the optimal structure. In this embodiment, the hydrogen circulation equipment is written in Modelica language, and the operation parameters are automatically collected and the optimal mechanism of the hydrogen circulation equipment is automatically controlled by switching modules, which improves the degree of automation and intelligence of the simulation.

Description

technical field [0001] The invention relates to a fuel cell model simulation technology, in particular to a hydrogen cycle equipment simulation method and system. Background technique [0002] The fuel system simulation plays an extremely important role in the design of fuel cell vehicles. The recovery and reuse of the remaining hydrogen after the combustion of the fuel cell stack has a great impact on the efficiency and performance of the fuel cell. The selection and debugging of system circulation equipment plays a vital role in improving the quality, cycle and cost of fuel cell vehicle projects. The above automated testing methods are based on the prior experience of the tester, compare the pre-prepared test cases with the test results, and find out the differences to complete the test. [0003] Most of the traditional or existing models are based on causal modeling methods, and model writing is limited. When the architecture is changed, the model changes greatly, and ex...

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Problems solved by technology

[0003] Most of the traditional or existing models are based on causal modeling, and model writing is restrictive. When the framework is changed, the model changes greatly, and experimental testing requires manpower, material resources, and financial resources.

For example, when using Simulink to build a fuel cell model, it is necessary to manually connect or change the lines between modules, which is insufficient in intelligence and automation

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