Intelligent parameter optimization method for thermal management type combined power device

A combined power and thermal management technology, applied in the field of aviation electromechanics, can solve the problems of complex neural network calculation, increased calculation cost, poor experience selection effect, etc., to improve system efficiency, reduce energy consumption, and reduce calculation and time costs. Effect

CN114815600APending Publication Date: 2022-07-29JINCHENG NANJING ELECTROMECHANICAL HYDRAULIC PRESSURE ENG RES CENT AVIATION IND OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2022-07-29

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Abstract

The invention belongs to the technical field of aviation electromechanics, and discloses an intelligent parameter optimization method for a thermal management type combined power device, which comprises the following steps of: determining input and output parameters of each component of the thermal management type combined power device, performing mathematical modeling on the input and output parameters, establishing a system common working equation according to each input and output parameter, and optimizing the parameters of each component; establishing an equation set and a simulation model according to a system balance relation, and solving to obtain an output parameter result of each component; determining a function target, a performance target, an input and output parameter, an optimization parameter and a system constraint condition of the device according to the system requirement of the current working mode; and optimizing the simulation model by applying a particle swarm intelligent algorithm, and finally obtaining system output parameters with optimal energy efficiency. According to the device, an optimization evaluation system with energy consumption as an evaluation index and system requirements as constraint conditions is established, and optimal input parameters meeting the optimization evaluation system are obtained through parameter optimization, so that the energy consumption is reduced, and the system efficiency is improved.
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Description

technical field

[0001] The invention belongs to the technical field of aviation electromechanics, and relates to a parameter optimization method of a power plant, in particular to an intelligent parameter optimization method of a thermal management type combined power plant. Background technique

[0002] The thermal management type combined power unit integrates the aircraft environmental control system and the two power systems. The same compressor can provide compressed air for the environmental control system and the auxiliary power system, and the generator, the compressor and the turbine are coaxially designed. , the mass and volume of the electromechanical system have been reduced, which is in line with the development trend of electromechanical system integration and multi-electronization. At the same time, it also reduces the overall quality of the aircraft and improves the combat performance of the aircraft. It is the focus of future research on aircraft electromecha...

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Embodiment Construction

[0062] This part is an embodiment of the present invention, and is used to explain and illustrate the technical solution of the present invention.

[0063] An intelligent parameter optimization method for a thermal management type combined power plant. The input and output parameters of each component of the thermal management type combined power plant are determined, the above input and output parameters are mathematically modeled, and a system common working equation is established according to the input and output parameters. Establish equations for the relationship between flow balance, power balance and pressure balance, establish a simulation model, and solve to obtain the output parameter results of each component;

[0064] According to the system requirements of the current working mode, the functional objectives, performance objectives, input and output parameters, optimization parameters and system constraints of the device are determined; the particle swarm intellige...