Intelligent parameter optimization method for thermal management type combined power device

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.

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...

AI Technical Summary

Problems solved by technology

[0004] 1. For complex systems with multiple inputs and multiple outputs, it is no longer suitable for empirically selected parameters, and it is difficult to specify design point parameters, and because the design parameters are nonlinearly coupled, the empirical selection effect is poor;

[0005] 2. The parameter allocation method selected by expert experience is highly subjective, low in precision, and the number of selected design parameters is small, and the optimization method has chance

[0006] 3. The thermal management combined power plant has the characteristics of nonlinearity and strong coupling. Using the exhaustive method to calculate a large number of design parameters will greatly increase the calculation cost and lower the efficiency

However, this method requires a large number of data samples for training, and the neural network has the characteristics of complex calculations. At present, it is impossible to obtain a large number of data samples required for machine training.

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