Multi-objective Pareto optimal control method of inverter based on immune algorithm

Abstract

The invention relates to a multi-objective Pareto optimal control method of an inverter based on an immune algorithm, and the waveform quality of output current of the inverter and the multi-objective optimal control sequence of switching losses can be solved by adopting the immune algorithm. A waveform quality objective of output current is portrayed by output waveform quality evaluation function of the inverter, a switching losses objective is portrayed by SwitchingLosses evaluation function and gives Pareto optimal solution set in the form of the Pareto frontier, and designers can select out the most satisfactory solution of an optimal design from the Pareto optimal solution set according to wills and the degree of emphasis of each goal. According to the multi-objective Pareto optimal control method of the inverter based on the immune algorithm, losses of the inverter can be real-timely calculated due to the fact that characteristics and parameters of a device, load current, a switch gate pole drive signal and direct current bus voltage are provided by a calculation data sheet. Therefore, the multi-objective Pareto optimal control method of the inverter based on the immune algorithm has the advantages of having operability. Moreover, compared with the modeling approach of a physical model and a functional model, the multi-objective Pareto optimal control method of the inverter based on the immune algorithm is more suitable for actual engineering applications and has a potential for online monitoring.

Description

technical field [0001] The invention relates to an inverter multi-objective Pareto optimal control method, in particular to an inverter multi-objective Pareto optimal control method based on an immune algorithm. Background technique [0002] With the adjustment of the energy structure and the rapid increase in power demand, in order to use electric energy efficiently, there is a large demand for systems that can convert voltage and frequency. Inverters can meet the requirements of electric energy conversion, so they have attracted much attention. Two of the hot issues in current inverter research are how to improve the quality of the inverter output waveform and how to reduce the loss of the inverter. [0003] When the inverter improves the output waveform quality, dynamic response characteristics and reduces the volume of the inverter by increasing the switching frequency of the power electronic device, it will inevitably lead to excessive switching loss. The loss not onl...

AI Technical Summary

Problems solved by technology

Jia Jiabin and others used the genetic algorithm (genetic algorithm, GA) algorithm to adopt the weight coefficient method to find the optimal control strategy of the multi-objective (THD and Switching losses) of the inverter, but the weight coefficient method itself relies on a large amount of prior knowledge, and the multi-objective function The solution is the only one that does not conform to the actual situation. At the same time, it does not analyze the different load conditions. The related research is only a qualitative analysis of the loss, and does not use an accurate method to calculate

Ramachandran et al. proposed to use immune algorithm (IA) for inverter control, mainly to overcome the shortcomings of GA such as slow convergence speed and insufficient local search ability.

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