Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm

LI Li; CHEN Can; LI Can; GAO Feifan; CHEN Zhuaixia; LIU Yang; ZHOU Hongxi

doi:10.11959/j.issn.1000-0801.2024145

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Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm

Research and Development | 更新时间：2024-08-05

- Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm
- Telecommunications Science Vol. 40, Issue 5, Pages: 121-130(2024)
- 作者机构：
  
  国家电网有限公司信息通信分公司，北京 100761
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2024145
  CLC： TM4
- Received：23 January 2024，
  
  Revised：09 May 2024，
  
  Published：20 May 2024
- 稿件说明：
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李黎,陈灿,李灿等.基于改进遗传算法的双向DC-DC变换器控制策略研究[J].电信科学,2024,40(05):121-130.

LI Li,CHEN Can,LI Can,et al.Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm[J].Telecommunications Science,2024,40(05):121-130.
李黎,陈灿,李灿等.基于改进遗传算法的双向DC-DC变换器控制策略研究[J].电信科学,2024,40(05):121-130. DOI： 10.11959/j.issn.1000-0801.2024145.

LI Li,CHEN Can,LI Can,et al.Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm[J].Telecommunications Science,2024,40(05):121-130. DOI： 10.11959/j.issn.1000-0801.2024145.

摘要

选取双向DC-DC变换器为研究对象，根据混合储能系统中储能元件和耗能元件的连接拓扑结构确定在不同能量流动方向上的功率需求指标，确定变换器主要元件的参数和合适的电路元件。搭建降压/升压（buck/boost）电路模型，并设计自适应快速终端滑模控制策略，提出改进遗传算法对控制器的参数进行优化。由于不同控制参数的控制效果不同，为了获得更好的电压输出特性，对自适应快速终端滑模控制策略进行参数优化，并通过仿真验证了该方法具有良好的控制性能。

Abstract

The bidirectional DC-DC converter was selected as the research object. Based on the connection topology of energy storage and consumption components in the hybrid energy storage system

power demand indicators were determined for different energy flow directions

and the parameters of the main converter components and appropriate circuit components were established. A circuit model of buck/boost was constructed

and an adaptive fast terminal sliding mode control strategy was designed. The controller parameters were optimized using an improved genetic algorithm. Different control parameters have different control effects. In order to obtain better voltage output characteristics

the parameters of the adaptive fast terminal sliding mode control strategy were optimized.The proposed method can be verified to exhibit good control performance through simulation.

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references

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