基于改进蜜獾算法的温差发电MPPT控制方法

刘新宇; 孟启蒙; 徐斌; 李继方; 黄心洋; 杨文静

doi:10.19912/j.0254-0096.tynxb.2025-0801

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基于改进蜜獾算法的温差发电MPPT控制方法

更新时间：2026-10-15

- 基于改进蜜獾算法的温差发电MPPT控制方法
- Vol. 47, Issue 9, Pages: 620-627(2026)
- 作者机构：
- 作者简介：
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- DOI：10.19912/j.0254-0096.tynxb.2025-0801
  CLC： TM913
- Online First：10 October 2026，
  
  Published：2026
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刘新宇, 孟启蒙, 徐斌, et al. 基于改进蜜獾算法的温差发电MPPT控制方法[J]. 2026, 47(9): 620-627.
DOI：

刘新宇, 孟启蒙, 徐斌, et al. 基于改进蜜獾算法的温差发电MPPT控制方法[J]. 2026, 47(9): 620-627. DOI： 10.19912/j.0254-0096.tynxb.2025-0801.

摘要

针对温差发电系统在非均匀温度条件下存在的多峰值功率跟踪问题

提出一种改进蜜獾算法（IHBA）与恒定电压法（CVT）相结合的混合控制策略。在Matlab/Simulink平台搭建仿真模型

测试结果表明：恒温条件下跟踪精度达98.9%

响应时间0.04 s;动态温度变化及负载突变工况下平均响应时间小于0.05 s。实物测试验证算法在温度恒定条件下的实用性

跟踪精度达99.3%且无超调。相比传统CVT、粒子群优化算法（PSO）等方法

该方法在跟踪精度、响应速度、稳定性和鲁棒性方面均表现出显著优势。

Abstract

To address the multi-peak power tracking problem of thermoelectric generation systems under non-uniform temperature conditions

a hybrid control strategy combining an improved honey badger algorithm （IHBA） with constant voltage tracking （CVT） is proposed. A simulation model is built on the Matlab/Simulink platform. Test results show that the tracking accuracy is 98.9% and the response time is 0.04 seconds under constant temperature conditions. The average response time under dynamic temperature change and sudden load mutation conditions is less than 0.05 seconds. Physical tests verify the practicality of the algorithm under constant temperature conditions

and the tracking accuracy reaches 99.3% without overshoot. Compared with traditional methods such as CVT and PSO

this approach demonstrates significant advantages in tracking accuracy

response speed

stability

and robustness.

关键词

Keywords

references

Zhao Y L, Zhang G Y, Wen L, et al.Experimental study on thermoelectric characteristics of intermediate fluid thermoelectric generator[J]. Applied Energy, 2024, 365: 123263.

Chen Y F, Xie C J, Li Y, et al.An improved metaheuristic-based MPPT for centralized thermoelectric generation systems under dynamic temperature conditions[J]. Energy, 2023, 277: 127485.

Pandit S, Mal R, Purwar A, et al.Waste heat regeneration from thermoelectric generator based improved biomass cookstove (TIBC): modelling of TEG system utilizing DC-DC converter with fuzzy logic MPPT[J]. Energy Conversion and Management, 2024, 300: 117977.

Khan N, Ahmed A, Haider S, et al.Hybrid general regression NN model for efficient operation of centralized TEG system under non-uniform thermal gradients[J]. Electronics, 2023, 12(7): 1688-1710.

Ding N, Cai Y Y, Deng F.Temperature-based thermo-electric coupling maximum power point tracking algorithm for thermoelectric generation systems under transient conditions[J]. Applied Thermal Engineering, 2023, 230: 120684.

Jang Y, Lee C, Bae S.Linear-extrapolation-based gray-wolf optimization algorithm for global maximum power tracking of thermoelectric generators[C]//2024 IEEE Power & Energy Society General Meeting (PESGM). Seattle, WA, USA, 2024: 1.

刘新宇, 李格, 李继方, 等. 基于混合算法的温差发电系统最大功率跟踪控制研究[J]. 太阳能学报, 2025, 46(8): 606-611.

Yang B, Wu S C, Li Q, et al.Jellyfish search algorithm based optimal thermoelectric generation array reconfiguration under non-uniform temperature distribution condition[J]. Renewable Energy, 2023, 204: 197-217.

樊立萍, 陈其鹏. 基于萤火虫优化模糊P&O的微生物燃料电池最大功率点跟踪[J]. 太阳能学报, 2024, 45(4): 373-381.

Hashim F A, Houssein E H, Hussain K, et al.Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems[J]. Mathematics and Computers in Simulation, 2022, 192: 84-110.

戴春雨, 马廉洁, 蒋涵存, 等. 基于多种策略改进的鲸鱼优化算法[J]. 计算机工程与科学, 2024, 46(9): 1635-1647.

薛阳, 燕宇铖, 贾巍, 等. 基于改进灰狼算法优化长短期记忆网络的光伏功率预测[J]. 太阳能学报, 2023, 44(7): 207-213.

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