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一个新的修改了不可理解但可理解的时间逻辑算法,用于模拟固体氧化物燃料电池的模型
Shahr Alshahr1, Fatma A Hashim2,3, Ahmed Alshahir1
1Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka, 72388, Saudi Arabia.
Scientific reports
|July 2, 2025
概括
一个新的REILA算法通过平衡勘探和开发来优化固体氧化物燃料电池 (SOFC) 等效电路. 它在稳态和动态模型中实现了最小的误差,证明了它对现实世界工程问题的有效性.
科学领域:
- 电气工程 电气工程
- 计算智能是一种计算智能.
- 化学工程是化学工程的重要组成部分.
背景情况:
- 准确的等效电路建模对于固体氧化物燃料电池 (SOFC) 性能评估至关重要.
- 优化算法对于SOFCs等复杂系统中的参数估计至关重要.
- 现有的算法可能会与局部最佳情况和平衡勘探/开发阶段作斗争.
研究的目的:
- 引入一个新的优化算法,REILA (随机探索和智能学习算法),用于增强的参数估计.
- 应用REILA来确定SOFC等效电路的最佳参数.
- 通过对基准函数和工程问题的既定算法验证 REILA 的性能.
主要方法:
- 开发REILA算法,将随机收缩策略 (RCS) 纳入勘探和新的开发阶段.
- REILA应用于IEEE CEC'2022测试函数和三个受约束的工程问题.
- 评估REILA在减轻SOFC稳态和动态模型的总平均平方误差 (SMSE) 的有效性.
主要成果:
- 与九个知名的算法相比,REILA在基准函数上的表现优越.
- 该算法在1173K的SOFC稳定状态模型中实现了1.5528e-06的最小适应性函数.
- 使用REILA,动态SOFC模型的最小误差被发现为1.1267.
结论:
- REILA有效地避免了地方解决方案,并在勘探和开采之间取得了良好的平衡.
- 拟议的方法适合,有弹性,并熟练评估SOFC等效电路参数.
- REILA显示了解决现实世界工程优化问题的巨大潜力.
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