建筑物的RC热模型的参数输入估计,使用未闻卡尔曼波器和非线性最小平方方法
Vahid Zamani1, Shaghayegh Abtahi1, Yuxiang Chen1
1Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Canada.
概括
本研究引入了一种使用无气味卡尔曼波器 (UKF) 和非线性最小正方形 (NLS) 的新方法,以准确估计构建电阻电容器 (RC) 热模型的参数和输入,即使缺少温度数据.
科学领域:
- 建筑能源系统 建筑能源系统
- 热建模 热建模
- 系统识别 系统识别
背景情况:
- 有效的建筑能源管理依赖于准确的热模型.
- 电阻电容器 (RC) 模型在计算上是高效的,但在参数和输入估计方面面临挑战,特别是缺少状态数据.
研究的目的:
- 开发和评估一个可靠的方法来估计RC热模型的参数和输入.
- 为了解决建筑热建模中不可用温度状态的挑战.
- 为了实现RC模型参数的及时在线更新,以改善预测.
主要方法:
- 使用无气味卡尔曼波器 (UKF) 与非线性最小正方形 (NLS) 结合.
- 开发了一种同时估计RC模型参数和输入的程序.
- 通过两个案例研究验证了该方法:一个合成RC模型和一个独立住宅的监控数据.
主要成果:
- 拟议的UKF-NLSs方法有效估计了RC模型参数和输入.
- 即使在某些温度状态不可用时,也实现了成功的估计.
- 案例研究通过将估计值与真实值进行比较来证明该方法的能力.
结论:
- 开发的方法为RC热模型中的参数和输入估计提供了可靠的方法.
- 该技术有效地处理缺失的温度状态数据,这是现实世界的应用中常见的问题.
- 这种方法促进了在线模型更新,提高了建筑能效预测的准确性.
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