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arXiv 1906.05028physics.app-phcond-mat.mtrl-sci
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最大功率点跟踪期间的瞬态分析(TrAMPPT)以评估钙钛矿太阳能电池的动态响应

Transient Analysis during Maximum Power Point Tracking (TrAMPPT) to Assess Dynamic Response of Perovskite Solar Cells

Aniela Czudek, Katrin Hirselandt, Lukas Kegelmann, Amran Al-Ashouri, Marko Jošt, Weiwei Zuo, Antonio Abate, Lars Korte, Steve Albrecht, Janardan Dagar, Eva L. Unger

摘要:

钙钛矿太阳能电池的器件性能参数的确定远非微不足道,因为瞬态效应可能导致作为扫描速率和预调节的函数的电流-电压测量的大的差异。最大功率点跟踪(MPPT)能够确定稳态最大功率转换效率。然而,MPPT不提供任何关于器件性能参数的信息,这些参数只有在从稳态条件下收集的电流-电压曲线中提取时才可靠。我们表明,是可能的,以确定较短的建立或延迟时间适合进行J-V测量在稳态条件下通过分析周围的MPP的瞬态器件响应。该过程被证明比在各种扫描速率下的测量J-V测量更省时。此外,这里提出的通用算法可以实现,以评估长期设备老化期间设备的动态响应的变化。

英文摘要:

Determination of the device performance parameters of perovskite solar cells is far from trivial as transient effects may cause large discrepancies in current-voltage measurements as a function of scan rate and pre-conditioning. Maximum power point tracking, MPPT, enables to determine the steady-state maximum power conversion efficiency. However, the MPPT does not provide any information on the device performance parameters, which are reliable only if extracted from current-voltage curves collected under steady-state conditions. We show that is possible to determine the shorter settling or delay time suitable to carry out J-V measurements under steady-state conditions by analysis of the transient device response around the MPP. This procedure proves to be more time-efficient than measurement J-V measurements at a variety of scan rates. Furthermore, the generic algorithm presented here can be implemented to assess changes in the dynamic response of devices during long-term device ageing.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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