Nonlinear Frequency Response Analysis for process identification and characterization of Li-ion batteries

锂离子电池是电动汽车和缓冲间歇性可再生能源的关键（未来）组件。为了提高它们的能量密度和节省成本，开发了改进的电极和电池设计。此外，现有电池优选地在其性能极限下操作，这导致老化和安全问题。在这两种情况下，都迫切需要非破坏性的操作分析，以提供对电池中物理和化学过程的深入和特别是定量的了解，以及电池设计和操作模式如何影响它们。只有电压和电流可以容易地测量，并且电化学阻抗谱，一种线性分析方法，经常用于此目的。然而，不同的状态和效应可以导致相似的光谱。为了解决这些限制，非线性方法，特别是非线性频率响应分析（NFRA），在这个项目中使用。分析的高次谐波响应包含非线性过程的信息，特别是高度非线性反应动力学，和表面状态。因此，NFRA是诊断电池的一种非常强大和有前途的工具，但目前几乎不为人所知。目前，还没有共同的理解如何NFRA光谱应该被测量和-更重要的-分析。这些是妨碍社区更广泛接受这一方法的主要障碍。在本项目中，将采用KIT和MPI开发的不同NFR方法进行电池分析。第一次，将研究阳极和阴极的NFR谱，以区分它们在电池信号中的贡献;此外，评估先前未分析的相位信息和DC分量的信息内容。将确定高阶频率响应函数，其类似于阻抗，不依赖于振幅，但包含非线性响应的信息。模型的解析解和数值解将用于再现和解释实验光谱。因此，该项目建立了一个系统的方法，通过非线性频率响应分析的电池（状态）信息的最佳提取，并铺平了道路，广泛的分析这一新技术。

Li-ion batteries are crucial (future) components for electromobility, and for buffering intermittent renewables. To increase their energy density and save costs, improved electrode and cell designs are developed. Furthermore, existing cells are preferably operated at their performance limits, which leads to aging and safety issues. In both cases, there is urgent need for non-destructive operando analysis that provides in-depth and especially quantitative understanding of the physical and chemical processes in the batteries, and how cell design and operating mode impact them. Only voltage and current can be readily measured, and electrochemical impedance spectroscopy, a linear analysis method, is frequently used for this purpose. Yet, various states and effects can cause similar spectra. To address these limitations, nonlinear methods, in particular nonlinear frequency response analysis (NFRA), is used in this project. The analysed higher harmonic responses contain information on nonlinear processes, especially the highly nonlinear reaction kinetics, and on surface states. NFRA is thus an extremely powerful and promising tool to diagnose batteries, but currently barely understood. Presently, there is no common understanding how NFRA spectra should be measured and - more importantly - analysed. These are main obstacles hindering broader acceptance of this method in the community. In this project different NFR approaches, developed at KIT and MPI will be employed for battery analyses. For the first time, NFR spectra of anode and cathode will be studied to discriminate between their contributions in the cell signal; further, the previously not analysed phase information and DC component is evaluated regarding information content. Higher order frequency response functions, which analogously to impedance are not amplitude-dependent but contain information on the nonlinear response will be determined. Analytical and numerical solutions of models will be used to reproduce and interpret the experimental spectra. Resultingly, the project establishes a systematic methodology for optimal extraction of battery (state) information by nonlinear frequency response analysis, and paves the way for a wide-spread analysis of this new technique.