A Comprehensive Review of Lithium-Ion Capacitor Technology: Theory, Development, Modeling, Thermal Management Systems, and Applications.

This review paper aims to provide the background and literature review of a hybrid energy storage system (ESS) called a lithium-ion capacitor (LiC). Since the LiC structure is formed based on the anode of lithium-ion batteries (LiB) and cathode of electric double-layer capacitors (EDLCs), a short overview of LiBs and EDLCs is presented following the motivation of hybrid ESSs. Then, the used materials in LiC technology are elaborated. Later, a discussion regarding the current knowledge and recent development related to electro-thermal and lifetime modeling for the LiCs is given. As the performance and lifetime of LiCs highly depends on the operating temperature, heat transfer modeling and heat generation mechanisms of the LiC technology have been introduced, and the published papers considering the thermal management of LiCs have been listed and discussed. In the last section, the applications of LiCs have been elaborated.

Development, retainment, and assessment of the graphite-electrolyte interphase in Li-ion batteries regarding the functionality of SEI-forming additives.

Formation of a decent solid-electrolyte interphase (SEI) is recognized as an approach to improve the performance of lithium-ion batteries. SEI is a passivation layer generated on the anode during the initial cycles. Characteristics of the graphite SEI depend on the operational parameters, state of the anode, and the content of the electrolyte. Introducing reduction-type additives to the carbonate electrolytes has been one of the most practiced methods to generate an effective SEI on carbonous anodes. To track the role of additives in SEI evolution, first, we have presented a general review on what is currently understood about the SEI formation processes and the impacting parameters. In the second step, the most reported methods to study and analyze the functionality of the SEI-forming additives are classified. As the third part, different reduction-type additives are categorized, and their performances are comparatively reviewed.

Improved Performance of Solid Polymer Electrolyte for Lithium-Metal Batteries via Hot Press Rolling.

Solid-state batteries (SSBs) are gaining attention as they promise to provide better safety and a higher energy density than conventional liquid electrolyte batteries. Solid polymer electrolytes (SPEs) are promising candidates due to their flexibility providing better interfacial contact between electrodes and the electrolyte. However, SPEs exhibit very low ionic conductivity at ambient temperatures, which prevents their practical use in batteries. Herein, a simple and effective technique of hot press rolling is demonstrated to improve ionic conductivity and, hence, the performance of polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP)-based solid polymer electrolyte. Applying hot press rolling to the electrolyte membrane induced structural changes in the grain boundaries, which resulted in a reduction in the crystallinity of the material and, hence, an increase in the amorphous phase of the material, which eased the movement of the lithium ions within the material. This technique also improved the surface of the membrane, making it homogeneous and smoother, which resulted in better interfacial contact between the electrodes and electrolyte. Electrochemical tests were carried out on electrolyte membranes treated with and without hot press rolling to evaluate the effect of the treatment. The hot pressed electrolyte membrane showed significant improvements in its ionic conductivity and transference number. The cycling performance of the LFP/Li batteries using a hot press rolled electrolyte was also evaluated, which gave a specific discharge capacity of 134 mAh/g at 0.1 C. These results demonstrate that hot press rolling can have a significant effect on the electrochemical performance of solid polymer electrolytes.

A hybrid thermal management system for high power lithium-ion capacitors combining heat pipe with phase change materials.

Lithium-ion capacitor (LiC) technology is an energy storage system (ESS) that combines the working mechanism of electric double-layer capacitors (EDLC) and lithium-ion batteries (LiB). When LiC is supposed to work under high power applications, the inevitable heat loss threatens the cell's performance and lifetime. Therefore, a proper thermal management system (TMS) can remove the generated heat of the LiC during high cycling conditions. In this paper, a hybrid TMS (HTMS) using phase change materials (PCM) and six flat heat pipes is proposed to maintain the temperature profile below 40 °C under a high current rate of 150 A for 1400 s profile without any pause. Two K-type thermocouples (T1 & T2) are responsible for monitoring the experiments' temperature evolution in the experiments. Numerical analysis is also performed and verified with experimental results to analyze the temperature profile numerically. The experimental and numerical simulation comprises three case studies, including the cell's temperature under natural convection, temperature distribution when using the heat pipe TMS, and temperature distribution when using HTMS. The results reveal that the HTMS is an exceptionally robust cooling system since it reduces the T1 temperature by 35% compared to the natural convection case study, while the heat pipe TMS can reduce the T1 temperature by 15% compared to the same case study.

Battery lifetime prediction and performance assessment of different modeling approaches.

Lithium-ion battery technologies have conquered the current energy storage market as the most preferred choice thanks to their development in a longer lifetime. However, choosing the most suitable battery aging modeling methodology based on investigated lifetime characterization is still a challenge. In this work, a comprehensive aging dataset of nickel-manganese-cobalt oxide (NMC) cell is used to develop and/or train different capacity fade models to compare output responses. The assessment is conducted for semi-empirical modeling (SeM) approach against a machine learning model and an artificial neural network model. Among all, the nonlinear autoregressive network (NARXnet) can predict the capacity degradation most precisely minimizing the computational effort as well. This research work signifies the importance of lifetime methodological choice and model performance in understanding the complex and nonlinear Li-ion battery aging behavior.