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18650 Lithium-ion batteries are wildly used as power sources for portable electronics because of the standardized format and economical manufacturing cost. However, commercial 18650 cells come in various designs due to the implementation of different protection devices. The current interrupt device and top vent are mandatory protection devices for all commercial 18650 Li-ion batteries. In contrast, the positive temperature coefficient thermistor, bottom vent, and protection circuit are optional protection devices that can be non-installed, installed separately, or combined in commercial 18650 batteries. Four representative commercial 18650 Li-ion batteries were disassembled and compared in terms of the similarities and differences of the protection devices. This paper overviews the working mechanism, advantages, and drawbacks of each protection device. Recommendations on battery selection and potential future trends are then provided.

Electric vehicles (EV) are considered the future of the automobile industry due to their high energy conversion efficiency and environmental friendliness. However, there are safety risks associated with Li-ion batteries, including the potential for fires and explosions. This paper reviews the challenges facing the electric vehicle market regarding the implementation of Li-ion batteries. It then presents two case studies of electric vehicles that experienced safety-related recalls which were not associated with vehicle collisions. For comparison, a history of Li-ion battery safety issues from the same brand in other applications than EV and the company’s reactions are provided. The case study and review of issues in other applications show a lack of consideration for customer safety, amplified by the additional risk used in an EV. The paper then explores corrective actions performed and analyzes how the actions will not address the root cause; additionally, contributing to a performance reduction. Recommended corrective actions for future implementation of EV batteries are provided.

Battery explosion incidents hinder the development and application of Li-ion batteries. This paper describes the use of nondestructive computed tomography (CT) to analyze cylindrical Li-ion battery samples that underwent thermal runaway and exploded. Unlike destructive analysis methods, which can lead to a loss of battery structural information, CT scan allows direct observation of a battery’s internal structure without disassembly. In this study, two case studies of 20700 and 18650 batteries show that sidewall and bottom case rupture was caused by blockage of the battery vent region, which prevented the release of the generated gas. This work demonstrates the ability of CT for post-mortem incident analysis and the limitations of current vent design, and also gives insight to a safety issue with some cylindrical batteries.

Cylindrical Li-ion batteries (cells) typically have safety vents in the positive terminal to enable the release of gases that build up inside the battery and thus help reduce the effects of thermal runaway, including fire and explosion. However, the vents are not always effective, and it is critical to understand why. This paper overviews various vent designs and presents two case studies of vents in cylindrical Li-ion batteries that failed to operate properly. The first case study concerns a Sony VCT5 18650 Li-ion battery in which thermal runaway caused the cylindrical casing (can) to rupture. The second case study involves an Ampking 20700 Li-ion battery in which thermal runaway caused side-wall rupture of the casing. In both cases, the vents did not function as intended. Computed tomography (CT) scanning was used to investigate the internal structure of the battery to assess the failure mechanisms of the failed vents. These cases raise concerns about the efficiency, reliability, and safety of some current vent designs.

Li-ion battery reliability has attracted significant research attention, but few studies have incorporated in-service performance and reliability data of batteries installed within a product. This paper investigates battery drain, unexpected shutdowns, and slow performance associated with Li-ion batteries, with a focus on Apple iPhones ® as a case study. The actions taken by Apple in response to these performance issues are discussed, especially from the perspective of Li-ion battery degradation. It is shown that not all battery reliability issues can be attributed to normal battery degradation; battery manufacturing defects and high C-rate applications are also shown to be contributors to battery reliability and performance issues, including those causing a low state of charge, a low state of health, and unexpected shutdowns.

The purpose of this study is to determine a method for quickly and accurately estimating the chlorophyll content of peanut plants at different plant densities. This was explored using leaf spectral reflectance to monitor peanut chlorophyll content to detect sensitive spectral bands and the optimum spectral indicators to establish a quantitative model. Peanut plants under different plant density conditions were monitored during three consecutive growth periods, single-photon avalanche diode (SPAD) and hyperspectral data derived from the leaves under the different plant density conditions were recorded. By combining arbitrary bands, indices were constructed across the full spectral range (350&ndash, 2500 nm) based on blade spectra: the normalized difference spectral index (NDSI), ratio spectral index (RSI), difference spectral index (DSI) and soil-adjusted spectral index (SASI). This enabled the best vegetation index reflecting peanut-leaf SPAD values to be screened out by quantifying correlations with chlorophyll content, and the peanut leaf SPAD estimation models established by regression analysis to be compared and analyzed. The results showed that the chlorophyll content of peanut leaves decreased when plant density was either too high or too low, and that it reached its maximum at the appropriate plant density. In addition, differences in the spectral reflectance of peanut leaves under different chlorophyll content levels were highly obvious. Without considering the influence of cell structure as chlorophyll content increased, leaf spectral reflectance in the visible (350&ndash, 700 nm): near-infrared (700&ndash, 1300 nm) ranges also increased. The spectral bands sensitive to chlorophyll content were mainly observed in the visible and near-infrared ranges. The study results showed that the best spectral indicators for determining peanut chlorophyll content were NDSI (R520, R528), RSI (R748, R561), DSI (R758, R602) and SASI (R753, R624). Testing of these regression models showed that coefficient of determination values based on the NDSI, RSI, DSI and SASI estimation models were all greater than 0.65, while root mean square error values were all lower than 2.04. Therefore, the regression model established according to the above spectral indicators was a valid predictor of the chlorophyll content of peanut leaves.

One of the root causes of lithium battery failure is lithium dendrite formation. Dendrites can result in internal short circuits and ultimately thermal runaway, fires, and explosions. Unfortunately, it has been difficult to study dendrites due to an inability to conduct in-situ observations. This paper presents an in-situ observation approach, consisting of an optically transparent lithium battery cell to observe dendrite growth evolution while concurrently monitoring the electrical characteristics of the cell under various current densities.