No abstract

To analyze the impact of two commonly neglected electrical abuse operations (overcharge and overdischarge) on battery degradation and safety, this study thoroughly investigates the high current overcharge/overdischarge effect and degradation on 18650-type Li-ion batteries (LIBs) thermal safety. Based on the temperature-voltage behavior and induced thermal runaway (TR) mechanisms, the overcharge and overdischarge-triggered TR processes are divided into four and three stages. Furthermore, the degradation effect is analyzed by analyzing the incremental capacity-differential voltage curves. During the high current cycling process, lithium inventory decreases significantly. Besides, the active material decreases when the battery degrades to a certain level. Lithium plating is the primary reason for lithium inventory loss; the plated lithium grows with the increment of degraded/overcharged level. Besides, the dissolution and deposition affect the internal short circuit degree, which can be observed from the electrode potential and cell voltage value. Moreover, battery cells undergo different degradation degrees, and different current rates of charging/discharging exhibit similar temperature-rising trends during the adiabatic TR tests. However, with the degradation degree increase, battery capacity fades, TR becomes easier to be triggered by the high current rate, and TR reactions are severe. This study guides early quantitative detection, safer battery cell design, and enhanced thermal safety management.

With the proposal of cloud computing, fog computing, and edge computing, various simulation operations are greatly guaranteed, which benefits the multi-model operations of Matlab and CFD. This paper established the 1-D flow network model and 12 cm ∗ 8 cm 3-steady-state PEMFC model. Based on the experiment, the intake flow distribution of the cathode anode of 80 cells is simulated to obtain the maximum and minimum intake flow cell. The 3-D and steady-state single-cell model is used to calculate the cell’s performance, and the performance difference between the two cells is improved by optimizing the size structure of the single cell. The results show that the best version of the cell was obtained when the values of the width and depth were 1.1  mm and 0.8  mm, and the power density difference between the two cells decreased from 5.7% to 2.1%. The voltage difference at 1000 mA·cm−2 current density decreases from 0.065 to 0.035 V after optimization. The intake flow extreme difference of the reactor improved significantly, and C v was reduced by 48.7%.