In recent years, with the swift progression of electric vehicles, new energy storage, intelligent robots and other fields, lithium-ion batteries have been widely used to meet the needs of high energy density, high out...
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In recent years, with the swift progression of electric vehicles, new energy storage, intelligent robots and other fields, lithium-ion batteries have been widely used to meet the needs of high energy density, high out...
In recent years, with the swift progression of electric vehicles, new energy storage, intelligent robots and other fields, lithium-ion batteries have been widely used to meet the needs of high energy density, high output voltage and wide operating range of the battery. Typically, lithium-ion batteries operate under complex conditions and are accompanied by physical and chemical changes within them. These factors lead to irreversible physical and chemical changes in lithium-ion batteries, and their potential pitfalls can lead to abnormal system operation and even catastrophic events in electrical systems. Therefore, accurate RUL prediction can effectively indicate the health condition of Li-ion battery, and at the same time can ensure the reliability and safety of the system, which is important for the safe operation of the whole Li-ion battery system, and its remaining life assessment has become a research hotspot in the related fields of electrochemistry, intelligent detection and reliability, and has a good development prospect. Therefore, this paper analyzes the common methods and application status of remaining life prediction of lithium-ion batteries, brings together the prediction methods based on model-based methods, data-driven methods and fusion-based methods, and analyzes the advantages and disadvantages of each method to provide reference for relevant technical personnel.
Picea mongolica W. D. Xu. is an endemic species in China. The spruce forest is only found in semi-arid habitat in Inner Mongolia Autonomous Region of China. Based on the simulative defoliation experiment, it was prove...
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Picea mongolica W. D. Xu. is an endemic species in China. The spruce forest is only found in semi-arid habitat in Inner Mongolia Autonomous Region of China. Based on the simulative defoliation experiment, it was proved that Picea mongolica seedlings had the compensatory and overcompensatory effects under the certain defoliation rate. The results of variance analysis on growth indexes showed that in PM Ⅰ(natural regeneration seedlings under Picea mongolica forest), the differences of H 1(height in June 23) and H 2(height in September 3) were extremely significant, and the difference of D(diameter at the breast height) were not significant. In PM Ⅱ(artificial regeneration seedlings under Betula platyphylla Suk. forest), the difference of H 1 was significant, the difference of H 2 was not significant, and the difference of D was extremely significant. The regression equations were established and the compensatory and overcompensatory points were obtained. In PM Ⅰ, the compensatory points of H 1, H 2, and D were 0.7628, 0.7436, 0.5725, and the overcompensatory points were 0.6056, 0.5802 and 0.2909 respectively. In PM Ⅱ, the compensatory points of H 1, H 2, and D are 0.5012, 0.3421, 0.2488, and the overcompensatory points are 0.4137, 0.2633 and 0.0747 respectively. These results suggested that the induction of compensatory growth mechanisms in spruce seedlings required a threshold level of defoliation, and the insects in Picea mongolica forest could be controlled in a certain degree.
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