12v lithium battery pack capacity improvement method

"Lithium-Ion Battery Capacity Prediction Method Based on Improved Extreme Learning Machine." ASME. . February 2025; 22 (1): 011002. Currently, research and applications in the field of capacity prediction mainly focus on the use and recycling of batteries, encompassing topics such as SOH estimation, RUL prediction, and echelon use.

Considering the limited voltage and capacity of one single lithium-ion battery cell, hundreds to thousands of cells are usually connected in series or parallel as the power unit to provide sufficient power for EVs.

To complete the battery pack model, we need to know how different cell capacities combine to give the overall capacity Q. Going back to our analogy at the start of the post, we can see that the capacity of each cell arrangement in parallel will sum up. But how about those arrangements in series?

However, there is scant research and application based on capacity prediction in the battery manufacturing process. Measuring capacity in the grading process is an important step in battery production. The traditional capacity acquisition method consumes considerable time and energy.

The manufacturing process of LIBs is divided into three stages: electrode production, battery assembly, and battery activation . In battery activation, the electrolyte is injected. Subsequently, formation and grading are conducted .

The final purpose of evaluating the battery pack consistency is to obtain its energy storage and power output capacity, that is, the maximum available energy Emax when the battery is fully charged and Pmax at a specific SOC point.