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Long-Lasting 12v 200ah Forklift Battery with Innovative Storage Design

Categories 12V Lithium Iron Phosphate Battery
Brand Name: EWT
Model Number: LFP 12V 200AH
Certification: UL UN38.3 IEC62133 CE ISO9001
Place of Origin: China
MOQ: 100
Price: 385USD/pc for 10-100pcs
Payment Terms: T/T
Supply Ability: 50000/DAY
Delivery Time: 7-12 delivery days
Packaging Details: carton box+paper box
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Long-Lasting 12v 200ah Forklift Battery with Innovative Storage Design

New Design Storage Rechargeable 12v 200ah For Forklift Batteries


species

Lithium Iron Phosphate


Voltage

32700-12V

capacity

200AH

Batteries

IFR32700 3.2V 6Ah

size

521*238*218mm

weight

24KG

Maximum charging current

100A

Maximum discharge current

150A



Display screen

No

Communication support

No

As the demand for EV batteries continues to grow, researchers at the University of Michigan have developed a method to predict how changes in manufacturing processes and materials will affect battery life.

Engineers at the University of Michigan have determined that the internal resistance, measured immediately after the battery is made, is a key measure of battery life. Measurements can be made in seconds at the end of the manufacturing process at little to no additional cost.

Previous studies have shown that lifetime prediction is possible, but it requires repeated cycles – charging, discharging, and recharging – to collect the data needed to train the algorithm. The aging tests required to determine lifespan can take weeks to months to complete. For this reason, the test was conducted only on a small number of cells, not all of the resulting cells.

But this new study, recently published in the journal Joule, shows that accurate battery life can be predicted with the help of a resistance measurement, or rather a measure of how well a battery resists the flow of current inside it. This resistance can come from the material of the internal components, or from electrochemical factors that affect the movement of ions between the battery electrodes. Measuring resistance at low charge levels is key.

Andrew Weng, the study's lead author and PhD student in mechanical engineering, said: "In principle, resistance measurements in the low-charge state can be obtained without any cycles, which makes the model training process faster. "

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