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Sino Science&Technology Battery Co.,ltd is a high-tech production enterprise which specialize in the R&D and production of Lifepo4 batteries,energy storage battery,portable UPS power supply,personalized customization lithium battery pack etc .

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Shenzhen Green Power Energy Battery Co.,ltd specializes in a wide range of digital battery such as environmental cylindrical 18650 21700 32700 26650 14500 18500 lithium ion rechargeable battery, LifePO4 battery, 3.7V lithium polymer battery, NiMH battery, NiCD battery, dry cell battery, alkaline battery, heavy duty battery, button cell battery etc. we devote to R&D, innovation, production & sales. With automatic production machines we have been exported goods to all over the world over 15years. We have complete exported certificate such as KC, CE, UL, BSCI, ROHS, BIS, SGS, PSE etc

Dongguan Datapower New Energy Co.,ltd is a high-tech production enterprise which specialize in the R&D and production&sale of lithium polymer batteries,drone battery,airplane batteries &battery pack etc.

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source:Industry News release time:2024-01-02 Hits: Popular:AG11 battery

Recently, a research team from Stanford University, MIT and Toyota Research Institute developed an AI algorithm that can predict battery life, thereby helping manufacturers reduce battery production and management costs.
The team collected various parameters of the battery for 5 charge and discharge cycles to determine the battery life. The accuracy of the judgment results was as high as 95%, and the error between the predicted value and the actual battery life value was within 9%. In addition, the researchers said they have also found a way to optimize battery charging speed, which may significantly improve battery charging time.
This battery life judgment algorithm can speed up the development time of new battery designs and other applications, and also provides an effective method for judging whether electric vehicle batteries can continue to be used. For OEMs, using this new technology speeds up battery time to market while also reducing production costs. It is reported that the research team has made the data set derived from the study public, and it is expected to be commercially available on a small scale soon.
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