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This New AI Might Increase EV Battery Lifespans, Here’s How

Electric mobility is a hot topic these days because of the fact that this is the sort of thing that could potentially end up allowing people to travel without burning harmful fossil fuels. In spite of the fact that this is the case, there is one major issue that is preventing EVs from dominating the transportation market. This issue is that the batteries EVs use to store energy tend to degrade rapidly over time which can be cost prohibitive to repair or replace.

Lithium ion batteries managed to provide a lot more battery life, but overall longevity continued to be an issue. Wear and tear that occurs even when the batteries are not being used can be a huge problem, but with all of that having been said and now out of the way it is important to note that a new AI might be the solution that could take EVs to the next level.

The EU’s funding program called Horizon used algorithms to predict how EV batteries would degrade in various conditions. This can be immensely useful since it can allow consumers to better predict how long their batteries might last than might have been the case otherwise. Additionally, manufacturers can use this information to forecast battery performance and make adjustments that can improve longevity.

The various AI used in this research had a high rate of accuracy, and this provides some hope to the still growing EV sector. There are many who consider electric vehicles the way of the future, but if batteries will degrade unpredictably and without warning this might make it difficult to convert new consumers since the lack of reliability would make them hesitant to take the plunge.

The information is now out there, and it will only be a matter of time before EV manufacturers start to act on it. The changes that this can bring about to the industry will be monumental, but it might stake a long time to gather enough data. Until then, consumers will need to contend with the realities of the industry which aren’t all that dire to begin with.




H/T: ORE

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