Daimler Will Invest $500 Million to a Battery Factory
As the need for plug-in cars increases so does the need for the batteries that run them. There are lithium ion cells used and full battery packs, and some assemble the kits on site.
As the need for plug-in cars increases so does the need for the batteries that run them. There are lithium ion cells used and full battery packs, and some assemble the kits on site. Deutsche Accumotive is going to triple the number of batteries they will produce. A second battery plant is going to be built and will cost around 500 million Euro. Lithium ion cells will be brought in from South Korea and then assembled before use.
Ironically, Li-Tec the Daimler cell subsidiary shut down last year as it was too expensive to make the cells in Germany. Production is expected to begin next year and work on the building in Saxony will start later in the year, and the batteries will go into both battery electric and plug-in cars.READ ALSO: Mercedes-Benz is kicking Robots Off the Assembly Line
Accumotive has been producing battery packs since 2009 but does not make the lithium ions cells rather they bring them in. Samsung has also provided cells for Daimler and SK Innovation have been chosen to be the company who will provide the cells, but there are few other details available. Tesla Motors had been the supplier in the past and these used Panasonic cells when they produced the last batch of Smart ForTwo electric cars.
Harald Kroger believes that they will be able to increase production regularly over the years and, as a result, Daimler is following General Motors who eight years ago set out the bidding process for contractors to compete for the work of providing the cells.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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