Serbian Battery Developer ElevenEs Will Build a Gigafactory with Support from EIT InnoEnergy

Battery developer ElevenEs announced on October 21 that it will build a battery manufacturing plant in Serbia with the financial backing from renewable energy investor EIT InnoEnergy. ElevenEs a spin-off from Al Pack Group, a Serbian aluminum processor. EIT InnoEnergy is a European consortium that provides funding and education to those who seek to build eco-friendly businesses. The proposed plant is to be located in the city of Subotica and have a total annual production capacity of 16GWh.

The battery developer has already set up an R&D facility near the plant site, which was chosen because of its close proximity to natural lithium deposits. Serbia actually possesses one of the world’s largest sources of lithium, and its government has just begun to tap into this resource. According to the reporting by various websites covering news about renewable energy and electric vehicles, the existing battery production line operated by ElevenEs near the site of the proposed plant will scale up to 300MWh. Then in 2024, the company will formally begin the construction of its battery manufacturing plant, setting up 8GWh in the initial phase and eventually raising the production capacity of the plant to 16GWh. The company told news media that the entire plant will run wholly on renewable energy. The products that the plant will be manufacturing are batteries for energy storage systems and electric vehicles. The production capacity of the plant is expected to meet the demand of more than 300,000 electric vehicles per year.

Commenting on the development of this project, Nemanja Mikac, founder and CEO of ElevenEs, emphasized the LFP battery technology that his company has been developing. He listed several advantages that LFP has over other lithium battery technologies. First, LFP offers twice as long operational lifespan. An LFP battery can be repeatedly charged up to 6,000 times while maintaining 100% state-of-charge. Furthermore, LFP charges much faster. Another major advantage is a higher level of safety due to a higher level of thermal stability. An electric vehicle that adopts LFP has a lower risk of suddenly catching fire due to a battery malfunction. Finally, LFP beats other lithium battery technologies in terms of cost. The cathode materials of most kinds of lithium batteries require cobalt, which is difficult to obtain. LFP is cobalt-free and is made from metals that are plentiful and relatively cheap.

Mikac pointed out that China is currently the leader with respect to development of lithium battery technologies, and LFP has become the “popular choice” there. Tesla, for instance, has adopted LFP for its vehicles manufactured and sold in that country.

Jakub Miler, CEO of EIT InnoEnergy Central Europe, added that LFP is the “next big thing” in the battery market. While acknowledging that lithium batteries with a nickel-based cathode still offer a higher energy density compared with LFP batteries, Miler argued that LFP is the better choice for electric vehicles that are not designed for long-range trips because of its advantages pertaining to lifespan, safety, and cost. He also noted that LFP is also highly suitable for energy storage and other industrial applications.

ElevenEs offers prismatic and pouch cells. The company has developed a battery manufacturing process as well as a recycling process for the aluminum in its battery packs. The proposed gigafactory could initiate the formation of a battery industry cluster in Serbia, thereby bringing significant economic benefits to the country. However, Serbian government is facing considerable public opposition to lithium mining. A referendum is expected to be held on the proposed Jadar lithium mine that will be situated in western part of the country and developed by Rio Tinto starting in 2022. The multi-billion project appears to have been officially approved despite popular protests. On the whole, whether Serbia will be able to establish a world-class lithium battery industry depends on many variables.

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