Abstract

Due to the rising interest in electric vehicles, the demand for more efficient battery cells is increasing rapidly. To support this trend, battery cells must become much cheaper and “greener.” Energy consumption during production is a major driver of cost and CO <formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex>$_2$</tex></formula> emissions. The drying production step is one of the major energy consumers and cost drivers. The technological approach of “dry coating” allows the energy-intensive drying step to be eliminated for significant energy and cost savings. However, there are numerous emerging dry coating technologies that differ significantly in physics, chemistry, and readiness levels. Moreover, typical methodological procedures for technology selection remain less applicable to the early stages of technological development. Both issues raise the questions, “What is the most promising dry coating technology?” and “How do we identify it?” To answer these questions, a comprehensive, systematic technology benchmark was conducted. Following a four-step analytical approach, based on the nominal group technique, qualitative content analysis, and multicriteria decision analysis, different dry coating technologies were identified, analyzed, and cross-compared. This was performed qualitatively and quantitatively. We also forecast which factor will impact the application of the most promising technologies for CO <formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex>$_2$</tex></formula> emission rate reductions and cost savings in 2030. In summary, four different technologies were identified with a high chance of technological breakthrough within the next 3–5 years. By applying these technologies, 4.76 million tons of CO <formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex>$_2$</tex></formula> could be saved per year by 2030.

Highlights

  • T HE international demand for electric vehicles is rising rapidly, and the demand for battery cells with it, especially for lithium-ion battery cells [1]

  • The technological readiness level (TRL) was used as a quantification indicator for the level of technological development

  • The classification of TRLs is challenging because each technology can only be rated qualitatively

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Summary

Introduction

T HE international demand for electric vehicles is rising rapidly, and the demand for battery cells with it, especially for lithium-ion battery cells [1]. Tesla’s CEO Elon Musk even predicts a future demand of 10 000 GWh/a [4] without naming an exact year. This overall development might be beneficial in Manuscript received January 10, 2021; revised May 20, 2021, September 2, 2021, and November 17, 2021; accepted January 16, 2022. Review of this manuscript was arranged by Department Editor S.

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