A team at the University of Münster has reviewed 53 studies that provide time- or technology-specific cost estimates for lithium-ion, solid-state, lithium–sulfur and lithium–air batteries among more than 2,000 publications related to the topic.
In an effort to provide a degree of transparency to the large variance of forecasted costs due to differences in methods and assumptions, the Münster team clustered the papers according to four applied forecasting methods: technological learning; literature-based projections; expert elicitations; and bottom-up modeling.
Further, the researchers consolidated 360 extracted data points into a pack cost trajectory that reaches a level of about $70 (kWh)−1 in 2050, and 12 technology-specific forecast ranges that indicate cost potentials below $90 (kWh)−1 for advanced lithium-ion and $70 (kWh)−1 for lithium-metal based batteries.
Overview of time-specific and technology-specific forecasts. Mauler et al.
Their open-access paper is published in Energy & Environmental Science.
Our analysis underlines that there is no such thing as the battery cost. The conducted literature review reveals a multitude of interacting dimensions that researchers investigate in order to find the right answers to their specific questions. We find studies applying technological learning, literature-based projection and expert elicitation to focus on time-specific forecasting, and bottom-up modeling to focus on technology-specific forecasting.
Every single study that provides time-based projections expects LIB cost to fall, even if increasing raw and battery material prices are taken into account. Recent technological learning studies expect higher battery-specific learning potentials and show confidence in a more stable battery market growth. Literature-based projections are shown to differ in both, consulted data sources and applied aggregation technique, but can provide forecasts with limited effort. Expert elicitations allow for insights in opinions and doubts regarding fundamentally new battery technologies, however, our analysis indicates a lack of consulted experts with sufficient knowledge of process improvements in the examined studies.
…Across studies and methods, we find high uncertainty in the level of forecasted values on chronological and technological level that will remain a key challenge for researchers and companies in the field. This uncertainty reflects different assumptions or beliefs regarding market expectations, material prices, and technological specifications underlying each of the examined studies.
… This review demonstrates a strong belief in both declining future battery cost and its transformative impact on the energy and mobility sector. Our analysis provides the required transparency for an understanding of the economics behind battery technology, which is vital for a smooth transition towards a climate-neutral future.—Mauler et al.
Lukas Mauler, Fabian Duffner, Wolfgang G. Zeier and Jens Lekerad (2021) “Battery cost forecasting: a review of methods and results with an outlook to 2050” Energy & Environmental Science doi: 10.1039/D1EE01530C