Rechargeable batteries are a key enabler to achieve the long-term goal to transform into a climate-neutral society. Within this transformation, battery costs are considered a main hurdle for the market-breakthrough of battery-powered products. Encouraged by this, various studies have been published attempting to predict these, providing the reader with a large variance of forecasted cost that results from differences in methods and assumptions. This article creates transparency by identifying 53 studies that provide time- or technology-specific estimates for lithium-ion, solid-state, lithium–sulfur and lithium–air batteries among more than 2000 publications related to the topic. The relevant publications are clustered according to four applied forecasting methods: technological learning, literature-based projections, expert elicitations and bottom-up modeling. Method-specific assumptions are analyzed in-depth and discussed with regard to their results and empirical evidence. Further, 360 extracted data points are consolidated into a pack cost trajectory that reaches a level of about 70 $ (kW h)−1 in 2050, and 12 technology-specific forecast ranges that indicate cost potentials below 90 $ (kW h)−1 for advanced lithium-ion and 70 $ (kW h)−1 for lithium-metal based batteries. Recent studies show confidence in a more stable battery market growth and, across time-specific studies, authors expect continuously declining battery cost regardless of raw material price developments. However, large cost uncertainties are found to exist on technological and chronological levels that will remain a key challenge for researchers and industry in the future.

/pdf/battery-cost-forecasting-a-review-of-methods-and-results-40d6dmg75y.pdf

Battery cost forecasting: a review of methods and results with an outlook to 2050

In this study, we develop a method for calculating electric vehicle lithium-ion battery pack performance and cost. To begin, we construct a model allowing for calculation of cell performance and material cost using a bottom-up approach starting with real-world material costs. It thus provides a supplement to existing models, which often begin with fixed cathode active material (CAM) prices that do not reflect raw metal price fluctuations. We collect and display data from the London Metal Exchange to show that such metal prices, in this case specifically cobalt and nickel, do indeed fluctuate and cannot be assumed to remain static or decrease consistently. We input this data into our model, which allows for a visualization of the effects of these metal price fluctuations on the prices of the CAMs. CAMs analyzed include various lithium transition metal oxide-type layered oxide (NMC and NCA) technologies, as well as cubic spinel oxide (LMO), high voltage spinel oxide (LNMO), and lithium metal phosphate (LFP). The calculated CAM costs are combined with additional cell component costs in order to calculate full cell costs, which are in turn scaled up to full battery pack costs. Economies of scale are accounted for separately for each cost fraction.

https://www.mdpi.com/1996-1073/12/3/504/pdf

A Bottom-Up Approach to Lithium-Ion Battery Cost Modeling with a Focus on Cathode Active Materials

Sodium-ion batteries (SIBs) are a recent development being promoted repeatedly as an economically promising alternative to lithium-ion batteries (LIBs). However, only one detailed study about material costs has yet been published for this battery type. This paper presents the first detailed economic assessment of 18,650-type SIB cells with a layered oxide cathode and a hard carbon anode, based on existing datasheets for pre-commercial battery cells. The results are compared with those of competing LIB cells, that is, with lithium-nickel-manganese-cobalt-oxide cathodes (NMC) and with lithium-iron-phosphate cathodes (LFP). A sensitivity analysis further evaluates the influence of varying raw material prices on the results. For the SIB, a cell price of 223 €/kWh is obtained, compared to 229 €/kWh for the LFP and 168 €/kWh for the NMC batteries. The main contributor to the price of the SIB cells are the material costs, above all the cathode and anode active materials. For this reason, the amount of cathode active material (e.g., coating thickness) in addition to potential fluctuations in the raw material prices have a considerable effect on the price per kWh of storage capacity. Regarding the anode, the precursor material costs have a significant influence on the hard carbon cost, and thus on the final price of the SIB cell. Organic wastes and fossil coke precursor materials have the potential of yielding hard carbon at very competitive costs. In addition, cost reductions in comparison with LIBs are achieved for the current collectors, since SIBs also allow the use of aluminum instead of copper on the anode side. For the electrolyte, the substitution of lithium with sodium leads to only a marginal cost decrease from 16.1 to 15.8 €/L, hardly noticeable in the final cell price. On the other hand, the achievable energy density is fundamental. While it seems difficult to achieve the same price per kWh as high energy density NMC LIBs, the SIB could be a promising substitute for LFP cells in stationary applications, if it also becomes competitive with LFP cells in terms of safety and cycle life.

https://publikationen.bibliothek.kit.edu/1000094100/27000531

Exploring the Economic Potential of Sodium-Ion Batteries

Large-scale automotive battery cell manufacturing: Analyzing strategic and operational effects on manufacturing costs

Energy impact of cathode drying and solvent recovery during lithium-ion battery manufacturing

Due to global warming and the rise of the CO2 emissions electric mobility is in the focus. In this case costs for li-ion batteries and especially the material costs are the main cost drivers for electric vehicles. The aim of this paper is to develop a material cost model which can evaluate cell chemistry alternatives for li-ion battery anodes and cathodes. A focus is set on innovative cell chemistries which currently are not using in mass production. The presented model is based on bottom-up approach which can calculate costs and cell performance together to determine the ratio of material cost and energy. The general results are complemented with a case study that assesses that active material with a high specific energy can help reducing the material costs and improves cell performance parameters.

/pdf/material-cost-model-for-innovative-li-ion-battery-cells-in-4qkxc336xy.pdf

Material cost model for innovative li-ion battery cells in electric vehicle applications

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Material cost model for innovative li-ion battery cells in electric vehicle applications