Consistency and Robustness in Forecasting for Emerging Technologies: The Case of Li-ion Batteries for Electric Vehicles

Apurba Sakti, I. Azevedo, E. Fuchs, Jeremy J. Michalek, K. Gallagher, J. Whitacre
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Abstract

There are a large number of accounts about rapidly declining costs of batteries with potentially transformative effects, but these accounts often are not based on detailed design and technical information. Using a method ideally suited for that purpose, we find that when experts are free to assume any battery pack design, a majority of the cost estimates are consistent with the ranges reported in the literature, although the range is notably large. However, we also find that 55% of relevant experts’ component-level cost projections are inconsistent with their total pack-level projections, and 55% of relevant experts’ elicited cost projections are inconsistent with the cost projections generated by putting their design- and process-level assumptions into our process-based cost model (PBCM). These results suggest a need for better understanding of the technical assumptions driving popular consensus regarding future costs. Approaches focusing on technological details first, followed by non-aggregated and systemic cost estimates while keeping the experts aware of any discrepancies, should they arise, may result in more accurate forecasts.    
新兴技术预测的一致性和稳健性:以电动汽车用锂离子电池为例
有大量关于电池成本迅速下降并具有潜在变革性影响的报道,但这些报道往往没有基于详细的设计和技术信息。使用一种非常适合这一目的的方法,我们发现,当专家可以自由地假设任何电池组设计时,大多数成本估算与文献中报道的范围一致,尽管范围非常大。然而,我们也发现55%的相关专家的组件级成本预测与他们的总包级预测不一致,55%的相关专家的成本预测与将他们的设计和过程级假设纳入我们的基于过程的成本模型(PBCM)所产生的成本预测不一致。这些结果表明,有必要更好地理解推动有关未来成本的普遍共识的技术假设。首先关注技术细节的方法,然后是非汇总和系统的成本估计,同时让专家了解任何差异,如果它们出现,可能会导致更准确的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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