Battery cost modeling: A review and directions for future research
Cost reduction of electric vehicles (EVs), which depends largely on their most cost-intensive component, the battery, is the prerequisite for their market success. To achieve this cost reduction, accurate and detailed cost forecasts are necessary to make the right operational and strategic decisions...
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Veröffentlicht in: | Renewable & sustainable energy reviews 2020-07, Vol.127, p.109872, Article 109872 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Cost reduction of electric vehicles (EVs), which depends largely on their most cost-intensive component, the battery, is the prerequisite for their market success. To achieve this cost reduction, accurate and detailed cost forecasts are necessary to make the right operational and strategic decisions like focusing on the right technology, product design, or process steps. Driven by this, numerous cost models were developed in recent years. The study at hand gives a systematic overview of the scientific publications within this research field and therefore provides researchers, industry representatives and policy makers with an overview of the benefits, reliability and transparency of the models studied. A total of 633 publications were initially identified. Conducting a systematic pre-selection, we selected the 21 most relevant ones which were analyzed in detail based on 17 characteristics. These characteristics were categorized and discussed in 6 main areas, namely impact of cost models, used cost estimation technique, model architecture and transparency, technology parameters, technical and operational depth of the calculation model, as well as the reported costs. In addition, five major recommendations for future research were derived.
•Comprehensive literature review of battery cost modelling.•Framework to identify most relevant publications.•Categories and characteristics for systematic analysis.•Time-specific cost profiles based on 500 data points.•Major recommendations to conduct further battery cost modelling research. |
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ISSN: | 1364-0321 1879-0690 |
DOI: | 10.1016/j.rser.2020.109872 |