Research on carbon footprint of power batteries for new energy vehicles based on trusted data space technology
トラステッドデータスペース技術に基づく新エネルギー車用パワーバッテリーのカーボンフットプリント研究 (AI 翻訳)
Chuan Chen, Huanhuan Ren, Chen Liu, Zidu Yang, Baoan Tang, Suyan Jia, Rui Huang, Yutong Song, Guorui Jia
🤖 gxceed AI 要約
日本語
新エネルギー車用トラクションバッテリーのライフサイクルカーボンフットプリント算定におけるデータ断片化と不正確さを解決するため、トラステッドデータスペースアーキテクチャを構築。データ統合効率を65%以上向上させ、算定誤差を18%から5.2%未満に低減。生産段階が総排出量の70%以上を占め、乾燥工程がエネルギー消費の32〜38%を占めることを特定。コバルト系三元材料はリン酸鉄リチウムより105〜140%排出量が多いと評価。
English
To address data fragmentation and inaccuracy in carbon footprint accounting for EV traction batteries, a trusted data space architecture was developed, improving data integration efficiency by over 65% and reducing accounting error from 18% to below 5.2%. The production stage contributes over 70% of total emissions, with the drying process accounting for 32-38% of energy use. Cobalt-based ternary materials generate 105-140% more emissions than lithium iron phosphate, and upstream materials represent 45-52% of life-cycle emissions.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ開示やサプライチェーン排出量算定の精度向上が急務であり、本手法はデータ連携基盤によるScope 3算定の信頼性向上に示唆を与える。電池産業の低炭素移行や国際的な炭素規制対応にも貢献し、日本の自動車・電池メーカーの開示実務に応用可能。
In the global GX context
This work aligns with global trends toward accurate Scope 3 accounting and supply-chain decarbonization, particularly under ISSB and CSRD requirements. The trusted data space approach offers a replicable model for improving data quality and traceability in battery value chains, supporting international carbon compliance and transition finance.
👥 読者別の含意
🔬研究者:Provides a novel data-space-based method for life-cycle carbon accounting with quantified accuracy improvements, useful for further research on data infrastructure and battery LCA.
🏢実務担当者:Offers a framework to enhance carbon footprint data reliability and identify emission hotspots, aiding corporate sustainability reporting and supply chain optimization.
🏛政策担当者:Highlights the importance of data trustworthiness for carbon compliance and suggests policy support for data-sharing infrastructures in the battery sector.
📄 Abstract（原文）
To address fragmentation of data and substantial inaccuracy in carbon footprint accounting for traction battery systems of new energy vehicles, as well as to enable precise identification of critical paths for emission reduction across the life cycle, a trustworthy data space architecture was constructed in this work. A systematic analysis of the full-life-cycle carbon footprint of traction batteries was conducted by use of the proposed architecture. It was found that data integration efficiency was increased by over 65 percent through the adopted framework. Carbon footprint accounting error was reduced from 18 percent to below 5.2 percent. Verification pass rate was achieved at 99.3 percent. The average carbon emission of the full life cycle was measured at 850 to 920 kg CO₂e per kWh. The production stage was shown to contribute more than 70 percent of total emissions. Within production, the drying process was identified to account for 32 to 38 percent of total energy consumption, with its share in carbon emission estimated at 29 to 35 percent. Site selection at higher latitudes was observed to lower energy use in this process by 15 to 20 percent. At material level, cobalt-based ternary materials were indicated to generate 105 to 140 percent more emissions than lithium iron phosphate. Upstream material emissions were assessed to represent 45 to 52 percent of the whole-life-cycle carbon output. Support of accurate quantification and scientific basis for decision-making were provided by this study. Contributions were made to low-carbon transition of the traction battery industry, optimization of supply chains, and alignment with international carbon compliance requirements.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1117/12.3109614first seen 2026-08-02 18:23:11
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