基于生态系统价值优化方法的电动汽车电池循环利用数字解决方案框架

Amit Kumar, Pierre Huyn, Ravigopal Vennelakanti
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引用次数: 0

摘要

电池的循环经济对于建立可持续的电池价值链至关重要,因为报废的电动汽车电池可以获得第二次生命,或者收获宝贵的原材料来制造新电池。然而,在预测可用性、预测剩余价值、最大限度地降低逆向物流成本以及最大限度地回收报废电池的价值方面,仍然存在巨大挑战。在此,我们设计了一种由创新分析模型和可信数据平台组成的数字解决方案框架驱动的生态系统价值优化方法,以优化电池循环利用的五个关键价值驱动因素--安全、合规、减少碳足迹、质量和财务。与目前的运输方式相比,设想中的解决方案可帮助将报废电池的平均运输成本降低 11% 至 44%,以低于 1% 的误差率估算电池健康状况,并通过将健康状况良好的电池输送给二次生命应用提供商,将价值回收率提高 52% 至 60%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A digital solution framework for enabling electric vehicle battery circularity based on an ecosystem value optimization approach

A digital solution framework for enabling electric vehicle battery circularity based on an ecosystem value optimization approach
A circular economy for batteries is crucial for building a sustainable battery value chain, as end-of-life electric vehicle batteries can be given a second life or valuable raw materials can be harvested to make new batteries. However, significant challenges remain in forecasting availability, predicting remaining value, minimizing reverse logistics costs, and maximizing value recovery from end-of-life batteries. Here we devise an ecosystem value optimization approach powered by a digital solution framework, consisting of innovative analytical models and a trusted data platform, to optimize five key value drivers for battery circularity—safety, regulatory compliance, carbon footprint reduction, quality, and financials. The envisioned solution can help reduce average transportation costs of end-of-life batteries by 11% to 44% compared to current shipping practices, estimate battery health with error rates less than 1%, and improve value recovery by 52% to 60% by routing batteries with good health to second-life application providers.
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