基于随机进化游戏模型的新能源汽车废电池回收效率加速的研究
Xiangyu Mao1, Ying Wang2, Yichong Mao3
1Business School, Jiangsu Second Normal University, Nanjing, China. xiangyumaonn@163.com.
Scientific reports
|January 20, 2025
概括
有效回收新能源汽车 (NEV) 废旧电池至关重要. 本研究使用游戏模型来分析挑战,并提出解决NEV电池回收的解决方案,涉及政府,企业和消费者.
科学领域:
- 环境科学 环境科学
- 材料科学 材料科学 材料科学
- 经济学 经济学 经济学
背景情况:
- 新能源汽车 (NEV) 的采用加速了碳减排,但也带来了废旧电池回收的挑战.
- 目前的新能源汽车电池回收面临的问题是:道有限,标准不一致,技术差距,非正式企业和消费者参与度低.
- 市场不成熟,监管不清晰和监管薄弱加剧了这些回收问题.
研究的目的:
- 解决新能源汽车行业中废旧电池回收效率低下的关键问题.
- 分析新能源汽车电池回收生态系统中关键利益相关者之间的战略互动.
- 制定有效的对策,促进可靠的废电池回收利用.
主要方法:
- 构建一个四方随机进化游戏模型.
- 包括政府监管机构,新能源汽车企业,第三方回收企业和消费者作为模型参与者.
- 分析各种参数对参与者战略选择的影响.
主要成果:
- 确定影响新能源汽车电池回收的战略决策的关键因素.
- 对监管,市场和消费者行为参数影响的量化.
- 了解利益相关者之间合作和竞争的动态.
结论:
- 该研究提供了对优化NEV电池回收系统的见解.
- 建议建议提高回收利用的效率和可持续性.
- 建议政府,新能源汽车公司,回收商和消费者进行政策和战略调整.
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