Modeling Uncertain Decision Factors in Power Battery Recycling Using a Pythagorean Fuzzy Bayesian Network

作者：Jia Li, Maokang Du · 发表于：2025 5th International Conference on New Energy and Power Engineering (ICNEPE) · 年份：2025 · DOI：10.1109/ICNEPE67923.2025.11384292

With the rapid development of electric vehicles (EVs) and the increasing volume of retired batteries, efficient and sustainable recycling of EV batteries has become a critical challenge. This study proposes a Pythagorean Fuzzy Bayesian Network (PF-BN) framework to systematically identify and evaluate the key factors influencing the recycling process. By integrating Pythagorean fuzzy sets with Bayesian networks, the proposed method effectively handles uncertainty and fuzziness in expert assessments while providing probabilistic inference of factor importance. Extensive experiments demonstrate that the PF-BN framework outperforms traditional fuzzy AHP and classical Bayesian network approaches in accurately identifying critical factors and enhancing decision-making reliability. The findings provide actionable insights for policymakers, recycling enterprises, and stakeholders, supporting the development of an efficient, sustainable, and environmentally friendly EV battery recycling system.