Scholarlink

<p>The rapid adoption of electric vehicles (EVs) has increased the demand for efficient battery swapping and charging services, making battery swapping and charging systems (BSCSs) a promising solution. In practice, BSCS operation management requires coordination among multiple subsystems through iterative information exchange, which may expose sensitive operational data in distributed optimization. To address this issue, we propose PriBSCS, a privacy-preserving distributed coordination scheme for BSCS operation management. The problem is formulated as a constrained mixed-integer programming (MIP) model and decomposed into swapping and charging subproblems using the alternating direction method of multipliers (ADMM). Homomorphic encryption is embedded into the iterative coordination process, where the Paillier cryptosystem is used to protect coupling-related quantities involved in iterative coordination without modifying the underlying optimization structure. We analyze the privacy properties of PriBSCS under a semi-honest, non-colluding threat model and show that exchanged coupling-related quantities remain protected in ciphertext form during coordination. Numerical results show that the proposed scheme achieves highly stable convergence behavior via ergodic averaging and achieves performance close to the centralized benchmark with modest computational overhead.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

PriBSCS: privacy-preserving distributed coordination for battery swapping and charging systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月18日

查看全文
  • Haotian Chi,
  • Fei Zuo,
  • Zhuocheng Sun,
  • Haijun Geng,
  • Yuwei Wang,
  • Shunrong Jiang

摘要

The rapid adoption of electric vehicles (EVs) has increased the demand for efficient battery swapping and charging services, making battery swapping and charging systems (BSCSs) a promising solution. In practice, BSCS operation management requires coordination among multiple subsystems through iterative information exchange, which may expose sensitive operational data in distributed optimization. To address this issue, we propose PriBSCS, a privacy-preserving distributed coordination scheme for BSCS operation management. The problem is formulated as a constrained mixed-integer programming (MIP) model and decomposed into swapping and charging subproblems using the alternating direction method of multipliers (ADMM). Homomorphic encryption is embedded into the iterative coordination process, where the Paillier cryptosystem is used to protect coupling-related quantities involved in iterative coordination without modifying the underlying optimization structure. We analyze the privacy properties of PriBSCS under a semi-honest, non-colluding threat model and show that exchanged coupling-related quantities remain protected in ciphertext form during coordination. Numerical results show that the proposed scheme achieves highly stable convergence behavior via ergodic averaging and achieves performance close to the centralized benchmark with modest computational overhead.