电器与能效管理技术Issue(4)：32-40,9.DOI:10.16628/j.cnki.2095-8188.2026.04.004
基于多智能体近端策略优化算法的电力机车受电弓随网压力研究
Investigation of Pantograph Wire-Following Contact Force in Electric Locomotives Based on Multi-Agent Proximal Policy Optimization
摘要
Abstract
The pantograph-catenary system,as the key interface for traction power transmission in electric locomotives,determines current-collection quality and operational reliability through its coordination performance.At high speeds,the sliding of pantograph along the contact wire excites coupled vibrations in the pantograph-catenary system,undermining contact stability and reducing current-collection efficiency.Regulating the wire-following contact force(WFCF)is an effective remedy.A multi-agent proximal policy optimization(MAPPO)method augmented with a long short-term memory(LSTM)network is proposed to achieve dynamic WFCF control.Within a centralized-training,decentralized-execution(CTDE)framework,multiple agents are trained to learn speed-specific control policies,enabling precise force regulation across operating conditions.Experimental results show that the proposed approach substantially suppresses WFCF fluctuations and enhances contact wire-following performance(CWFP).关键词
随网压力/多智能体近端策略优化/受电弓/随网性能Key words
wire-following contact force/MAPPO/pantograph/contact wire-following performance分类
信息技术与安全科学引用本文复制引用
马振豪,郭凤仪,韩聪信..基于多智能体近端策略优化算法的电力机车受电弓随网压力研究[J].电器与能效管理技术,2026,(4):32-40,9.基金项目
国家自然科学基金(52477153) （52477153）
