光储充移动式充电机器人研发综述

doi:10.3969/j.issn.1674-8484.2025.04.001

汽车安全与节能学报 ›› 2025, Vol. 16 ›› Issue (4): 505-520.DOI: 10.3969/j.issn.1674-8484.2025.04.001

• 综述与展望 • 下一篇

光储充移动式充电机器人研发综述

李舜酩¹^,²(), 王昌荣¹, 史文贝²

¹ 南通理工学院汽车工程学院，南通 430064，中国
² 南京航空航天大学能源与动力学院，南京 210016，中国

收稿日期:2025-04-24 修回日期:2025-08-01 出版日期:2025-08-30 发布日期:2025-08-27
作者简介:李舜酩（1962—），男（汉），山东，教授。E-mail：smli@nuaa.edu.cn。
李舜酩教授
南京航空航天大学航空航天结构力学与控制全国重点实验室教授、博士生导师，南通理工学院车辆工程专业带头人。主持完成国家重点研发计划项目、国家自然科学基金、国家重大科技专项子课题、国家重点研发计划子课题、省部委基金等 60 余项研究项目，主持或参与撰写企业/行业标准 7 项，获省部级科学技术进步奖 7 项（6 项排名第一）。主编出版科技著作 10 余部，发表学术论文 400 多篇，获发明专利和软著权 40 多件。入选 2024 年全球前 2% 顶尖科学家/终身科学影响力排行榜榜单、2024 年知网评选 1‰ 高被引学者。两次作为大会主席，主持召开国际著名学术会议。先后访问多个国际著名大学开展学术交流并做学术报告。主要研究方向为现代信号处理理论方法与应用、智能健康检测与故障诊断、智能车辆与现代设计技术。
Prof. LI Shunming
He is a professor and doctoral supervisor of the National Key Laboratory of Aerospace Structural Mechanics and Control at Nanjing University of Aeronautics and Astronautics, and Leading figure in vehicle engineering discipline at Nantong University of Science and Technology. He hosted and completed over 60 research projects, including National Key R&D Program Projects, National Natural Science Foundation, Sub Project of National Major Science and Technology Projects, Sub Project of National Key R&D Program Projects, and provincial and ministerial funds. He led or participated in the writing of 7 enterprise/industry standards, won 7 provincial and ministerial level science and technology progress awards (ranked first in 6 of them), edited and published over 10 scientific and technological works, published more than 400 academic papers, and obtained over 40 invention patents and software copyrights. He was selected for the top 2% of global scientists/lifetime scientific influence rankings in 2024, and selected as a 1‰ highly cited scholar by CNKI in 2024. As the chairman of the conference, he has presided over two internationally renowned academic conferences. He visited several internationally renowned universities abroad to conduct academic exchanges and give academic presentations. His main researches include modern signal processing theory, methods and applications, intelligent health detection and fault diagnosis, intelligent vehicles and modern design technology.
基金资助:
南通理工学院科技创新团队基金项目(KCTD010);国家自然科学基金项目(51975276)

Progress of mobile charging robot for photovoltaic energy storage and charging

LI Shunming¹^,²(), WANG Changrong¹, SHI Wenbei²

¹ School of Automotive Engineering, Nantong Institute of Technology, Nantong 226002, China
² College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received:2025-04-24 Revised:2025-08-01 Online:2025-08-30 Published:2025-08-27

摘要/Abstract

摘要：

为满足迅速增加的新能源汽车充电需求，光储充移动式充电机器人成为重要的研发方向。该文介绍了新能源汽车光伏储能移动充电机器人研发的必要性、重要性和基本运作模式，以及光储充系统的构架与核心优势、移动式充电机器人的分类和场景适配，分析了光储充移动式充电机器人的经济性、安全性与可靠性；梳理了移动式充电机器人在自主充电、路径规划、充电口识别并插入等3个关键技术方面的研究现状，并指出其优势和欠缺；综述了光储充移动充电机器人应用技术研发的新体系构建及其关键技术，并分析了各个专门应用场景；最后提出了光储充技术在能量传输效率、安全性和稳定性、动态规划、充电口识别与插入、高技术储能以及应用场景拓展等方面面临的挑战，展望了光储充移动式充电机器人的研发趋势。

关键词: 光储充, 移动充电, 机器人, 路径规划, 充电口识别并插入

Abstract:

To address the rapidly growing charging demands of new energy vehicles, mobile charging robots integrated with photovoltaic energy storage and charging systems have emerged as a crucial direction in research and development. This paper outlines the necessity and significance of developing photovoltaic energy storage systems and mobile charging robots for new energy vehicles, along with their fundamental operational modes. It presents the structural framework and core advantages of the photovoltaic energy storage and charging system, as well as the classification and scenario-specific adaptability of mobile charging robots. Furthermore, the economic viability, safety, and reliability of photovoltaic energy storage and charging mobile robots are analyzed. The study reviews the current research status of three key technologies—autonomous charging, path planning, and charging port recognition and insertion—and evaluates their respective strengths and limitations. This paper also summarizes the development of a new system for application-oriented research on photovoltaic energy storage and mobile charging robots, along with its key enabling technologies, and explores various specialized application scenarios. Finally, the paper identifies the challenges faced by photovoltaic energy storage and charging technologies in areas such as energy transmission efficiency, safety and stability, dynamic programming, charging port identification and insertion, advanced energy storage solutions, and the expansion of application domains. It also provides insights into the future development trends of mobile charging robots.

Key words: photovoltaic energy storage and charging, mobile charging, robot, path planning, charging port identification and insertion

中图分类号:

TP242.6

李舜酩, 王昌荣, 史文贝. 光储充移动式充电机器人研发综述[J]. 汽车安全与节能学报, 2025, 16(4): 505-520.

LI Shunming, WANG Changrong, SHI Wenbei. Progress of mobile charging robot for photovoltaic energy storage and charging[J]. Journal of Automotive Safety and Energy, 2025, 16(4): 505-520.

图/表 18

参考文献 67

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充电方式	初期投资成本	长期运营成本	效益优势
光储充移动式充电机器人	初始投资高，设备复杂度高	光伏发电降低购电依赖，储能系统利用峰谷电价差降低充电成本	服务灵活性高、多元收益、低碳战略价值
传统充电桩	初始投资低，短期部署快	完全依赖电网，无法参与电网调峰，成本波动大	充电效率稳定，适合高频固定场景

充电方式	初期投资成本	长期运营成本	效益优势
光储充移动式充电机器人	初始投资高，设备复杂度高	光伏发电降低购电依赖，储能系统利用峰谷电价差降低充电成本	服务灵活性高、多元收益、低碳战略价值
传统充电桩	初始投资低，短期部署快	完全依赖电网，无法参与电网调峰，成本波动大	充电效率稳定，适合高频固定场景

关键技术	优点	缺点
磁耦合谐振技术	非接触充电，适用于移动场景，避免机械磨损；支持多机器人协同充电	对充电距离和空间对准要求高；金属障碍物易干扰能量传输效率；设备成本高，体积适配性差
自主充电系统	全流程自动化，提升续航能力；支持动态路径规划与实时状态监控	依赖高精度传感器和复杂算法，硬件成本高；环境适应性不足
多传感器融合	提升定位精度；增强环境鲁棒性	多源数据处理复杂度高，实时性要求高；传感器间校准难度大，可能引入累积误差
深度学习算法	复杂环境下识别精度高；支持端到端自主决策	模型训练需大量数据，计算资源消耗大；实时性与模型轻量化矛盾

关键技术	优点	缺点
磁耦合谐振技术	非接触充电，适用于移动场景，避免机械磨损；支持多机器人协同充电	对充电距离和空间对准要求高；金属障碍物易干扰能量传输效率；设备成本高，体积适配性差
自主充电系统	全流程自动化，提升续航能力；支持动态路径规划与实时状态监控	依赖高精度传感器和复杂算法，硬件成本高；环境适应性不足
多传感器融合	提升定位精度；增强环境鲁棒性	多源数据处理复杂度高，实时性要求高；传感器间校准难度大，可能引入累积误差
深度学习算法	复杂环境下识别精度高；支持端到端自主决策	模型训练需大量数据，计算资源消耗大；实时性与模型轻量化矛盾

算法	路径长度			迭代次数
算法	最优	最劣	平均	最优	最劣	平均
传统灰狼算法	27.11	27.99	27.45	3	47	9.5
适应度加权平均法	27.11	27.84	27.25	3	45	11.7
头狼加权平均法	27.11	27.84	27.41	5	48	16.2

光储充移动式充电机器人研发综述

Progress of mobile charging robot for photovoltaic energy storage and charging

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	障碍物类型	导航依赖	算法	通信需求
充电机器人行驶路径	以静态障碍物为主，动态障碍物较少	依赖激光雷达、摄像头、超声波等本地传感器构建局部地图，结合云端调度指令	全局路径规划(如栅格法、拓扑地图法)确定宏观路线，局部路径规划(如人工势场法、向量场直方图法)处理实时障碍物	需与云端平台、目标车辆实时通信
行车路径	动态障碍物密集，需实时处理突发状况	依赖高精度地图、车载导航系统及车联网数据	基于Dijkstra算法、Floyd算法等图论方法，结合实时交通数据生成全局最优路径	需与交通基础设施及其他车辆通信，实现协同驾驶

关键技术	优点	缺点	核心优势
模板匹配法	算法简单、实时性强；无需复杂硬件，成本低	对光照、角度变化敏感；仅适用于标准充电口，无法适配异形或脏污接口	低成本、高实时性
视觉-激光雷达融合	融合视觉语义与激光雷达精度，定位误差< 5 mm；支持动态环境	多传感器标定复杂；激光雷达成本高	高精度、动态校准
点云+力觉协同	适应非结构化环境；插入成功率>98%	点云数据处理算力需求高；力控算法依赖机械臂刚度，柔性场景易触发过载保护	强鲁棒性、接触容错
深度学习端到端	复杂环境鲁棒性强；端到端决策，无需人工特征设计	模型轻量化不足；小样本场景泛化差	复杂场景适应、多车型兼容
CPS多源融合	突破单机器人感知局限，全局调度精度< 3 cm；支持车-桩-云协同	依赖基础设施改造；通信延迟影响实时性	全局协同、超精度定位

发展阶段	推出时间	企业/机构	产品名称	核心技术/特点	应用场景	市场表现摘要	主要挑战
早期探索	2015年	特斯拉	蛇形充电机器人	独特的蛇形机械臂，灵活适应车辆位置，高效充电	特斯拉专属充电站	车主高度认可，提升科技形象	仅适用特斯拉车型；设备成本高；需提升机械臂可靠性和寿命
早期探索	2018年	三星	自主导航充电机器人	先进导航技术，自主规划路径，适应复杂停车场环境	大型停车场	试点效果良好，提高空间利用率	对停车场环境依赖高；需提高充电功率；降低能耗
集中发展	2020年	上海电气	直角坐标式构架机器人	结构简单，运行稳定，成本较低	住宅小区、商业综合体地下停车场	交流慢充需求大场景应用效果好	充电速度慢；灵活性受限；需拓展适用场景
	2020年	国网电力科学研究院、国网天津滨海电力公司	自动充电机器人	针对公交车型定制，充电效率高	公交车站	保障公交运营，提高充电管理效率	场地改造要求高；需提高设备通用性；降低改造成本
	2020年	享奕科技	-	融合自主化技术，实现定位、开盖、插拔全流程无人化	商业/高端小区停车场	试点认可度高，提高便利性	设备成本高；需提高系统稳定性/可靠性；解决多品牌桩兼容性
	2020年	爱驰汽车	移动式自动充电机器人carl	基于App指令，图像识别技术识别充电接口	停车场、私人车库	用户体验良好，操作便捷	复杂环境识别准确率待提高；小众车型兼容性不足
近期突破	2022年	IONITY等 (ROCIN-ECO联盟	-	推动标准化/产业化，整合资源，制定标准，促进共享	多品牌合作的充电网络	行业关注度高，有望加速普及	标准制定复杂；各方利益协调难；需加快互通互联；提升服务质量
	2024 上半年	华为	快充自动充电机器人	融合视觉+雷达感知，适配多品牌车型，快充	公共快充站、高速服务区等	试点受欢迎，充电效率和适配性获认可	初期建设成本高；需优化识别精度/稳定性；降低成本；拓展网络
	?	挚达科技	FS/FA/MA系列	独特机械结构设计，先进识别技术(多项专利)，满足多场景需求	各类停车场、住宅小区	海外份额稳定，产品稳定性/创新性获认可	国内品牌知名度待提高；需加大推广力度；优化性能；拓展国内渠道

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