引用本文:杨子荣,郝冬,姚占辉,张妍懿,王佳.基于大数据的燃料电池汽车关键性能分析与衰减预测[J].控制理论与应用,2025,42(8):1606~1614.[点击复制]
YANG Zi-rong,HAO Dong,YAO Zhan-hui,ZHANG Yan-yi,WANG Jia.Key performance analysis and degradation prediction of fuel cell vehicles based on big data[J].Control Theory & Applications,2025,42(8):1606~1614.[点击复制]
基于大数据的燃料电池汽车关键性能分析与衰减预测
Key performance analysis and degradation prediction of fuel cell vehicles based on big data
摘要点击 3529  全文点击 172  投稿时间：2024-01-20  修订日期：2025-07-04
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DOI编号  10.7641/CTA.2024.40051
  2025,42(8):1606-1614
中文关键词  燃料电池汽车  道路行驶数据  关键特征体系  加氢特性  性能衰减预测
英文关键词  fuel cell vehicle  road operating data  key performance index  hydrogen refueling characteristics  perfor mance degradation and prediction
基金项目  国家重点研发计划项目(2021YFB2501500)资助.
作者单位E-mail
杨子荣 中国汽车技术研究中心有限公司 yangzirong@catarc.ac.cn 
郝冬* 中国汽车技术研究中心有限公司 haodong@catarc.ac.cn 
姚占辉 中国汽车技术研究中心有限公司  
张妍懿 中国汽车技术研究中心有限公司  
王佳 中国汽车技术研究中心有限公司  
中文摘要
      开展苛刻复杂道路工况下燃料电池汽车(FCV)的运行特征分析与性能衰减预测对于指导产品迭代升级具 有重要意义.本文基于40辆燃料电池重型货车的道路行驶数据,首先,提出了数据预处理、数据分析与挖掘以及数 据后处理方法,随后,建立了涵盖车辆出行行为、加氢特性以及燃料电池系统性能的FCV关键特性体系,进一步构 建了基于实车运行数据的发动机性能衰减与预测方法,满足不同时间跨度、不同车队规模的整车、发动机、辅助系 统等不同对象的全方位性能分析需求.研究发现,车队中单次出行里程不超过50%纯氢续驶里程的总占比达 到95%以上. 加氢行为最密集的区域是加氢间隔里程为180～220km、加氢间隔时间为24h左右.
英文摘要
      Conducting the statistical characteristics analysis and performance degradation prediction of fuel cell vehicles (FCV) under complex road conditions is of great significance for product improvement. Based on the real operating data of 40 heavy-duty trucks, the paper firstly proposes the pre-processing, data analysis, and post-processing procedure. Subsequently, the FCV key performance index system were established, covering the vehicle travel behaviors, hydrogen refueling characteristics, and fuel cell system performances. Then, the engine performance degradation and prediction methods based on the FCV travelling data was established, satisfying the performance analysis of different time span, motorcade scale, and multi-objects of vehicle, engine as well as auxiliary systems. It was found that the total proportion of the single trip distance divided by pure hydrogen driving mileage of no more than 50% accounted for over 95%. The most frequent hydrogenation behavior happened in the section of 180～220 km hydrogen refueling interval distance and around 24 h hydrogen refueling interval time.