Self-powered and self-feedback wind energy harvester for intelligent metro air conditioningOA
Metro is an essential component of urban transport and has received attention for its intelligibility and sustainability.In this paper,a self-feedback wind energy harvester(SWEH)based on a piston wind pavilion is designed consisting of four modules,namely:a wind energy harvesting module(WEHM),an energy conversion module(ECM),an energy storage module(ESM),a machine learning module(MLM).The SWEH collects the wind energy passing through the piston wind kiosk and gathers information about the voltage generated by the inlet rotor.The MLM module uses a deep learning model based on Convolutional Neural Networks(CNN)to enable SWEH to recognize real-time ventilation status.Experiments show that the maximum output power of the prototype is 0.7 W and the maximum average power is 781 mW.Feedback to get the predicted airflow information and feedback system device of the electrical signal on the deep learning network can reach a 99.92%recognition rate.The experimental results show that the SEWH can collect redundant piston wind energy passing through the metro piston kiosk for application to the appropriate sensors,and the feedback from the SWEH possesses the potential to provide a form of identifying information for energy saving in metro air conditioning.
Congcong Zhang;Jiaoyi Wu;Zutao Zhang;Yajia Pan;Tengfei Liu;Hao Wang;Hongyu Chen;Long Wang
School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR ChinaSchool of Information Science and Technical,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR ChinaSchool of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,PR China Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,PR China
交通工程
Wind energySelf-feedback energy harvesterEnergy conversionEnergy storageCNN network
《Energy and Built Environment》 2026 (2)
P.364-380,17
supported by the National Natural Foundation of China under Grant No.51975490by the Science and Tech-nology Projects of Sichuan under Grants Nos.23QYCX0280 and 2022NSFSC0461by the Science and Technology Projects of Yibin under Grant No.2021ZYCG017,2023SJXQYBKJJH005,No.YBSCXY2023020004 and YBSCXY2023020008by the Science and Technology Projects of Chengdu under Grant No.2021YF0800138GX。
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