何洪文
作者: 王泽兴,何洪文,彭剑坤,张炀,季双,张媛 (北京理工大学机械与车辆学院;东南大学交通学院;国家新能源汽车技术创新中心)
出处: 汽车工程 2024 第3期
关键词: 混合动力构型;筛选;变速器参数优化;Pareto前沿;仿真
摘要: 针对采用拉维娜行星齿轮机构和传统多挡变速器的并联混合动力构型选择,采用基于杠杆法以挡位设计规则、动力特性规则、工作模式规则、可制造性规则相结合的一种综合评价方法,对混合动力系统构型进行分析和筛选,并确定了构型方案和该方法的筛选流程。其次针对整车的设计目标,对发动机、电机的参数进行了选择,并运用GT- ...
作者: Yue, Hongwei1; He, Hongwen1; Han, Mo1; Gong, Sikai1 (1National Key Laboratory of Advanced Vehicle Integration and Control, National Engineering Research Center for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing; 100081, China)
出处: Fuel 2024
作者: Jia,Chunchun1;He,Hongwen13;Zhou,Jiaming2;Li,Jianwei13;Wei,Zhongbao1;Li,Kunang1; (1Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China;2School of Intelligent Manufacturing, Weifang University of Science and Technology, Weifang, 262700, China;3Yangtze Delta Region Institute of Beijing Institute of Technology, Zhejiang, 314001, China)
出处: Applied Energy 2024 Vol.355
摘要: Advanced energy management strategy (EMS) can ensure healthy, stable, and efficient operation of the on-board energy systems. Model Predictive Control ...
作者:
Ruoyan Han1;Hongwen He1,2;
出处: Journal of Energy Storage 2024 Vol.76 P109858
摘要: This paper proposes a multi-stack fuel cell system (MFCS) for a distributed fuel cell hybrid electric tracked vehicle. The power distribution results ...
作者: Wu, Jingda1;Huang, Chao1;He, Hongwen2;Huang, Hailong1 (1Hong Kong Polytech Univ, Hung Hom, Hong Kong, Peoples R China.;2Beijing Inst Technol, Beijing 100081, Peoples R China.)
出处: RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2024 Vol.191
关键词: STRATEGY; NETWORK
摘要: The reliability of data-driven techniques, such as deep reinforcement learning (DRL) frequently diminishes in scenarios beyond their training environm ...
作者: Jia, Chunchun1; Zhou, Jiaming3; He, Hongwen1, 2; Li, Jianwei1, 2; Wei, Zhongbao1; Li, Kunang1 (1National Key Laboratory of Advanced Vehicle Integration and Control, School of Mechanical Engineering, Beijing Institute of Technology, Beijing; 100081, China;2Yangtze Delta Region Institute of Beijing Institute of Technology, Zhejiang, 314003, China;3School of Intelligent Manufacturing, Weifang University of Science and Technology, Weifang; 262700, China)
出处: Energy 2024
作者: Zhang, Zhendong1; He, Hongwen1; Wang, Yaxiong2; Quan, Shengwei1; Chen, Jinzhou1; Han, Ruoyan1 (1National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China;2School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China)
出处: Applied Energy 2024
作者: Jia, Chunchun1; He, Hongwen1, 3; Zhou, Jiaming2; Li, Kunang1; Li, Jianwei1, 3; Wei, Zhongbao1 (1Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, Beijing; 100081, China;2School of Intelligent Manufacturing, Weifang University of Science and Technology, Weifang; 262700, China;3Yangtze Delta Region Institute of Beijing Institute of Technology, Zhejiang, 314003, China)
出处: International Journal of Hydrogen Energy 2024 P133-146
作者: He,Hongwen12;Su,Qicong12;Huang,Ruchen12;Niu,Zegong12; (1National Key Laboratory of Advanced Vehicle Integration and Control, Beijing Institute of Technology, Beijing, 100081, China;2School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China)
出处: Energy 2024 Vol.294
摘要: Due to the complex driving conditions faced by hybrid electric tracked vehicles, energy management is crucial for improving fuel economy. However, dev ...
作者: Tang,Yingjuan1;He,Hongwen1;Wang,Yong1; (1School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China)
出处: Neurocomputing 2024 Vol.580
摘要: In dynamic and interactive autonomous driving scenarios, accurately predicting the future movements of vehicle agents is crucial. However, current met ...