作者：Li, Guoqiang¹;Guo, Hongliang^1,2;Wang, Zhenpo¹;Wang, Meng³; （¹School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China ²Institute for Infocomm Research, Agency for Science, Technology and Research (ASTAR), Singapore ³Faculty of Transport and Traffic Sciences, Technische Universität Dresden, Dresden, Germany）

出处：Robotics & Autonomous Systems 2023

关键词：Autonomous overtaking;Dual optimization;Object avoidance;Receding horizon;Trajectory optimization

摘要：Autonomous driving with active obstacle avoidance in dynamic urban environment has attracted significant attention to improve road safety and traffic ...

作者：Lei Zhang^1,2;Zhijia Huang^1,2;CA1;Zhenpo Wang^1,2;Xiaohui Li^1,2;Fengchun Sun^1,2; （¹Collaborative Innovation Center for Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing, 100081, China;²National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081, China）

出处：Energy 2024

摘要：The rapid adoption of electric vehicles (EVs) has led to dramatic increase in charging demands that poses great challenges for charging infrastructure ...

作者：Yuan, Heng¹; Zhang, Jun¹; Zhang, Lei¹; Zhang, Zhiqiang¹; Wang, Zhenpo¹; （¹Collaborative Innovation Center for Electric Vehicles in Beijing and National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing, China）

出处：IEEE Transactions on Transportation Electrification 2023

关键词：automated vehicles;Biological system modeling;Hidden Markov models;planning-based posterior distribution fitting;Predictive models;Roads;temporal convolutional network;Training;Trajectory;Uncertainty;Vehicle trajectory prediction

摘要：Accurate and efficient prediction of future motions of surrounding vehicles plays a crucial role in navigating complex traffic scenarios for automated ...

作者：Wang, Mingqiang¹; Zhang, Lei¹; Chen, Jun²; Zhang, Zhiqiang¹; Wang, Zhenpo¹; Cao, Dongpu³; （¹Collaborative Innovation Center for Electric Vehicles in Beijing and the National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing, China;²Department of Electrical and Computer Engineering, Oakland University, Rochester, MI, USA;³School of Vehicle and Mobility, Tsinghua University, Beijing, China）

出处：IEEE Transactions on Transportation Electrification 2023

关键词：Automated driving;Behavioral sciences;Convolution;Encoding;interaction;long short-term memory (LSTM);Planning;Predictive models;Trajectory;trajectory prediction;Uncertainty

摘要：The driving safety of automated vehicles is largely dependent on accurately predicting the motions of surrounding vehicles. However, the existing appr ...

作者：Yang Zhao;Zhenpo Wang;Zuo-Jun Max Shen;Fengchun Sun （¹ National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081, China. ² College of Engineering, University of California, Berkeley, CA 94720. ³ National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100081, China; wangzhenpo@bit.edu.cn maxshen@berkeley.edu. ⁴ College of Engineering, University of California, Berkeley, CA 94720; wangzhenpo@bit.edu.cn maxshen@berkeley.edu. ⁵ Faculty of Engineering, The University of Hong Kong, Hong Kong SAR, China. ⁶ Faculty of Business and Economics, The University of Hong Kong, Hong Kong SAR, China.）

出处：Proceedings of the National Academy of Sciences of the United States of America 2021

关键词：battery resource;electric vehicle;energy consumption;sustainability;transport electrification.

摘要：Electrifying transportation in the form of the large-scale development of electric vehicles (EVs) plays a pivotal role in reducing urban atmospheric p ...

作者：Shan, Tongxin¹; Wang, Zhenpo¹; Zhu, Xiaoqing¹; Wang, Hsin²; Zhou, Yangjie¹; Wang, Yituo³; Zhang, Jinghan¹; Sun, Zhiwei¹; （¹National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China;²Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge; TN; 37831, United States;³State-assigned Electric Vehicle Power Battery Testing Center, China North Vehicle Research Institute, Beijing; 100072, China）

出处：Journal of Energy Chemistry 2022

关键词：Lithium-ion battery;Overcharge;Explosion behavior;Safety;Explosion dynamics

摘要：Large-format lithium-ion (Li-ion) batteries with high energy density for electric vehicles are prone to thermal runaway (or even explosion) under abus ...

作者：王震坡¹;，张雷¹;，王青松²;，张照生¹;，冯旭宁³; （¹北京理工大学；²中国科学技术大学；³清华大学）

出处：机械工程学报 2023

关键词：战略新兴产业；新能源汽车产业；能量密度；车辆运行；动力电池；自放电率；循环寿命；锂离子电池

摘要：新能源汽车产业是我国七大战略新兴产业之一，也是“中国制造2025”十大重点推动领域之一。动力电池系统是新能源汽车的核心部件，其性能直接影响车辆运行效率、安全性与可靠性。由于锂离子电池具有能量密度高、自放电率小、循环寿命长等优点，已在车载动力电池领域占据统治地位。近年来，我国新能源汽车产销量呈现出快速 ...

作者：刘鹏^1,2;，贾寒冰^1,2;，张雷^1,2;，王震坡^1,2; （¹北京理工大学电动车辆国家工程实验室；²北京电动车辆协同创新中心）

出处：机械工程学报 2023

关键词：路径规划；多项式曲线；环境势场；速度规划；凸优化

摘要：自主换道系统是智能汽车关键技术之一。针对自主换道系统的轨迹规划，提出基于路径-速度分解的分层换道轨迹规划方法。在路径规划层，基于改进二维正态分布函数建立道路、固定障碍物、周围车辆势场并生成环境总势场，采用五次多项式曲线构建换道路径簇，并基于环境总势场确定车辆的最优换道路径；在速度规划层，考虑换道效率 ...

发明人：张照生，王震坡，王帅，刘鹏，叶宝霖

申请日期：2023.09.20

摘要：本发明提供了一种基于机器学习的电动公交车能耗预测方法，其通过对部分难以直接提取的能耗相关特征参数建立基于机器学习的预测模型，有效解决了特征提取不符合实际的问题，显著改善了用于电动公交车能耗预测的数据质量与模型训练水平，提高了能耗预测结果的精确性。本方法的实现较为简便，能够有效节约计算资源。

发明人：张照生，王震坡，王瑞阳，刘鹏，贺一凡

申请日期：2023.11.20

摘要：本发明提供了一种电动汽车区域能耗地图绘制方法，可充分利用当前较为成熟的海量国标实车数据，并创新性地利用行驶片段切分、数据清洗、特征提取等一系列手段将车辆能耗与区域微元建立起联系，从而能够动态精确的反映不同电动汽车车型在不同区域位置的能耗水平，相对于现有技术具有更广泛的适用性和更低的计算成本，有利于在 ...