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Optimum Driving System Design for Dual-Motor Pure Electric Vehicles
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作者 Hongwei Zhang Weichi Chen +4 位作者 Zhuangzhuang Shang Zhifeng Xu Zepeng Gao Yong Chen Hongbin Ren 《Journal of Beijing Institute of Technology》 EI CAS 2020年第4期592-602,共11页
A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the ... A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%. 展开更多
关键词 pure electric vehicle vehicle powertrain parameter matching time sharing drive
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Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model 被引量:4
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作者 Hongxin Chen Shuo Feng +2 位作者 Xin Pei Zuo Zhang Danya Yao 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2017年第6期682-690,共9页
Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autore... Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autoregressive(AR) time-series model is improved and adopted to describe the dynamic variations of average daily time headway. Based on the model, a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway. The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China. Finally, a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks. 展开更多
关键词 time headway driving behavior traffic safety autoregressive time-series model remaining life driving warning strategy
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