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Active Control and Validation of the Electric Vehicle Powertrain System Using the Vehicle Cluster Environment

Authors: Ming Ye; Yitao Long; Yi Sui; Yonggang Liu; Qiao Li;

Active Control and Validation of the Electric Vehicle Powertrain System Using the Vehicle Cluster Environment

Abstract

With the development of intelligent vehicle technologies, vehicles can obtain more and more information from various sensors. Many researchers have focused on the vertical and horizontal relationships between vehicles in a vehicle cluster environment and control of the vehicle power system. When the vehicle is driving in the cluster environment, the powertrain system should quickly respond to the driver’s dynamic demand, so as to achieve the purpose of quickly passing through the cluster environment. The vehicle powertrain system should be regarded as a separate individual to research its active control strategy in a vehicle cluster environment to improve the control effect. In this study, the driving characteristics of vehicles in a cluster environment have been analyzed, and a vehicle power-demanded prediction algorithm based on a vehicle-following model has been proposed in a cluster environment. Based on the vehicle power demand forecast and driver operation, an active control strategy of the vehicle powertrain system has been designed considering the passive control strategy of the powertrain system. The results show that the vehicle powertrain system can ensure a sufficient backup power with the active control proposed in the paper, and the motor efficiency is improved by 0.61% compared with that of the passive control strategy. Moreover, the overall efficiency of the powertrain system is increased by 0.6% and the effectiveness of the active control is validated using the vehicle cluster environment.

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Keywords

power-demanded prediction, Technology, T, active control, efficiency, cluster environment, powertrain system, electric vehicles

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
gold