A Vehicle-Environment Cooperative Control Based Velocity Profile Prediction Method and Case Study in Energy Management of Plug-in Hybrid Electric Vehicles

9Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The vehicle-environment cooperative (VEC) control has shown a great potential to improve vehicle performance. Consequently, it is desirable to further investigate the incorporation of the VEC control. In this context, a novel method is proposed to predict the velocity profile; meanwhile, the potential of the proposed method is exploited to improve energy management performance of plug-in hybrid electric vehicles (PHEVs). In particular, a specific VEC control framework is first introduced based on the mobile edge computation (MEC). On this basis, a compound velocity profile prediction (CVPP) algorithm is developed, which merges the cloud server (CS), MEC servers, and on-board vehicle control unit (VCU), and provides more accurate and reasonable prediction results. Finally, a case study is conducted that applies the proposed CVPP method to energy management of PHEVs. The simulation results manifest that the performance of the proposed energy management strategy (EMS) is dramatically improved after incorporating the forecasted velocity profile information given by the proposed CVPP method.

Cite

CITATION STYLE

APA

Zhang, S., Dou, W., Zhang, Y., Hao, W., Chen, Z., & Liu, Y. (2019). A Vehicle-Environment Cooperative Control Based Velocity Profile Prediction Method and Case Study in Energy Management of Plug-in Hybrid Electric Vehicles. IEEE Access, 7, 75965–75975. https://doi.org/10.1109/ACCESS.2019.2921949

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free