A Hierarchical Model Predictive Control Based Connected Series Hybrid Electric Vehicle Energy Management Considering Speed Planning Chongqing University of Technology, School of Vehicle

Format:

Book

Conference/Event

Author/Creator:

Tan, Senlin, author.

Contributor:

Chen, Jiahui

Hu, Bo

Lin, Yuqiang

Conference Name:

SAE 2022 Vehicle Electrification and Powertrain Diversification Technology Forum (2022-08-23 : Beijing, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

In the context of global warming and energy shortage crisis, how to deal with vehicle speed planning and energy management strategies using intelligent connected information is one of the most significant ways to improve traffic efficiency and vehicle fuel economy. In this paper, a hierarchical model predictive control algorithm based on the connected environment is designed for the study of series hybrid electric vehicles (HEVs). The higher level and the lower level controller share information with each other and solve two different problems aiming at improving its fuel efficiency. V2X (Vehicle to Everything) information is used as an input for the high-level controller to establish a model predictive framework to plan the future speed and improve its stability of the whole vehicle platoon. The low-level MPC provides a real-time HEV energy management strategy. The result shows that our hierarchical algorithm can achieve the vehicle platoon follow-up control while maintaining the fuel economy

Notes:

Vendor supplied data

Publisher Number:

2022-01-7064

Access Restriction:

Restricted for use by site license