HEV Energy Prediction Management Based on Future Road Condition China FAW Group Corporation

Format:

Book

Conference/Event

Author/Creator:

Zhao, Hui Chao, author.

Contributor:

Cui, Jinlong

Guo, Yuanke

Huo, Haitao

Jiaming, Liu

Song, Yangyang

Yang, Fang

Zhang, Qi

Zhang, Qiang

Conference Name:

WCX SAE World Congress Experience (2023-04-18 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

In order to further improve the vehicle economy of hybrid vehicles, this paper first discusses the existing hybrid energy management strategies, and analyzes the shortcomings of the existing strategies considering the actual road conditions, and points out the importance of future road condition information to energy management. Then, an energy prediction management strategy by acquiring future road condition information is proposed. The main work of this paper is centered on this strategy. This strategy is to use information about future working conditions provided by navigation and other sensing systems and predict energy consumption in future working conditions, so as to optimize the energy management strategy between engine and motor. The strategy is mainly composed of four parts: future information acquisition, future energy consumption prediction, energy management target calculation, and control target execution. Among them, future information acquisition is to obtain future road condition information through perception systems such as navigation and V2X; future energy consumption prediction is to estimate the energy demand in the future vehicle driving direction based on the future information; The energy management target calculation is to plan the energy distribution management method in advance with the goal of optimizing the economy; the control target execution is that each assembly component performs corresponding actions according to the energy distribution requirements. Finally, this paper takes the powertrain of a hybrid vehicle as the carrier, and conducts a powertrain bench test by simulating road conditions. The results show that the proposed HEV energy prediction management method based on future road condition information can realize the optimal allocation and management of energy by predicting the energy demand in the future driving direction on the basis of the existing control strategy. Ultimately, the vehicle economy can be further improved without changing driving habits

Notes:

Vendor supplied data

Publisher Number:

2023-01-0899

Access Restriction:

Restricted for use by site license