The Energy Consumption Characteristics of Electric Vehicles in the Coastal Area Based on the Powertrain Ocean University of China, Engineering College

Format:

Book

Conference/Event

Author/Creator:

Zhao, Zunlong, author.

Contributor:

Liao, Peng

Ning, Donghong

Wang, Tao

Conference Name:

SAE 2023 Intelligent Urban Air Mobility Symposium (2023-10-20 : Hangzhou, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

The sensitivity of the electric vehicle (EV) energy consumption characteristics has seriously hindered the promotion and development of vehicle electrification in the coastal area, as quantities of additional energy are caused by the complex and ever-changing coastal driving conditions. In that case, this paper aims to clarify the quantitative impacts of coastal driving conditions on EV energy consumption characteristics based on the coastal traffic data and the EV powertrain. Firstly, this paper analyzes the coastal driving conditions with the help of multisource traffic data. Secondly, the costal-adapted EV energy consumption model is constructed to reveal the relationship between powertrain performance and coastal driving conditions. Next, the EV coastal driving framework is proposed to identify the EV driving state in the coastal area. Finally, the EV energy consumption spatiotemporal characteristics in a typical coastal road are discussed with the help of simulations. The results show that coastal driving conditions have great impacts on the EV energy consumption characteristics, where the temporal difference of EV energy consumption in coastal areas is as high as 19.4%, causing a 19.1% difference in the SOC, and the EV spatial energy consumption characteristics are deteriorated by the high road slope and reversed wind direction once the EV velocity and acceleration are relatively large

Notes:

Vendor supplied data

Publisher Number:

2023-01-7098

Access Restriction:

Restricted for use by site license