LAPSE:2023.21223
Published Article
LAPSE:2023.21223
Considering Well-to-Wheels Analysis in Control Design: Regenerative Suspension Helps to Reduce Greenhouse Gas Emissions from Battery Electric Vehicles
Xu Hu, Jinwei Sun, Yisong Chen, Qiu Liu, Liang Gu
March 21, 2023
Abstract
Recent research has investigated the energy saving potential of regenerative suspension. However, the greenhouse gas (GHG) emission mitigation potential of regenerative suspension in battery electric vehicles (BEVs) has not been considered. Life cycle assessment (LCA) is a typical method for evaluating GHG emissions but is rarely used in vehicle control design. Here we explore the effects of regenerative suspension on reducing the GHG emissions from a BEV, whose control design considers well-to-wheels (WTW) analysis. The work first conducts the WTW analysis and modelling of the GHG emissions from a BEV equipped with regenerative suspension. Based on the models, the relation between suspension control parameters and GHG emissions is obtained. To reach a compromise between dynamic performance and environmental benefit, two types of control parameters are recommended and their switch rules during the operation are proposed. Finally, we take a case study with different driving cycles, road levels and country contexts. The results show that considering WTW analysis in control design can contribute to GHG emission mitigation, especially for countries that have a high-carbon intensity of the electricity grid. These findings provide a quantitative reference for technology path decision on regenerative suspension. This paper may provide a new insight for employing LCA in vehicle design.
Keywords
battery electric vehicles, control design, greenhouse gas emission reduction, life cycle assessment, regenerative suspension
Suggested Citation
Hu X, Sun J, Chen Y, Liu Q, Gu L. Considering Well-to-Wheels Analysis in Control Design: Regenerative Suspension Helps to Reduce Greenhouse Gas Emissions from Battery Electric Vehicles. (2023). LAPSE:2023.21223
Author Affiliations
Hu X: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Sun J: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Chen Y: School of Automobile, Chang’an University, Xi’an 710064, China
Liu Q: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Gu L: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Journal Name
Energies
Volume
12
Issue
13
Article Number
E2594
Year
2019
Publication Date
2019-07-05
ISSN
1996-1073
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PII: en12132594, Publication Type: Journal Article
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LAPSE:2023.21223
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https://doi.org/10.3390/en12132594
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