Single-Cell Battery Pack Dimensioning Optimization Method for Plug-in Hybrid Electric Vehicles on ABNT Driving Cycle

2021-36-0078

02/04/2022

Features
Event
SAE BRASIL 2021 Web Forum
Authors Abstract
Content
Electric vehicles are spreading across the world as a promising solution for the creation of a clean and sustainable fleet as part of the mobility for the future. Mainly at emerging markets, such as the Brazil, an introductory step for this electrification process can be expected, where the Hybrid Electric Vehicles (HEV) play an important role as an enabler to this transition. This first electrification phase already contributes to the current mobility environmental challenges and provides a larger adaptation period for the industry and the infrastructure. Further studies are required to explore the battery pack dimensioning processes and its influences on the main characteristics of the powertrain. This work presents a dimensioning optimization process of single-cell battery packs for Plug-in Hybrid Electric Vehicles (PHEV) considering the impact of that over the vehicle performance and efficiency characteristics on the ABNT driving cycle. The analysis considers penalty points of performance and efficiency characteristics according to the dimensioning of the single-cell battery packs. The results are generated through simulations of multiple PHEV models on the software Dyfasim and MATLAB, which are compiled in a form of penalty maps, which in turn expresses the tradeoffs between the battery pack design and the evaluation criteria and also can be used for the optimization of the battery pack dimension. This work contributes to the field of knowledge by providing quality information to fundament discussions of HEV powertrain definition.
Meta TagsDetails
DOI
https://doi.org/10.4271/2021-36-0078
Pages
13
Citation
Falleiros, M., and Gioria, G., "Single-Cell Battery Pack Dimensioning Optimization Method for Plug-in Hybrid Electric Vehicles on ABNT Driving Cycle," SAE Technical Paper 2021-36-0078, 2022, https://doi.org/10.4271/2021-36-0078.
Additional Details
Publisher
Published
Feb 4, 2022
Product Code
2021-36-0078
Content Type
Technical Paper
Language
English