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Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain.

Authors :
Ju, Fei
Du, Wei
Zhuang, Weichao
Li, Bingbing
Wang, Tao
Wang, Weiwei
Ma, Huijie
Source :
Energy. Jun2024, Vol. 296, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

This study proposes a novel component sizing method for electric delivery trucks (EDTs) employing dual motor coupling powertrain (DMCP) to enhance both the energy efficiency and operating profitability. A control-oriented model for the EDT is first established, encompassing the three-mode DMCP dynamics. Variations in component size and mass have been modeled, with consideration of their effects on the load capacity. To maximize the average profit per kilometer over the truck's lifespan, four objective functions are defined to accommodate to the diverse types of cargo being transported. We formulate the optimization problem in a bi-level form, and propose a solution method that combines particle swarm optimization (PSO) handling parameter filtering with iterative dynamic programming (IDP) to minimize energy consumption. Three real-world delivery tests show that component sizing leads to an increase in the average profit per kilometer by 2.62 %–8.10 %. Upon evaluating the impact of powertrain and battery mass/volume on cargo capacity, the battery pricing ceases to impact the sizing of components. However, the electricity price and freight significantly influence the optimal size of components. Moreover, a sensitivity analysis focusing on market price factors underscores the importance of component sizing for maximizing profit, particularly in scenarios where freight costs fluctuate in commercial settings. • Optimal sizing for an electric delivery truck with a dual motor powertrain. • Both size and mass of the components are taken into optimization. • The average lifetime profit per kilometer of the truck is maximized. • Sensitivity of the optimal component size to market price changes is reported. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
296
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
176631474
Full Text :
https://doi.org/10.1016/j.energy.2024.131055