Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain
Fei Ju,
Wei Du,
Weichao Zhuang,
Bingbing Li,
Tao Wang,
Weiwei Wang and
Huijie Ma
Energy, 2024, vol. 296, issue C
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.
Keywords: Electric delivery truck; Dual motor coupling powertrain; Energy management; Optimal sizing; Sensitivity analysis (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:296:y:2024:i:c:s0360544224008272
DOI: 10.1016/j.energy.2024.131055
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