Economic-social-oriented energy management of plug-in hybrid electric vehicles including social cost of carbon
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Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
For plug-in hybrid electric vehicles (PHEVs), conventional energy management strategies (EMSs) incorporate the output of the battery and power sources for energy-saving studies. The source of the battery charge and the social cost of carbon (SCC) associated with carbon emissions result in the economic-social cost of climate and environmental damage, particularly when the battery charge comes from thermal power. Consequently, conventional EMSs cannot improve the efficiency of PHEVs with respect to the SCC from an environment-friendly perspective. Also, overuse of battery charge can provide low-cost vehicular propulsion, but lead to battery aging, implying an associated cost. In this context, the battery discharge and aging are conflicted in the design of EMSs for PHEVs. This paper develops a novel EMS by explicitly considering the social cost of carbon emissions using model predictive control (MPC). The strategy devises the trade -off between the energy consumption cost, battery life loss cost, and social cost of carbon emissions by minimizing their total cost over a specific driving range. The driving cycle is developed based on real -world data in Xi ' an City, and the MPC is employed to assess the performance of EMS in a PHEV bus. Meanwhile, the widely used EMSs are compared in the simulation analysis, including the rule-based strategy, dynamic programming, and Pontryagin ' s minimum principle. Moreover, two sources of thermal power and wind power for the battery charge are conducted and compared. The results demonstrate that the proposed MPC-based EMS can generate the minimum total cost compared to the EMSs only considering the energy consumption and battery aging costs. Compared to thermal power as the source of battery charge, wind power can remarkably lower the total cost using the MPC, achieving a 19.2 % improvement. In addition, the results also demonstrate that the total cost in the case of wind power can be lowered by 24.6 %, 25.7 %, and 27.5 % compared to thermal power for battery charge under the methods of rule-based strategy, Pontryagin ' s minimum principle and dynamic programming, respectively.
Açıklama
Anahtar Kelimeler
Plug-in hybrid electric vehicle, Energy management, Economy, Social cost of carbon, Model predictive control
Kaynak
Journal of Energy Storage
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
90
