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دسته بندی:
مدیریت انرژی - Energy Management
سال انتشار:
2020
عنوان انگلیسی مقاله:
Online energy management strategy of fuel cell hybrid electric vehicles based on rule learning
ترجمه فارسی عنوان مقاله:
استراتژی مدیریت انرژی آنلاین از وسایل نقلیه برقی هیبریدی سلول سوختی بر اساس یادگیری قانون
منبع:
Sciencedirect - Elsevier - Journal of Cleaner Production, 260 (2020) 121017. doi:10.1016/j.jclepro.2020.121017
نویسنده:
Yonggang Liu a, **, Junjun Liu a, Datong Qin a, Guang Li b, Zheng Chen c, *, Yi Zhang d
چکیده انگلیسی:
In this paper, a rule learning based energy management strategy is proposed to achieve preferable energy
consumption economy for fuel cell hybrid electric vehicles. Firstly, the optimal control sequence of
fuel cell power and the state of charge trajectory of lithium-ion battery pack during driving are derived
offline by the Pontryagin’s minimum principle. Next, the K-means algorithm is employed to hierarchically
cluster the optimal solution into the simplified data set. Then, the repeated incremental pruning
to produce error reduction algorithm, as a propositional rule learning strategy, is leveraged to learn and
classify the underlying rules. Finally, the multiple linear regression algorithm is applied to fit the
abstracted parameters of generated rule set. Simulation results highlight that the proposed strategy can
achieve more than 95% savings of energy consumption economy, solved by Pontryagin’s minimum
principle, with less calculation intensity and without dependence on prior driving conditions, thereby
manifesting the feasibility of online application.
Keywords: Fuel cell hybrid electric vehicle | Energy management strategy | Hierarchical clustering | Rule learning
قیمت: رایگان
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