A real-time blended energy management strategy of plug-in hybrid electric vehicles considering driving conditions

JOURNAL OF CLEANER PRODUCTION

卷:252

Article

Lei, Zhenzhen¹  Qin, Datong^2,3  Zhao, Pan^2,3  Li, Jie^2,3  Liu, Yonggang^2,3  Chen, Zheng⁴ 

[1] Chongqing Univ Sci & Technol, Sch Mech & Power Engn, Chongqing 401331, Peoples R China

[2] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China

[3] Chongqing Univ, Sch Automot Engn, Chongqing 400044, Peoples R China

[4] Kunming Univ Sci & Technol, Fac Transportat Engn, Kunming 650500, Yunnan, Peoples R China

关键词: Plug-in hybrid electric vehicles;    Energy management strategy;    Global optimization;    Driving condition;    Equivalent driving distance coefficient;   

DOI  :  10.1016/j.jclepro.2019.119735

来源: Elsevier

【 摘 要 】

In this study, a blended energy management strategy considering influences of driving conditions is proposed to improve the fuel economy of plug-in hybrid electric vehicles. To attain it, dynamic programming is firstly applied to solve and quantify influences of different driving conditions and driving distances. Then, the driving condition is identified by the K-means clustering algorithm in real time with the help of Global Positioning System and Geographical Information System. A blended energy management strategy is proposed to achieve the real-time energy allocation of the powertrain with incorporation of the identified driving conditions and the extracted rules, which includes the engine starting scheme, gear shifting schedule and torque distribution strategy. Simulation results reveal that the proposed strategy can effectively adapt to different driving conditions with the dramatic improvement of fuel economy and the decrement of calculation intensity and highlight the feasibility of real-time implementation. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free