An all-in-one design method for plug-in hybrid electric buses considering uncertain factor of driving cycles

被引:20
作者
Hou, Daizheng [1 ]
Sun, Qun [1 ]
Bao, Chunjiang [1 ]
Cheng, Xingqun [1 ]
Guo, Hongqiang [1 ]
Zhao, Ying [1 ]
机构
[1] Liaocheng Univ, Sch Mech & Automot Engn, Liaocheng 252059, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Plug-in hybrid electric bus; All-in-one method; Typical driving cycle; Energy management; Receding horizon control; ENERGY-MANAGEMENT STRATEGY; PONTRYAGINS MINIMUM PRINCIPLE; MODEL-PREDICTIVE CONTROL; POWER MANAGEMENT; OPTIMIZATION; SYSTEM;
D O I
10.1016/j.apenergy.2019.113499
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The interaction between components and energy management is an obstacle for the fuel economy improvement of plug-in hybrid electric buses (PHEBs). Although the systematic method of design, optimization and energy management is recognized as a promising solution, two problems including the robust design of component matching considering the influence of uncertain driving cycles and the integrated design of energy management are still need to be solved. This paper proposes a novelty all-in-one method to address the issues. Firstly, a typical driving cycle construction method for city bus route is proposed to solve the first problem, based on a series of historical driving cycles. Secondly, a co-optimization framework including an outer layer constituted by multi-island genetic algorithm, and an inner layer constituted by dynamic programming (DP) is proposed, to find the best component matching. Specially, in the outer layer, two engines and six motors are taken as discrete design variables, meanwhile, the speed ratios of AMT and final driver are taken as continuous design variables; in the inner layer, the fuel consumption is taken as the objective of the outer layer. Finally, a receding horizon control (RHC)-based energy management strategy together with a predictive model of terminal state of charge (SOC) are proposed to solve the second problem, based on the same DP algorithm in the co-optimization framework. Simulation results demonstrate that the proposed all-in-one method can find the robust component matching; the RHC strategy can realize the real-time control, and its fuel economy is better than the rule-based strategy.
引用
收藏
页数:19
相关论文
共 39 条
[1]  
[Anonymous], 2013, IFAC P
[2]  
[Anonymous], IEEE CONTR SYST MAG
[3]   A Rule-Based Energy Management Strategy for Plug-in Hybrid Electric Vehicle (PHEV) [J].
Banvait, Harpreetsingh ;
Anwar, Sohel ;
Chen, Yaobin .
2009 AMERICAN CONTROL CONFERENCE, VOLS 1-9, 2009, :3938-3943
[4]  
Bayrak A., 2016, J MECH DESIGN, V138, P7
[5]   Design and analysis of power management strategy for range extended electric vehicle using dynamic programming [J].
Chen, Bo-Chiuan ;
Wu, Yuh-Yih ;
Tsai, Hsien-Chi .
APPLIED ENERGY, 2014, 113 :1764-1774
[6]   Fuzzy-based blended control for the energy management of a parallel plug-in hybrid electric vehicle [J].
Denis, Nicolas ;
Dubois, Maxime R. ;
Desrochers, Alain .
IET INTELLIGENT TRANSPORT SYSTEMS, 2015, 9 (01) :30-37
[7]   Techno-economic design of hybrid electric vehicles using multi objective optimization techniques [J].
Dimitrova, Zlatina ;
Marechal, Francois .
ENERGY, 2015, 91 :630-644
[8]   Equivalent fuel consumption optimal control of a series hybrid electric vehicle [J].
Gao, J-P ;
Zhu, G-M G. ;
Strangas, E. G. ;
Sun, F-C .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2009, 223 (D8) :1003-1018
[9]   Energy Management Control of Microturbine-Powered Plug-In Hybrid Electric Vehicles Using the Telemetry Equivalent Consumption Minimization Strategy [J].
Geng, Bo ;
Mills, James K. ;
Sun, Dong .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (09) :4238-4248
[10]   A systematic design and optimization method of transmission system and power management for a plug-in hybrid electric vehicle [J].
Guo, Hongqiang ;
Sun, Qun ;
Wang, Chong ;
Wang, Qinpu ;
Lu, Silong .
ENERGY, 2018, 148 :1006-1017