Efficiency improvement of a novel dual motor powertrain for plug-in hybrid electric buses

被引:5
作者
Cong Thanh Nguyen [1 ]
Walker, Paul D. [1 ]
Zhang, Nong [1 ]
Ruan, Jiageng [1 ]
机构
[1] Univ Technol Sydney, Fac Engn & Informat Technol, Sch Mech & Mechatron Engn, 15 Broadway, Ultimo, NSW 2007, Australia
关键词
Plug-in hybrid electric buses; dual motor powertrain; energy management strategy; enumeration method; dynamic programming; ENERGY MANAGEMENT; CONTROL STRATEGY; FUEL-ECONOMY; VEHICLES; DESIGN;
D O I
10.1177/0954407019896888
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Powertrain configuration plays an important role in the performance of plug-in hybrid electric buses. Current designs are the compromise between energy efficiency, dynamic ability, shifting smoothness and manufactural cost. To balance the above requirements, this research proposes a novel dual motor powertrain for plug-in hybrid electric buses. The efficiency improvement is compared to the conventional plug-in parallel hybrid electric buses with a single motor powertrain. Parameter designs of system components guarantee two configurations equivalently. To maximize the benefits of the proposed powertrain, this paper introduces an energy management strategy which coordinates enumeration method and dynamic programming to build the optimal maps of powertrain operation. The enumeration method determines the working points of power sources and gear states in all possible modes according to vehicle speed and power. The dynamic programming then selects the most suitable mode with the consideration of gear shifting and mode change in the optimal maps. Simulation results show that the dual motors work in peak efficiency region much more frequently than the single motor in different conditions. Therefore, the total energy cost of dual motor powertrain for entire driving cycles decreases significantly in comparison with the single motor powertrain, 6.5% in the LA92 and 6.7% in the Urban Dynamometer Driving Schedule.
引用
收藏
页码:1869 / 1882
页数:14
相关论文
共 28 条
[1]   Particle Swarm Optimization of Coupled Electromechanical Systems [J].
Al-Aawar, N. ;
Hijazi, T. M. ;
Arkadan, A. A. .
IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (05) :1314-1317
[2]   Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles [J].
Awadallah, Mohamed ;
Tawadros, Peter ;
Walker, Paul ;
Zhang, Nong .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2018, 232 (13) :1846-1862
[3]  
Du S, 2018, P IMECHE D, V233, P1067
[4]  
Ehsani M, 2010, POW ELECTR APPL, P1
[5]  
Enang W, 2016, P IMECHE D, V231, P99
[6]   Modelling and control of hybrid electric vehicles (A comprehensive review) [J].
Enang, Wisdom ;
Bannister, Chris .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 74 :1210-1239
[7]   Modelling and heuristic control of a parallel hybrid electric vehicle [J].
Enang, Wisdom ;
Bannister, Chris ;
Brace, Chris ;
Vagg, Chris .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2015, 229 (11) :1494-1513
[8]   Analysis and simulation of a torque assist automated manual transmission [J].
Galvagno, E. ;
Velardocchia, M. ;
Vigliani, A. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (06) :1877-1886
[9]   Energy management for plug-in hybrid electric vehicles considering optimal engine ON/OFF control and fast state-of-charge trajectory planning [J].
Guo, Ningyuan ;
Shen, Jiangwei ;
Xiao, Renxin ;
Yan, Wensheng ;
Chen, Zheng .
ENERGY, 2018, 163 :457-474
[10]   Comparison study on the battery models used for the energy management of batteries in electric vehicles [J].
He, Hongwen ;
Xiong, Rui ;
Guo, Hongqiang ;
Li, Shuchun .
ENERGY CONVERSION AND MANAGEMENT, 2012, 64 :113-121