A systematic design and optimization method of transmission system and power management for a plug-in hybrid electric vehicle

被引:54
作者
Guo, Hongqiang [1 ]
Sun, Qun [1 ]
Wang, Chong [1 ]
Wang, Qinpu [2 ]
Lu, Silong [1 ]
机构
[1] Liaocheng Univ, Sch Mech & Automot Engn, Liaocheng 252059, Shandong, Peoples R China
[2] Zhongtong Bus Hold Co Ltd, Liaocheng 252000, Shandong, Peoples R China
关键词
Plug-in hybrid electric vehicle; Transmission system; Design of experiment; Co-optimization; Power management; ENERGY MANAGEMENT; STRATEGY; BUS;
D O I
10.1016/j.energy.2018.01.152
中图分类号
O414.1 [热力学];
学科分类号
摘要
The transmission system together with power management will simultaneously affect the fuel economy of the plug-in hybrid electric vehicle (PHEV) with automated mechanical transmission (AMT). This paper strives to make three contributions to realize systematic design and optimization of the transmission and power management. Firstly, a design of experiment method is proposed to redesign the current transmission system of the PHEV with Optimal Latin Hypercube Design algorithm. Then, a co-optimization method is proposed to insight into the preferable speed ratios of the redesigned transmission system with multi-island genetic and dynamic programming algorithms. Finally, a Pontryagin's Minimum Principle-based self-identification controller is proposed to realize adaptive power management control, based on a significant finding that the constant solution of the co-state from off-line iteration optimization can be approximately identified by the mean value of the co-state with time-moving in the self identification controller. Results demonstrate that the current 6-speed ratio AMT can be reduced to 4, the fuel economy of the redesigned transmission system can be improved by 2.9% compared to the current transmission system and the self-identification controller can further improve the fuel economy of the PHEV compared to the conventional PI controller. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1006 / 1017
页数:12
相关论文
共 30 条
[1]   Adoption of PHEV/EV in Malaysia: A critical review on predicting consumer behaviour [J].
Adnan, Nadia ;
Nordin, Shahrina Md ;
Rahman, Imran .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 72 :849-862
[2]  
[Anonymous], 2014, IFAC P
[3]  
[Anonymous], 2013, IFAC P
[4]   Decomposition-Based Design Optimization of Hybrid Electric Powertrain Architectures: Simultaneous Configuration and Sizing Design [J].
Bayrak, Alparslan Emrah ;
Kang, Namwoo ;
Papalambros, Panos Y. .
JOURNAL OF MECHANICAL DESIGN, 2016, 138 (07)
[5]   MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle [J].
Borhan, Hoseinali ;
Vahidi, Ardalan ;
Phillips, Anthony M. ;
Kuang, Ming L. ;
Kolmanovsky, Ilya V. ;
Di Cairano, Stefano .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (03) :593-603
[6]   Comparison study of sampling methods for computer experiments using various performance measures [J].
Cho, Inyong ;
Lee, Yongbin ;
Ryu, Dongheum ;
Choi, Dong-Hoon .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2017, 55 (01) :221-235
[7]   Techno-economic design of hybrid electric vehicles using multi objective optimization techniques [J].
Dimitrova, Zlatina ;
Marechal, Francois .
ENERGY, 2015, 91 :630-644
[8]   Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness [J].
Du, Jiuyu ;
Chen, Jingfu ;
Song, Ziyou ;
Gao, Mingming ;
Ouyang, Minggao .
ENERGY, 2017, 121 :32-42
[9]   Electromobility Studies Based on Convex Optimization DESIGN AND CONTROL ISSUES REGARDING VEHICLE ELECTRIFICATION [J].
Egardt, Bo ;
Murgovski, Nikolce ;
Pourabdollah, Mitra ;
Mardh, Lars Johanne Sson .
IEEE CONTROL SYSTEMS MAGAZINE, 2014, 34 (02) :32-49
[10]   Charging, power management, and battery degradation mitigation in plug-in hybrid electric vehicles: A unified cost-optimal approach [J].
Hu, Xiaosong ;
Martinez, Clara Marina ;
Yang, Yalian .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 87 :4-16