A Rule-Based Energy Management Strategy Based on Dynamic Programming for Hydraulic Hybrid Vehicles

被引：16

作者：

Zhou, Haicheng ^{[1
]}

Xu, Zhaoping ^{[1
]}

Liu, Liang ^{[1
]}

Liu, Dong ^{[1
]}

Zhang, Lingling ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing 210094, Jiangsu, Peoples R China

来源：

MATHEMATICAL PROBLEMS IN ENGINEERING | 2018年 / 2018卷

基金：

中国国家自然科学基金;

关键词：

OPTIMIZATION;

D O I：

10.1155/2018/9492026

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Energy management strategy is very important for hydraulic hybrid vehicles to improve fuel economy. The rule-based energy management strategies are widely used in engineering practice due to their simplicity and practicality. However, their performances differ a lot from different parameters and control actions. A rule-based energy management strategy is designed in this paper to realize real-time control of a novel hydraulic hybrid vehicle, and a control parameter selection method based on dynamic programming is proposed to optimize its performance. Firstly, the simulation model of the hydraulic hybrid vehicle is built and validated by the data tested from prototype experimental platform. Based on the simulation model, the optimization method of dynamic programming is used to find the global optimal solution of the engine control for the UDDS drive cycle. Then, the engine control parameters of the rule-based energy management strategy are selected according to the engine control trajectory of the global optimal solution. The simulation results show that the 100km fuel consumption of the proposed rule-based energy management strategy is 12.7L, which is very close to the global optimal value of 12.4L and is suboptimal.

引用

页数：10

共 50 条

[41] Rule-based Control and Fuzzy Control for Power Management Strategies for Hybrid Vehicles
Correa, Fernanda C.
Eckert, Jony J.
Silva, Ludmila C. A.
Martins, Marcella
Baroncini, Virginia
Santiciolli, Fabio M.
Goncalves, Cristhiane
Dedini, Franco G.
[J]. 2020 IEEE COLOMBIAN CONFERENCE ON APPLICATIONS OF COMPUTATIONAL INTELLIGENCE (IEEE COLCACI 2020), 2020,
[42] Rule-based energy management system
[J]. Thomasson, F.Y., 2000, Fadum Enterp Inc, Boulder, CO, United States (20):
[43] Online energy management strategy of fuel cell hybrid electric vehicles based on rule learning
Liu, Yonggang
Liu, Junjun
Qin, Datong
Li, Guang
Chen, Zheng
Zhang, Yi
[J]. JOURNAL OF CLEANER PRODUCTION, 2020, 260
[44] Dynamometer test of a rule-based discharge strategy for plug-in hybrid electric vehicles
Larsson, Viktor
Arvidsson, Rickard
Westerlund, Anette
Akerblom, Niklas
[J]. IFAC PAPERSONLINE, 2016, 49 (11): : 141 - 146
[45] A Rule-Based Operating Strategy for the Pre-Design of a Powertrain for Hybrid Electric Vehicles
Lampe, Alexander
[J]. Lampe, Alexander, 1600, Springer Nature (116): : 56 - 62
[46] A Rule-based Energy Management Strategy with Current Estimation for Controlling Grid Connected Hybrid Energy Storage System
Farrokhi, Ehsan
Safari, Pouria
Ghoreishy, Hoda
[J]. 2023 14TH POWER ELECTRONICS, DRIVE SYSTEMS, AND TECHNOLOGIES CONFERENCE, PEDSTC, 2023,
[47] Blended Rule-Based Energy Management for PHEV: System Structure and Strategy
Padmarajan, Brahmadevan V.
McGordon, Andrew
Jennings, Paul A.
[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (10) : 8757 - 8762
[48] A rewriting framework for rule-based programming dynamic applications
Doroshenko, Anatoliy
Shevchenko, Ruslan
[J]. FUNDAMENTA INFORMATICAE, 2006, 72 (1-3) : 95 - 108
[49] A Rule-Based Energy Management Strategy for a Plug-in Hybrid School Bus Based on a Controller Area Network Bus
Peng, Jiankun
Fan, Hao
He, Hongwen
Pan, Deng
[J]. ENERGIES, 2015, 8 (06): : 5122 - 5142
[50] A distributed rule-based power management strategy in a photovoltaic/hybrid energy storage based on an active compensation filtering technique
Ghorashi Khalil Abadi, Seyyed Ali
Bidram, Ali
[J]. IET RENEWABLE POWER GENERATION, 2021, 15 (15) : 3688 - 3703

← 1 2 3 4 5 →