Login Register Cart 0
Generic placeholder image

Recent Patents on Engineering

Editor-in-Chief

ISSN (Print): 1872-2121
ISSN (Online): 2212-4047

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Power Management for Plug-in Hybrid Electric Vehicle with Automated Mechanical Transmission using Multiple Dimensional Scaling Method

Author(s): Zhenyou Wang, Qun Sun*, Hongqiang Guo and Ying Zhao

Volume 14, Issue 1, 2020

Page: [133 - 141] Pages: 9

DOI: 10.2174/1872212113666190618105623

Price: $65

Abstract

Background: The study of kerosene fuel for gasoline engines is of great significance to the supply, management, storage and transportation of military fuel, as well as its safety. Small aviation two-stroke kerosene engine fuel injection controller is the key technology of kerosene engines. It is very important to improve the performance of kerosene engine by controlling the air-fuel ratio accurately.

Objective: The initial injection pulse spectrum was firstly obtained by numerical calculation in the absence of kerosene injection pulse spectrum, and then the injection controller was designed based on the initial injection pulse spectrum.

Methodology: Firstly, a numerical model of the whole engine was established by using BOOST software. The air mass flow data of the inlet was obtained through numerical calculation. The amount of initial engine fuel injection was calculated according to the requirements of air-fuel ratios in each working condition, from which an initial injection pulse spectrum was obtained. Then, based on Free scale 16-bit embedded micro-controller MC9S12DP512, a kerosene engine fuel injection controller was developed, together with the circuit was also designed. According to the initial fuel injection pulse spectrum, a two-dimensional interpolation algorithm was developed by using assembly language and C language mixed programming, and the anti-electromagnetic interference ability of the controller was further enhanced. Finally, the accuracy of the initial injection pulse spectrum and the performance and reliability of the injection controller of the kerosene engine were verified by the kerosene engine bench test.

Conclusion: The experimental results show that the numerical model was accurate, and the development time of the injection controller was shortened by using the numerical model to calculate the initial injection pulse spectra. The developed controller was stable and reliable, which can meet the control requirement.

Keywords: Plug-in hybrid electric vehicle, predictive power management, dynamic programing, multiple dimensional scaling, kerosene engines, injection controller.

Graphical Abstract

[1]
Y. Huang, H. Wang, A. Khajepour, and J. Ji, "Model predictive control power management strategies for HEVs: A review", J. Power Sources, vol. 341, pp. 91-106, 2017.
[http://dx.doi.org/10.1016/j.jpowsour.2016.11.106]
[2]
A. Santucci, A. Sorniotti, and C. Lekakou, "Power split strategies for hybrid energy storage systems for vehicular applications", J. Power Sources, vol. 258, pp. 395-407, 2014.
[http://dx.doi.org/10.1016/j.jpowsour.2014.01.118]
[3]
A.A. Malikopoulos, "Supervisory power management control algorithms for hybrid electric vehicles: a survey", IEEE Trans. Intell. Transp. Syst., vol. 15, pp. 1869-1885, 2014.
[http://dx.doi.org/10.1109/TITS.2014.2309674]
[4]
Z. Chen, R. Xiong, and J. Cao, "Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions", Energy, vol. 96, pp. 197-208, 2016.
[http://dx.doi.org/10.1016/j.energy.2015.12.071]
[5]
C.M. Martinez, X. Hu, and D. Cao, "Energy management in plug-in hybrid electric vehicles: recent progress and a connected vehicles perspective", IEEE Trans. Vehicular Technol., pp. 1-16, 2016.
[6]
J. Aghaei, A.E. Nezhad, and A. Rabiee, "Contribution of plug-in hybrid electric vehicles in power system uncertainty management", Renew. Sustain. Energy Rev., vol. 59, pp. 450-458, 2016.
[http://dx.doi.org/10.1016/j.rser.2015.12.207]
[7]
M.F.M. Sabri, K.A. Danapalasingam, and M.F. Rahmat, "A review on hybrid electric vehicles architecture and energy management strategies", Renew. Sustain. Energy Rev., vol. 53, pp. 1433-1442, 2016.
[http://dx.doi.org/10.1016/j.rser.2015.09.036]
[8]
N. Cui, G. Bu, and J. Wu, "“Real-time optimization of energy management strategy for plug-in parallel hybrid electric vehicles”, Transactions of China Electro technical", Society, vol. 26, pp. 155-160, 2011.
[9]
J. Peng, H. He, and R. Xiong, "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming", Appl. Energy, vol. 185, pp. 1633-1643, 2017.
[http://dx.doi.org/10.1016/j.apenergy.2015.12.031]
[10]
J. Peng, H. Fan, and H. He, "A rule-based energy management strategy for a plug-in hybrid school bus based on a controller area network bus", Energies, vol. 8, pp. 5122-5142, 2015.
[http://dx.doi.org/10.3390/en8065122]
[11]
S.G. Wirasingha, and A. Emadi, "Classification and review of control strategies for plug-in hybrid electric vehicles", IEEE Trans. Vehicular Technol., vol. 60, pp. 111-122, 2011.
[http://dx.doi.org/10.1109/TVT.2010.2090178]
[12]
S.G. Li, S.M. Sharkh, and F.C. Walsh, "Energy and battery management of a plug-in series hybrid electric vehicle using fuzzy logic", Vehicular Technology IEEE Transactions on, vol. 60, pp. 3571-3585, 2011.
[http://dx.doi.org/10.1109/TVT.2011.2165571]
[13]
O. Sundstrom, and L. Guzzella, A generic dynamic programming Matlab functionControl Applications., IEEE, 2009, pp. 1625-1630.
[http://dx.doi.org/10.1109/CCA.2009.5281131]
[14]
E.V. Denardo, Dynamic programming: models and applications., Prentice Hall PTR: NJ, USA, 2003.
[15]
S. Zhang, R. Xiong, and J. Cao, "Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system", Appl. Energy, vol. 179, pp. 316-328, 2016.
[http://dx.doi.org/10.1016/j.apenergy.2016.06.153]
[16]
J. Salpakari, and P. Lund, "Optimal and rule-based control strategies for energy flexibility in buildings with PHEV", Appl. Energy, vol. 161, pp. 425-436, 2016.
[http://dx.doi.org/10.1016/j.apenergy.2015.10.036]
[17]
Z. Chen, C.C. Mi, and J. Xu, "Energy management for a power-split plug-in hybrid electric vehicle based on dynamic programming and neural networks", IEEE Trans. Vehicular Technol., vol. 63, pp. 1567-1580, 2014.
[http://dx.doi.org/10.1109/TVT.2013.2287102]
[18]
X. Lin, A. Ivanco, and Z. Filipi, "Optimization of rule-based control strategy for a hydraulic-electric hybrid light urban vehicle based on dynamic programming", SAE Int. J. Alternative Powertrains, vol. 1, pp. 249-259, 2012.
[http://dx.doi.org/10.4271/2012-01-1015]
[19]
L. Lai, and M. Ehsani, "Dynamic programming optimized constrained engine on and off control strategy for parallel HEV", Proc. of IEEE Vehicle Power and Propulsion Conference vol. 85, pp. 1- 5, 2013.
[http://dx.doi.org/10.1109/VPPC.2013.6671731]
[20]
C. Sun, and J.Q. Li, Energy management method for plug-in hybrid electric vehicle and system China Patent, 2018.CN 108909702 A..
[21]
J.Q. Xi, and Y. Chen, "Research on Conflict Decision between Shift Schedule and Multienergy Management for PHEV with Automatic Mechanical Transmission under Special Driving Cycles", Math. Probl. Eng., vol. 6, pp. 1-8, 2013.
[http://dx.doi.org/10.1155/2013/517387]
[22]
C.N. Zhang, W. Zhou, Z.F. Wang, and J.Q. Li, Energy management method for electric vehicle extended range mode China Patent, 2015.CN 105667499 A.
[23]
H. Lee, J. Jeong, and Y.I. Park, "“Energy management strategy of hybrid electric vehicle using battery state of charge trajectory information”, Int. J. Precis. Eng. Manuf.-", Green Technol., vol. 4, pp. 79-86, 2017.
[http://dx.doi.org/10.1007/s40684-017-0011-4]
[24]
E. Mehrdad, Y. Gao, S.E. Gay, and E. Ali, Modern electric, hybrid electric and fuel cell vehicles fundamentals, theory, and design., CRC Press, 2005.
[25]
H. Lee, Y. Park, and S.W. Cha, "Power management strategy of hybrid electric vehicle using power split ratio line control strategy based on dynamic programming", Int. Conf. Control, 2015pp. 1739-1742
[http://dx.doi.org/10.1109/ICCAS.2015.7364645]
[26]
Z. Zhou, Machine Learning. Tsinghua University press, BJ, China, 2016.

Rights & Permissions Print Cite
Article Metrics
5
© 2024 Bentham Science Publishers | Privacy Policy