雷达共用型智能混合动力汽车节能控制策略

解来卿; 张东好; 罗禹贡; 陈锐; 李克强

doi:10.16511/j.cnki.qhdxxb.2018.21.004

PDF(2906 KB)

清华大学学报（自然科学版） ›› 2018, Vol. 58 ›› Issue (3) : 286-291,297. DOI: 10.16511/j.cnki.qhdxxb.2018.21.004

汽车工程

雷达共用型智能混合动力汽车节能控制策略

解来卿^1,2, 张东好¹, 罗禹贡¹, 陈锐¹, 李克强¹

作者信息 +

Radar sharing energy-saving control strategy for intelligent hybrid electric vehicle

XIE Laiqing^1,2, ZHANG Donghao¹, LUO Yugong¹, CHEN Rui¹, LI Keqiang¹

Author information +

文章历史 +

摘要

为解决现有混合动力汽车能量管理常依赖固定循环工况设计，未考虑车辆实际运行环境所造成的节能潜力挖掘不足的问题，该文运用结构共用思想，提出共用雷达信号的智能混合动力汽车能量管理优化控制方法。依托雷达对前车运动信息的感知，划分4种不同场景和工作模式，通过动态优化汽车电机的驱动转矩并增加电机再生制动，从而在不增加额外硬件成本的前提下，提升智能混合动力汽车的节能性能。并以某混合动力客车为应用对象进行了实车道路试验，结果表明所提出的节能控制策略在城市拥堵路况下节能效果明显。

Abstract

A radar sharing based energy-saving control method was developed for intelligent hybrid electric vehicles to reduce energy loss caused by designs for fixed working conditions that disregard the actual running environment. Four scenarios were developed base on the relative motion of the vehicle in front of this vehicle. The motor drive torque was optimized with regenerative braking by the motor added for some scenarios. These control strategies reduce the hybrid electric vehicle energy use without adding extra hardware cost. Tests on different road conditions show that this intelligent energy-saving control strategy provides large energy savings especially on congested urban roads.

导出引用

解来卿, 张东好, 罗禹贡, 陈锐, 李克强. 雷达共用型智能混合动力汽车节能控制策略[J]. 清华大学学报（自然科学版）. 2018, 58(3): 286-291,297 https://doi.org/10.16511/j.cnki.qhdxxb.2018.21.004

XIE Laiqing, ZHANG Donghao, LUO Yugong, CHEN Rui, LI Keqiang. Radar sharing energy-saving control strategy for intelligent hybrid electric vehicle[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(3): 286-291,297 https://doi.org/10.16511/j.cnki.qhdxxb.2018.21.004

中图分类号： U461.6

参考文献

[1] CHAN C C, BOUSCAYROL A, CHEN K Y. Electric, hybrid, and fuel-cell vehicles:Architectures and modeling[J]. IEEE Transactions on Vehicular Technology, 2010, 59(2):589-598.
[2] 赵秀春, 郭戈. 混合动力电动汽车能量管理策略研究综述[J]. 自动化学报, 2016, 42(3):321-334. ZHAO X C, GUO G. Survey on energy management strategies for hybrid electric vehicles[J]. Acta Automatica Sinica, 2016, 42(3):321-334. (in Chinese)
[3] 潘龙. 基于动态交通信息的电动汽车节能行驶控制模型研究[D]. 北京:北京交通大学, 2014:9-12. PAN L. Study on energy-saving driving control model for electric vehicle based on dynamic traffic information[D]. Beijing, China:Beijing Jiaotong University, 2014:9-12. (in Chinese)
[4] Edmunds. We test the tips. (2009-05-05). http://www.Edmunds.com/fuel-economy/we-test-the-tips.html.
[5] BARTH M, BORIBOONSOMSIN K. Energy and emissions impacts of a freeway-based dynamic eco-driving system[J]. Transportation Research Part D:Transport and Environment, 2009, 14(6):400-410.
[6] GROSSARD M, KACHROUDI S, ABROUG N. An optimal energy-based approach for driving guidance of full electric vehicles[C]//Proceedings of 2012 IEEE International Symposium on Industrial Electronics (ISIE). Hangzhou, China:IEEE, 2012:1708-1713.
[7] KURIYAMA M, YAMAMOTO S, MIYATAKE M. Theoretical study on eco-driving technique for an electric vehicle with dynamic programming[C]//Proceedings of 2010 International Conference on Electrical Machines and Systems (ICEMS). Incheon, Korea:IEEE, 2010:2026-2030.
[8] MIYATAKE M, KURIYAMA M, TAKEDA Y. Theoretical study on eco-driving technique for an electric vehicle considering traffic signals[C]//Proceedings of 2011 IEEE Ninth International Conference on Power Electronics and Drive Systems (PEDS). Singapore:IEEE, 2011:733-738.
[9] MENSING F, TRIGUI R, BIDEAUX E. Vehicle trajectory optimization for application in ECO-driving[C]//Proceedings of 2011 IEEE Vehicle Power and Propulsion Conference (VPPC). Chicago, IL:IEEE, 2011:1-6.
[10] WU C X, ZHAO G Z, OU B. A fuel economy optimization system with applications in vehicles with human drivers and autonomous vehicles[J]. Transportation Research Part D:Transport and Environment, 2011, 16(7):515-524.
[11] VAN KEULEN T, DE JAGER B, FOSTER D, et al. Velocity trajectory optimization in hybrid electric trucks[C]//Proceedings of 2010 American Control Conference. Baltimore, MD:IEEE, 2010:5074-5079.
[12] RAKHA H, KAMALANATHSHARMA R K. Eco-driving at signalized intersections using V2I communication[C]//Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems. Washington DC, USA:IEEE, 2011:341-346.
[13] BHAVSAR P, HE Y M, CHOWDHURY M, et al. Energy consumption reduction strategies for plug-in hybrid electric vehicles with connected vehicle technology in urban areas[J]. Transportation Research Record:Journal of the Transportation Research Board, 2014, 2424(1):29-38.
[14] LANG D, SCHMIED R, DEL RE L. Prediction of preceding driver behavior for fuel efficient cooperative adaptive cruise control[J]. Simulation & Modeling, 2014, 7(1):14-20.
[15] ZHANG S W, ZHANG D H, LUO Y G, et al. Predictive energy management strategy for electric vehicles based on estimation of preceding vehicle future movements[C]//Proceedings of 2016 IEEE International Conference on Advanced Intelligent Mechatronics. Banff, AB:IEEE, 2016:1436-1441.
[16] CHAKRABARTI A. A new approach to structure sharing[J]. Journal of Computing and Information Science in Engineering, 2004, 4(1):11-19.
[17] LI K Q, CHEN T, LUO Y G, et al. Intelligent environment-friendly vehicles:Concept and case studies[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1):318-328.

基金

国家重点研发计划（2016YFB0100905）；国家自然科学基金重点项目（U1564208）；北京市科技计划项目（D161100003516002）

PDF(2906 KB)

Accesses

Citation

Detail

段落导航

收稿日期	出版日期
2017-09-20	2018-03-15
发布日期
2018-03-15

选择文件类型/文献管理软件名称

选择包含的内容

摘要

Abstract

关键词

Key words

引用本文

{{custom_sec.title}}

{{custom_sec.title}}

参考文献

基金

访问统计

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

摘要

Abstract

关键词

Key words

引用本文

{{custom_sec.title}}

{{custom_sec.title}}

参考文献

基金

访问统计