基于道路工况分析的HEV控制策略优化方法

doi:10.12068/j.issn.1005-3026.2017.04.020

东北大学学报:自然科学版 ›› 2017, Vol. 38 ›› Issue (4): 551-556.DOI: 10.12068/j.issn.1005-3026.2017.04.020

基于道路工况分析的HEV控制策略优化方法

连静，范悟明，李琳辉，袁鲁山

(大连理工大学汽车工程学院，辽宁大连116024)

收稿日期:2015-12-04 修回日期:2015-12-04 出版日期:2017-04-15 发布日期:2017-04-11
通讯作者: 连静
作者简介:连静(1981-)，女，吉林公主岭人，大连理工大学副教授.
基金资助:
国家自然科学基金资助项目(61473057); 中央高校基本科研业务费专项资金资助项目(DUT15LK13).

Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV

LIAN Jing， FAN Wu-ming， LI Lin-hui， YUAN Lu-shan

School of Automotive Engineering， Dalian University of Technology， Dalian 116024， China.

Received:2015-12-04 Revised:2015-12-04 Online:2017-04-15 Published:2017-04-11
Contact: LI Lin-hui
About author:-
Supported by:
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摘要/Abstract

摘要： 以某并联式混动公交车为研究对象，建立了四种典型工况模型，采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子；分析了路面坡度与电池荷电状态(state of charge， SOC)目标值域调整之间的对应关系，设计了相应坡度自适应模块；提出了基于道路工况分析的混合动力汽车(hybrid electric vehicle， HEV)控制策略优化方法.典型工况下的仿真对比分析表明，该方法具有良好的工况适应能力，燃油经济性明显优于几类典型HEV控制策略.

关键词: 混合动力汽车, 工况识别, 蚁群优化, SOC目标值域, 控制策略

Abstract: Taking a parallel hybrid bus as research object， four kinds of typical working condition models were established， and the ant colony optimization algorithm was used to optimize the charge and discharge equivalent factor for each working condition in minimal equivalent fuel consumption control strategy. The relation between road gradient and adjustment of battery SOC target range was analyzed， and the corresponding gradient adaptive module was designed. A control strategy optimization method was proposed based on driving cycle recognition for HEV. The results of simulation and comparison analysis under typical working conditions showed that the method has very well driving condition adaptability， and its fuel economy is significantly higher than that of other several typical HEV control strategies.

Key words: HEV(hybrid electric vehicle), driving cycle recognition, ant colony optimization, SOC target range, control strategy

中图分类号:

U469.72

连静，范悟明，李琳辉，袁鲁山. 基于道路工况分析的HEV控制策略优化方法[J]. 东北大学学报:自然科学版, 2017, 38(4): 551-556.

LIAN Jing， FAN Wu-ming， LI Lin-hui， YUAN Lu-shan. Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV[J]. Journal of Northeastern University Natural Science, 2017, 38(4): 551-556.

参考文献

[1]Bayindir K ，Gzüküük M A，Teke A.A comprehensive overview of hybrid electric vehicle:powertrain configurations，powertrain control techniques and electronic control units［J］.Energy Conversion and Management，2011，52(2):1305-1313.
[2]于秀敏，曹珊，李君.混合动力汽车控制策略的研究现状及其发展趋势［J］.机械工程学报，2006，42(11):10-16.(Yu Xiu-min，Cao Shan，Li Jun.The current research condition and development trend of HEV［J］.Chinese Journal of Mechanical Engineering， 2006，42(11):10-16.)
[3]Martínez J S，Hissel D，Péra M C.Practical control structure and energy management of a testbed hybrid electric vehicle ［J］.IEEE Transactions on Vehicular Technology，2011，60(9):4139-4152.
[4]Mashadi B，Emadi S A M.Dual-mode power-split transmission for hybrid electric vehicles［J］.IEEE Transactions on Vehicular Technology， 2010，59(7):3223-3232.
[5]Dosthosseini R，Kouzani A Z，Sheikholeslam F.Direct method for optimal power management in hybrid electric vehicles［J］.International Journal of Automotive Technology，2011，12(6):943-950.
[6]Wang D，Lin X，Zhang Y.Fuzzy logic control for a parallel hybrid hydraulic excavator using genetic algorithm［J］.Automation in Construction，2011，20(5):581-587.
[7]Moura S J，Fathy H K，Callaway D S.A stochastic optimal control approach for power management in plug-in hybrid electric vehicles ［J］.IEEE Transactions on Control Systems Technology，2011，19(3):545-555.
[8]He H，Sun C，Zhang X.A method for identification of driving patterns in hybrid electric vehicles based on a LVQ neural network［J］.Energies，2012，5(9):3363-3380.
[9]Safaei A，Ha’iri-Yazdi M R，Esfahanian V，et al.Designing an intelligent control strategy for hybrid powertrains utilizing a fuzzy driving cycle identification agent［J］.Proceedings of the Institution of Mechanical Engineers，Part D:Journal of Automobile Engineering，2014，11(5):1-20.
[10]Jiang P，Shi Q，Chen W.Driving cycle construction method of city motors based on clustering method and Markov process［J］.China Mechanical Engineering，2010，21(23):2893-2897.
[11]Marano V，Rizzoni G，Tulpule P，et al.Intelligent energy management for plug-in hybrid electric vehicles:the role of its infrastructure in vehicle electrification［J］.Oil & Gas Science and Technology-Revue d’IFP Energies Nouvelles，2012，67(4):575-587.
[12]Unger J，Kozek M，Jakubek S.Nonlinear model predictive energy management controller with load and cycle prediction for non-road HEV［J］.Control Engineering Practice，2015，3(6):120-132.
[13]Wu J，Zhang C H，Cui N X.Fuzzy energy management strategy for a hybrid electric vehicle based on driving cycle recognition［J］.International Journal of Automotive Technology，2012，13(7):1159-1167.
[14]Van Keulen T，De Jager B，Serrarens A，et al.Optimal energy management in hybrid electric trucks using route information［J］.Oil & Gas Science and Technology-Revue de l’Institut Franais du Pétrole，2010，65(1):103-113.
[15]吕仁志，周雅夫，刘吉顺.基于工况识别的并联混合动力客车控制策略［C］//2014 中国汽车工程学会年会论文集.大连，2014:115-118.(Lyu Ren-zhi，Zhou Ya-fu，Liu Ji-shun.Control strategy of parallel hybrid electric city bus based on driving cycle recognition［C］//Proceeding of 2014 Annual Meeting of China Automotive Engineering Society.Dalian，2014:115-118.)
[16]Dorigo M，Maniezzo V，Colorni A.The ant system:an autocatalytic optimizing process［R］.Milano:Politecnico di Milano，1991.
[17]裴玉龙，邢恩辉.高等级公路纵坡的坡度、坡长限制分析［J］.哈尔滨工业大学学报，2005，37(5):629-632.(Pei Yu-long，Xing En-hui.Grade and its length limitation analysis of highway［J］.Journal of Harbin Institute of Technology，2005，37(5):629-632.)(上接第545页)
[12]Malachi M，Park S，Jun M B G.Modeling of dynamic micro-milling cutting forces ［J］.International Journal of Machine Tools and Manufacture，2009，49(7):586-598.
[13]Jin X，Latinas Y.Slip-line field model of micro-cutting process with round tool edge effect［J］.Journal of Materials Processing Technology，2011，211(3):339-355.
[14]高奇，巩亚东，周云光.单晶Ni₃Al基高温合金微铣削表面粗糙度试验研究［J］.中国机械工程，2016，27(6):801-804.(Gao Qi，Gong Ya-dong，Zhou Yun-guang.Experimental study on surface quality in micro-milling of single crystal Ni₃Al-based superalloy［J］.China Mechanical Engineering，2016，27(6):801-804.)
[15]Liu X，Devor R E，Kapoor S G.An analytical model for the prediction of minimum chip thickness in micro machining［J］.Journal of Manufacturing Science and Engineering，2006，128(2):474-485.

基于道路工况分析的HEV控制策略优化方法

Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV

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