基于显式随机模型预测控制的功率分流式混合动力车辆能量管理策略
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摘要
混合动力车辆的能量管理策略对提高燃油经济性十分重要.为了提高功率分流式混合动力车辆的燃油经济性以及能量管理策略的实时性,设计了基于显式随机模型预测控制的能量管理策略.首先利用马尔科夫链预测车速,通过简化控制模型,把非线性的能量管理问题转化为线性二次优化问题,建立了以预测域内能量消耗最小为目标的随机模型预测策略(SMPC);然后通过参数化求解得到显式随机模型预测控制策略,该策略既保持了随机模型预测控制方法的优势,又提高了计算速度;最后在多个工况下进行仿真,对提出的能量管理策略的有效性进行验证.仿真结果表明:与基于规则的控制策略相比燃油经济性最高可提高28.64%,同时该策略在仿真中的平均计算时间为3.1 ms,具有实时运算潜力.
Energy management strategies are important for hybrid electric vehicles to improve fuel economy.In order to improve the fuel economy of power split hybrid vehicles and the real-time performance of energy management strategies,an energy management strategy based on explicit stochastic model predictive control was designed.Firstly,the Markov chain was used to predict the vehicle speed.Then by simplifying the control model and transforming the nonlinear energy management problem into a linear quadratic optimization problem,a stochastic model prediction strategy(SMPC) with the minimum energy consumption in the prediction domain was established.Secondly,the explicit stochastic model prediction strategy is obtained by solving the problem parametrically,and this strategy not only maintained the advantages of the stochastic model predictive control method,but also improved the calculation speed.Finally,the simulation is carried out under multiple working conditions to verify the effectiveness of the proposed energy management strategy.The simulation results show that fuel economy can be increased by up to 28.64% compared to rule-based control strategies,and the average calculation time in the simulation is 3.1 ms,which indicate that the strategy has real-time computing potential.
Energy management strategies are important for hybrid electric vehicles to improve fuel economy.In order to improve the fuel economy of power split hybrid vehicles and the real-time performance of energy management strategies,an energy management strategy based on explicit stochastic model predictive control was designed.Firstly,the Markov chain was used to predict the vehicle speed.Then by simplifying the control model and transforming the nonlinear energy management problem into a linear quadratic optimization problem,a stochastic model prediction strategy(SMPC) with the minimum energy consumption in the prediction domain was established.Secondly,the explicit stochastic model prediction strategy is obtained by solving the problem parametrically,and this strategy not only maintained the advantages of the stochastic model predictive control method,but also improved the calculation speed.Finally,the simulation is carried out under multiple working conditions to verify the effectiveness of the proposed energy management strategy.The simulation results show that fuel economy can be increased by up to 28.64% compared to rule-based control strategies,and the average calculation time in the simulation is 3.1 ms,which indicate that the strategy has real-time computing potential.
引文
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[19] BERNARDINI Daniele,BEMPORAD Alberto.Stabilizing model predictive control of stochastic constrained linear systems [J].IEEE Transactions on Automatic Control,2012,57(6):1468- 1480,.
[20] BOLZERN Paolo,COLANERI Patrizio,NICOLAO De Giuseppe.Markov jump linear systems with switching transition rates:mean square stability with dwell-time [J].Automatica,2010,46(6):1081- 1088.
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[22] BEMPORAD Alberto,MORARI Manfred,DUA Vivek,et al.The explicit linear quadratic regulator for constrained systems [J].Automatica,2002,38(1):3- 20.
[23] TORRISI D F,BEMPORAD A.HYSDEL—A tool for generating computational hybrid models for analysis and synthesis problems [J].IEEE Transactions on Control Systems Technology,2004,12(2):235- 249.
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[2] BORHAN Ali H,VAHIDI Ardalan,PHILLIPS M A,et al.Predictive energy management of a power-split hybrid electric vehicle [C]//Proceedings of the American Control Conference.St.Louis:IEEE,2009:3970- 3976.
[3] 邹渊,侯仕杰,韩尔樑,等.基于动态规划的混合动力商用车能量管理策略优化 [J].汽车工程,2012,34(8):663- 668.ZOU Yuan,HOU Shijie,HAN ErLiang,et al.Dynamic programming-based energy management strategy optimization for hybird electric commercial Vehicle [J].Automotive Engineering,2012,34(8):663- 668.
[4] 王钦普,游思雄,李亮,等.插电式混合动力汽车能量管理策略综述 [J].机械工程学报,2017,32(11):1- 18.WANG Qinpu,YOU Sixiong,LI Liang,et al.Survey on Energy management strategy for plug-in hybrid electric vehicles [J].Journal of Mechanical Engineering,2017,32(11):1- 18.
[5] ORTNER P,LANGTHALER P,ORTIZ J V G,et al.MPC for a diesel engine air path using an explicit approach for constraint systems [C]//Proceedings of the 2006 IEEE International Conference on Control Applications.Munich:IEEE,2006:2760- 2765.
[6] 谢海明,黄勇,王静,等.插电式混合动力汽车能量管理策略综述 [J].重庆理工大学学报,2015,29(7):1- 9.XIE Haiming,HUANG Yong,WANG Jing,et al.Review of energy management strategies for plug-in HEVs [J].Journal of Chongqing Institute of Technology,2015,29(7):1- 9.
[7] BEMPORAD Alberto,MORARI Manfred,DUA Vivek,et al.The explicit linear quadratic regulator for constrained systems [J].Automatica,2002,38(1):3- 20.
[8] 罗禹贡,陈涛,李克强.混合动力汽车非线性模型预测巡航控制 [J].机械工程学报,2015,51(16):11- 21.LUO Yugong,CHEN Tao,LI Keqiang.Nonlinear model predictive cruise control of hybrid electric vehicle [J].Journal of Mechanical Engineering,2015,51(16):11- 21.
[9] CAIRANO Di Stefano,BERNARDINI Daniele,BEMPORAD Alberto,et al.Stochastic MPC with learning for dri-ver-predictive vehicle control and its application to HEV energy management [J].IEEE Transactions on Control Systems Technology,2014,22(3):1018- 1031.
[10] 丁峰,王伟达,项昌乐,等.基于行驶工况分类的混合动力车辆速度预测方法与能量管理策略 [J].汽车工程,2017,39(11):1223- 1231.DING Feng,WANG Weida,XIANG Changle,et al.Speed prediction method and energy management strategy for a hybrid electric vehicle based on driving condition classification [J].Automotive Engineering,2017,39(11):1223- 1231
[11] 赵韩,吴迪.基于随机模型预测控制的并联式混合动力汽车控制策略研究 [J].汽车工程,2014,36(11):1289- 1294.ZHAO Han,WU Di.A research on the control strategy of a parallel HEV based on stochastic model predictive control [J].Automative Engineering,2014,36(11):1289- 1294.
[12] LI Weimin,XU Guoqing,XU Yangsheng.Online learning control for hybrid electric vehicle [J].Chinese Journal of Mechanical Engineering,2012,25(1):98- 106.
[13] 秦大同,杨官龙,刘永刚,等.插电式混合动力汽车能耗优化控制策略的研究 [J].汽车工程,2015,37(12):1366- 1371.QIN Datong,YANG Guanlong,LIU Yonggang,et al.A research on energy consumption optimization control strategy for plug-in hybrid electric vehicle [J].Automotive Engineering,2015,37(12):1366- 1371.
[14] 舒红,聂天雄,邓丽君,等.插电式并联混合动力汽车模型预测控制 [J].重庆大学学报,2011,34(5):36- 41.SHU Hong,NIE Tianxiong,DENG Lijun,et al.Model predictive control for a plug-in hybrid electric vehicle [J].Journal of Chongqing University,2011,34(5):36- 41.
[15] TAGHAVIPOUR A,AZAD N L,MCPHEE J.Real-time predictive control strategy for a plug-in hybrid electric powertrain [J].Mechatronics,2015,29:13- 27.
[16] CAIRANO Di S,LIANG W,KOLMANOVSKY V I,et al.Engine power smoothing energy management strategy for a series hybrid electric vehicle [C]//Proceedings of the 2011 American Control Conference.San Francisco:IEEE,2011:2101- 2106.
[17] MUTA Koichiro,YAMAZAKI Makoto,TOKIEDA Junji.Development of new-generation hybrid system THS II-Drastic improvement of power performance and fuel economy [R].[S.l.]:SAE Technical Paper,2004.
[18] DRGONA Jan,KVASNICA Michal,KLAUCO Martin,et al.Explicit stochastic MPC approach to building temperature control [C]//Proceedings of the 52nd IEEE Conference on Decision and Control.Florence:IEEE,2013:6440- 6445.
[19] BERNARDINI Daniele,BEMPORAD Alberto.Stabilizing model predictive control of stochastic constrained linear systems [J].IEEE Transactions on Automatic Control,2012,57(6):1468- 1480,.
[20] BOLZERN Paolo,COLANERI Patrizio,NICOLAO De Giuseppe.Markov jump linear systems with switching transition rates:mean square stability with dwell-time [J].Automatica,2010,46(6):1081- 1088.
[21] BORELLI Francesco.Constrained optimal control of linear and hybrid systems [J].Lecture Notes in Control and Information Sciences,2003,290(7):143- 171.
[22] BEMPORAD Alberto,MORARI Manfred,DUA Vivek,et al.The explicit linear quadratic regulator for constrained systems [J].Automatica,2002,38(1):3- 20.
[23] TORRISI D F,BEMPORAD A.HYSDEL—A tool for generating computational hybrid models for analysis and synthesis problems [J].IEEE Transactions on Control Systems Technology,2004,12(2):235- 249.
[24] HERCEG M,KVASNICA M,JONES C N,et al.Multi-parametric toolbox 3.0 [C]//Proceedings of the 2013 European Control Conference.Zurich:IEEE,2013:502- 510.
[25] 张聚.显式模型预测控制理论与应用 [M].北京:电子工业出版社,2015.
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