混合动力电动汽车控制策略的优化研究
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摘要
控制策略是混合动力电动汽车的关键技术之一,本文结合国家“863”计划电动汽车重大专项的研究课题“电动汽车控制算法与基础技术研究”的研究工作,针对串并联混合动力汽车分别建立了串联和并联混合动力汽车的仿真模型及其相应的能量管理控制策略。并在此基础上,应用模糊逻辑技术,制定了模糊逻辑控制策略,构建了模糊推理器,用以确定发动机和电机的最佳转矩分配。以并联混合动力汽车为研究对象,UDDS、CHINA、NEDC三种循环工况的仿真结果显示,在燃油经济性方面,模糊控制与电辅助控制相比,模糊控制下的整车燃油经济性分别提高9.3%、8.4%和7.6%。为实现模糊逻辑控制在实际HEV上的应用打下了良好的基础。
本文将蓄电池高比能量和超级电容高比功率的优点结合起来,建立了复合电源模型,并且制定了相应的控制策略,以避免电池大电流充放电和提高制动能量的回收率。在UDDS和NEDC循环工况下,分别对复合电源和单一的电池电源进行仿真,结果表明复合电源制动能量回收率分别为71.4%、81.3%,而单一的电池电源制动能量回收率分别为43.2%、68.5%,复合电源的引入使得制动能量回收率分别提高28.1%和12.8%。
综合考虑动力系统匹配参数和控制策略参数对整车性能的影响,提出将遗传算法和模拟退火算法相结合的组合优化算法,分别对以油耗为单目标和以油耗和排放为多目标进行了优化分析。优化结果表明,单目标优化前后进行对比,优化后并联混合动力汽车油耗降低9.6%左右,排放也有所下降;多目标优化前后相比,优化后并联混合动力汽车油耗下降约7.1%,而CO、HC和NO_x排放降低得比较多,优化后三者分别下降23.4%、5.6%和17.4%。
Control strategy for hybrid electric vehicle is one of the key technologies. Supported by the major project "Research on Control Algorithm and Basis Technology for Electric Vehicles" under "High-Tech R&D Program of China", the energy management control strategies for series and parallel hybrid electric vehicles have been research. On this basis, a fuzzy logic control strategy has been build in order to distribute the torque between engine and motor reasonably. The simulation results of three cycles UDDS、CHINA and NEDC show that the fuel economy in fuzzy control strategy is better. It improves 9.3%、8.4%and 7.6% respectively compared with the electric assist control strategy. This has laid a good foundation for the application of a fuzzy logic control strategy in the actual hybrid electric vehicles.
In this paper, combined the benefits of batteries and ultra capacitors, a hybrid power system has been model and the corresponding control strategy in order to avoid the high current and improve the recovery of braking energy has been research. The simulations of the hybrid power system and the battery power system have been done in the cycles of UDDS and NEDC respectively. The results show that the braking energy recovery rates of the hybrid power system are 71.4% and 81.3%, and that of the battery power system are 43.2% and 68.5%.
In view of optimizing for design parameters, considered of performances on hybrid electrical vehicle of power-train parameters and control parameters, the optimizations on both parameters are concurrently performed. A new optimization scheme in which the genetic algorithm is used combined with simulated annealing algorithm is proposed. The optimizations for single-objective function and multi-objective function have been done respectively. Optimization results show that the fuel consumption of the single-objective optimization reduces 9.6% and emissions also decline compared with pre-optimization, and that of the multi-objective optimization reduces 7.1% and emissions of CO, HC and NO_x fell 23.4%, 5.6% and 17.4% compared with pre-optimization.
本文将蓄电池高比能量和超级电容高比功率的优点结合起来,建立了复合电源模型,并且制定了相应的控制策略,以避免电池大电流充放电和提高制动能量的回收率。在UDDS和NEDC循环工况下,分别对复合电源和单一的电池电源进行仿真,结果表明复合电源制动能量回收率分别为71.4%、81.3%,而单一的电池电源制动能量回收率分别为43.2%、68.5%,复合电源的引入使得制动能量回收率分别提高28.1%和12.8%。
综合考虑动力系统匹配参数和控制策略参数对整车性能的影响,提出将遗传算法和模拟退火算法相结合的组合优化算法,分别对以油耗为单目标和以油耗和排放为多目标进行了优化分析。优化结果表明,单目标优化前后进行对比,优化后并联混合动力汽车油耗降低9.6%左右,排放也有所下降;多目标优化前后相比,优化后并联混合动力汽车油耗下降约7.1%,而CO、HC和NO_x排放降低得比较多,优化后三者分别下降23.4%、5.6%和17.4%。
Control strategy for hybrid electric vehicle is one of the key technologies. Supported by the major project "Research on Control Algorithm and Basis Technology for Electric Vehicles" under "High-Tech R&D Program of China", the energy management control strategies for series and parallel hybrid electric vehicles have been research. On this basis, a fuzzy logic control strategy has been build in order to distribute the torque between engine and motor reasonably. The simulation results of three cycles UDDS、CHINA and NEDC show that the fuel economy in fuzzy control strategy is better. It improves 9.3%、8.4%and 7.6% respectively compared with the electric assist control strategy. This has laid a good foundation for the application of a fuzzy logic control strategy in the actual hybrid electric vehicles.
In this paper, combined the benefits of batteries and ultra capacitors, a hybrid power system has been model and the corresponding control strategy in order to avoid the high current and improve the recovery of braking energy has been research. The simulations of the hybrid power system and the battery power system have been done in the cycles of UDDS and NEDC respectively. The results show that the braking energy recovery rates of the hybrid power system are 71.4% and 81.3%, and that of the battery power system are 43.2% and 68.5%.
In view of optimizing for design parameters, considered of performances on hybrid electrical vehicle of power-train parameters and control parameters, the optimizations on both parameters are concurrently performed. A new optimization scheme in which the genetic algorithm is used combined with simulated annealing algorithm is proposed. The optimizations for single-objective function and multi-objective function have been done respectively. Optimization results show that the fuel consumption of the single-objective optimization reduces 9.6% and emissions also decline compared with pre-optimization, and that of the multi-objective optimization reduces 7.1% and emissions of CO, HC and NO_x fell 23.4%, 5.6% and 17.4% compared with pre-optimization.
引文
[1]胡骅,宋慧.电动汽车(第二版)[M].北京:人民交通出版社,2006
[2]罗永革,冯樱,何晓春.混合电动汽车的开发前景[J].湖北汽车工业学院学报,2000,14(1)
[3]岳东鹏,郝志勇,张俊智.混合动力电动汽车研究开发及前景展望[J].拖拉机与农用运输车,2004,(02)
[4]沈同全,程夕明,孙逢春.混合动力汽车的发展趋势[J].农业装备与车辆工程,2006,(3).
[5]蔡梦贫.混合动力系统概述[J].汽车电器,2005,1:55-59.
[6]刘发文.HEV多能源动力总成控制系统的研究与实现[D].华中科技大学硕士学位论文,2004
[7]陈洁平,王耀南,徐华,王辉.基于DSP的混合动力汽车能源总成控制系统[J].控制工程,2003
[8]朱庆林,王庆年,曾小华,于远彬,王鹏宇.基于V模式的混合动力汽车多能源动力总成控制器开发平台[J].吉林大学学报(工学版),2007,(06),
[9]鲍辰宇,冯旭云.混合动力汽车研究现状和发展趋势[J].中国科技信息,2006,(18).
[10]信继欣.清洁汽车的发展与东风公司的发展战略研究[D].武汉理工大学硕士学位论文,2002.
[11]Powers W F,Nicastri P R.Automotive vehicle control challenges in the 21~(st) century.Control Engineering Practice 2000,8(6):605-618
[12]刘金玲,宋健,于良耀,王玉海等.并联混合动力客车控制策略比较[J].公路交通科技,2005,22(1):144-146
[13]卢山,高峰,史广奎.并联型混合动力汽车的仿真研究[J].机电工程技术,2005,34(5):59-61
[14]刘明辉,混合动力客车整车控制策略及总成参数匹配研究[D].吉林大学博士学位论文.2005.03
[15]王伟华.并联混合动力汽车的控制[D].吉林大学博士学位论文,2006.04
[16]Matthew Zolot,Dual-Source Energy Storage-Control and Performance Advantages in Advanced Vehicles,EVS-20,November 2003
[17]Delparat S,Lauber J L.Guerra T M,et al.Control of a parallel hybrid powertrain:optimal control.IEEE Trans.contr.Syst.Technol,2004,53(3):872—881
[18]K.T.Chau,Y.S.Wong.Overview of power management in hybrid electric vehicles.Energy Conversion and Management 2002,43:1953-1968.
[19]Laura V.Guillermo R.Optimization of power management in hybrid electric vehicle using dynamic programming.Mathematics and Computers in Simulation.2006,73:244-254.
[20]古艳春,殷承良,张建武.并联混合动力汽车扭矩协调控制策略仿真研究[J].系统仿真学报,2007,19(3)
[21]李兴虎.电动汽车概论[M].北京:北京理工大学出版,2005
[22]浦金欢,殷承良,张建武.遗传算法在混合动力汽车汽车控制策略优化中的应用[J].中国机械工程,2005(7):648-651
[23]Won J S,Langari R,Ehsani M.An energy management and charge sustaining strategy for a
[50]张志涌.MATLAB教程—基于6.x版[M].北京:航空航天大学出版社,2001.4
[51]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[52]王庆年,金启前,初亮,王伟华.传动系参数和控制参数对并联混合动力轿车性能的影响[J].吉林大学学报(工学版),2005,(03)
[53]金启前.混合动力客车试验与评价问题研究[D].吉林大学博士学位论文,2006.06
[54]Ippolito L,Loia V,Siano P.Extended fuzzy c-means and genetic algorithms to optimize power flow management in hybrid electric vehicles.Proc.IEEE Conference on Control Applications,Istanbul,Turkey,2003,V1.115-119
[55]刘万辉,田树军,贾春强等.混合遗传-模拟退火算法应用于液压集成块优化设计的研究[J].中国机械工程,2007(17):2021-2025.
[56]Johnson V H,Wipke K B,Rausen D J.HEV control strategy for real-time optimization of fuel economy and emissions.SAE Paper 2000-01-1543,2000
[57]雷英杰,张善文,李续武,周创明.Matlab-遗传算法工具箱及应用[M].西安:西安电子科技大学出版社,2005.04
[58]Wang Zhangcheng,Li Weimin.Optimization of Series Hybrid Electric Vehicle Operational Parameters By Simulated Annealing Algorithm[C]//2007 IEEE International Conference on Control and Automation,Guangzhou,CHINA,May30 to Junel,2007.
[59]Huang Bufu,Wang Zhangcheng,Xu Yangsheng.Multi-Objective Genetic Algorithm for Hybrid Electric Vehicle Parameter Optimization[C]//Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems,Beijing,China,October2006.
[60]Fang Licun,Qin Shiyin.Concurrent Optimization for Parameters of Powertrain and Control System of Hybrid Electric Vehicle Based on Multi-Objective Genetic Algorithms [C]//SICE-ICASE International Joint Conference 2006.Bexco,Korea,Oct 2006.
[61]Gakdi V,Ippolite L,Piccolo A,et al.Evaluation of Emissions Influence on Hybrid Electric Vehicles Sizing[C]//Process of International Conference on Power Electronics,Electrical Drives,Advanced Machines and Power Quality(SPEEDAM2000),2000(A4):1-7
[62]Gao Wenzhong,Porandla S K.Design Optimization of a Parallel Hybrid Electric Power train[C]//IEEE Conference on Vehicle Power and Propulsion,2005:530-535.
[63]张翔,赵韩,钱立军,张炳力.电动汽车仿真软件ADVISOR[J].汽车研究与开发,2003,(4)
[64]Wipke K,Markel T,Nelson D.Optimizing energy management strategy and degree of hybridization for a hydrogen fuel cell SUV.Proc.the 18th International Electric Vehicle Symposium,Berlin,Germany,2001
[2]罗永革,冯樱,何晓春.混合电动汽车的开发前景[J].湖北汽车工业学院学报,2000,14(1)
[3]岳东鹏,郝志勇,张俊智.混合动力电动汽车研究开发及前景展望[J].拖拉机与农用运输车,2004,(02)
[4]沈同全,程夕明,孙逢春.混合动力汽车的发展趋势[J].农业装备与车辆工程,2006,(3).
[5]蔡梦贫.混合动力系统概述[J].汽车电器,2005,1:55-59.
[6]刘发文.HEV多能源动力总成控制系统的研究与实现[D].华中科技大学硕士学位论文,2004
[7]陈洁平,王耀南,徐华,王辉.基于DSP的混合动力汽车能源总成控制系统[J].控制工程,2003
[8]朱庆林,王庆年,曾小华,于远彬,王鹏宇.基于V模式的混合动力汽车多能源动力总成控制器开发平台[J].吉林大学学报(工学版),2007,(06),
[9]鲍辰宇,冯旭云.混合动力汽车研究现状和发展趋势[J].中国科技信息,2006,(18).
[10]信继欣.清洁汽车的发展与东风公司的发展战略研究[D].武汉理工大学硕士学位论文,2002.
[11]Powers W F,Nicastri P R.Automotive vehicle control challenges in the 21~(st) century.Control Engineering Practice 2000,8(6):605-618
[12]刘金玲,宋健,于良耀,王玉海等.并联混合动力客车控制策略比较[J].公路交通科技,2005,22(1):144-146
[13]卢山,高峰,史广奎.并联型混合动力汽车的仿真研究[J].机电工程技术,2005,34(5):59-61
[14]刘明辉,混合动力客车整车控制策略及总成参数匹配研究[D].吉林大学博士学位论文.2005.03
[15]王伟华.并联混合动力汽车的控制[D].吉林大学博士学位论文,2006.04
[16]Matthew Zolot,Dual-Source Energy Storage-Control and Performance Advantages in Advanced Vehicles,EVS-20,November 2003
[17]Delparat S,Lauber J L.Guerra T M,et al.Control of a parallel hybrid powertrain:optimal control.IEEE Trans.contr.Syst.Technol,2004,53(3):872—881
[18]K.T.Chau,Y.S.Wong.Overview of power management in hybrid electric vehicles.Energy Conversion and Management 2002,43:1953-1968.
[19]Laura V.Guillermo R.Optimization of power management in hybrid electric vehicle using dynamic programming.Mathematics and Computers in Simulation.2006,73:244-254.
[20]古艳春,殷承良,张建武.并联混合动力汽车扭矩协调控制策略仿真研究[J].系统仿真学报,2007,19(3)
[21]李兴虎.电动汽车概论[M].北京:北京理工大学出版,2005
[22]浦金欢,殷承良,张建武.遗传算法在混合动力汽车汽车控制策略优化中的应用[J].中国机械工程,2005(7):648-651
[23]Won J S,Langari R,Ehsani M.An energy management and charge sustaining strategy for a
[50]张志涌.MATLAB教程—基于6.x版[M].北京:航空航天大学出版社,2001.4
[51]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[52]王庆年,金启前,初亮,王伟华.传动系参数和控制参数对并联混合动力轿车性能的影响[J].吉林大学学报(工学版),2005,(03)
[53]金启前.混合动力客车试验与评价问题研究[D].吉林大学博士学位论文,2006.06
[54]Ippolito L,Loia V,Siano P.Extended fuzzy c-means and genetic algorithms to optimize power flow management in hybrid electric vehicles.Proc.IEEE Conference on Control Applications,Istanbul,Turkey,2003,V1.115-119
[55]刘万辉,田树军,贾春强等.混合遗传-模拟退火算法应用于液压集成块优化设计的研究[J].中国机械工程,2007(17):2021-2025.
[56]Johnson V H,Wipke K B,Rausen D J.HEV control strategy for real-time optimization of fuel economy and emissions.SAE Paper 2000-01-1543,2000
[57]雷英杰,张善文,李续武,周创明.Matlab-遗传算法工具箱及应用[M].西安:西安电子科技大学出版社,2005.04
[58]Wang Zhangcheng,Li Weimin.Optimization of Series Hybrid Electric Vehicle Operational Parameters By Simulated Annealing Algorithm[C]//2007 IEEE International Conference on Control and Automation,Guangzhou,CHINA,May30 to Junel,2007.
[59]Huang Bufu,Wang Zhangcheng,Xu Yangsheng.Multi-Objective Genetic Algorithm for Hybrid Electric Vehicle Parameter Optimization[C]//Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems,Beijing,China,October2006.
[60]Fang Licun,Qin Shiyin.Concurrent Optimization for Parameters of Powertrain and Control System of Hybrid Electric Vehicle Based on Multi-Objective Genetic Algorithms [C]//SICE-ICASE International Joint Conference 2006.Bexco,Korea,Oct 2006.
[61]Gakdi V,Ippolite L,Piccolo A,et al.Evaluation of Emissions Influence on Hybrid Electric Vehicles Sizing[C]//Process of International Conference on Power Electronics,Electrical Drives,Advanced Machines and Power Quality(SPEEDAM2000),2000(A4):1-7
[62]Gao Wenzhong,Porandla S K.Design Optimization of a Parallel Hybrid Electric Power train[C]//IEEE Conference on Vehicle Power and Propulsion,2005:530-535.
[63]张翔,赵韩,钱立军,张炳力.电动汽车仿真软件ADVISOR[J].汽车研究与开发,2003,(4)
[64]Wipke K,Markel T,Nelson D.Optimizing energy management strategy and degree of hybridization for a hydrogen fuel cell SUV.Proc.the 18th International Electric Vehicle Symposium,Berlin,Germany,2001