串联式混合动力电动汽车仿真及动力总成控制策略研究
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摘要
本文针对串联式混合动力电动汽车开发了一套前向仿真模型,针对串联式混合动力电动汽车的部件模型和动力总成控制策略进行了研究,并应用课题组现有的混合动力电动汽车车辆台架进行了软硬件优化和试验研究。本文首先对混合动力电动汽车的仿真现状和控制算法现状进行了介绍,并采用了前向仿真作为本文的主线,分别设计了驾驶员模型、前向发动机模型、前向电机(驱动电机和发电机)模型、前向电池模型、前向车辆模型等。在控制策略方面,针对串联式混合动力电动汽车的经典控制策略恒温式和功率跟随式控制策略进行了设计和分析,得出恒温式控制策略有利于发动机的排放和油耗却不利于电池的寿命和成本的降低,功率跟随式控制策略有利于电池的寿命和体积的减小,却不利于发动机的油耗和排放的结论。经过进一步的研究,在率跟随控制基础上设计了模糊控制,取得了较好的效果,经过试验验证,上述结论成立。
Electric vehicle, especially hybrid electric vehicle, has been known as one of the best future vehicles. In the 1990s, USA had developed the PNGV (Partnership of New Generation Vehicle) plan, which was focusing on HEV, as far as we now, the team has been working well.
Chinese government has invested electric vehicle program since“the 9th five plans”. The electric vehicle program was developed as one of the key“863 program”during“the 10th five plans”. Now it turns to“the 11th five program”, the government pays more attention on this field. The key technology of“863 program”is about new concept total electric vehicle (FCV/HEV/EV).The key technology of HEV of Chinese electric vehicle industry is control system algorithm parametric match, and etc.
In this thesis, the key technology of control system for Powertrain has studied and completed it based on both simulation and experimentation. The content are as follows:
1. First of all, after comparing with many series components, the important components of SHEV were selected, for example: 4G18 IC engine (Made by Dong An company); ISG permanent magnet synchronous motor (Made by Institute of Electrical Engineering, Chinese Academy of Sciences); Ni-MH battery (Made by Chunlan company, Jiangsu); BJ2023 vehicle.
2. The difference between the forward model and the backward model was analyzed. Finally, the forward was selected, and then the driver model was designed with PID algorithm. The driver model is used for simulating the change of the vehicle pedal, which was brought it into control model.
3. The parameters of important parts were selected, and it was transferred into model based on Matlab/Simulink software. For example, IC engine’s Engine speed characteristics model, Ni-MH battery capacity’s Resistance model, the motor’s Output characteristics and efficiency characteristics model.
4. In order to meet the vehicle need, hardware and software was designed for the ECU. The principle of the sensors and executants were introduced in this thesis. Some circles were designed about these parts, for example, digital signals input circles, analog signals input circles, communicate circles, clock circles and restoration circles etc. The main program combining with interrupt program was used in the control strategy. And every function was designed by using blocking program in order to be modified easily.
5. Three kinds of control strategy of SHEV were designed to make the vehicle work well. The balance control strategy has a simple principle, however, it does badly to battery’s life, vehicle’s cost and total fuel consume. The power flow control strategy has a better fuel consume and lower vehicle cost, but a bad emission. Fuzzy control algorithm joints the advantages of the two foregoing algorithms.
6. Several driver cycles were analyzed, and SFTPUS06 and SFTPUS06HWYwere selected to test for the SUV’s SHEV test. The driver cycles were designed based on Simulink.
7. The program that displays the experimental data was designed based on Lab VIEW software. The hybrid electric vehicle was tested by the professional instrument. After compare the result and the simulation’s result, the error is undertaken. Some conclusions can be made as follows through the experimental study on the SHEV:
1. The PID algorithm of driver model in the foreward simulation of hybrid electric vehicle can meet the SHEV accurately. It transfers the speed’s error between the two pedometers into the vehicle’s torque what was the drive torque for the simulation, and then provided itself used by the controller to determine the next step.
2. In order to meet the driver cycle for SUV, the fuzzy control strategy can be better than power flow strategy and balance strategy. Based on the battery SOC, the required driving torque as fuzzy inputs, the actual output torque of IC Engine is determined by FLC principle. And the overall optimization on fuel consumption of complete vehicle is finally realized. The comparison of simulation model for the control strategy established by software shows that the FLC is more effective for improving fuel economy of complete vehicle and reducing cycle times of batteries.
3. Study on some other driver cycles, for example, Beijing bus cycle, was established with fuzzy control strategy established. The results show that the batteries’SOC change strongly and the IC engine work well. So it was got that different cycle needs different control strategy.
Electric vehicle, especially hybrid electric vehicle, has been known as one of the best future vehicles. In the 1990s, USA had developed the PNGV (Partnership of New Generation Vehicle) plan, which was focusing on HEV, as far as we now, the team has been working well.
Chinese government has invested electric vehicle program since“the 9th five plans”. The electric vehicle program was developed as one of the key“863 program”during“the 10th five plans”. Now it turns to“the 11th five program”, the government pays more attention on this field. The key technology of“863 program”is about new concept total electric vehicle (FCV/HEV/EV).The key technology of HEV of Chinese electric vehicle industry is control system algorithm parametric match, and etc.
In this thesis, the key technology of control system for Powertrain has studied and completed it based on both simulation and experimentation. The content are as follows:
1. First of all, after comparing with many series components, the important components of SHEV were selected, for example: 4G18 IC engine (Made by Dong An company); ISG permanent magnet synchronous motor (Made by Institute of Electrical Engineering, Chinese Academy of Sciences); Ni-MH battery (Made by Chunlan company, Jiangsu); BJ2023 vehicle.
2. The difference between the forward model and the backward model was analyzed. Finally, the forward was selected, and then the driver model was designed with PID algorithm. The driver model is used for simulating the change of the vehicle pedal, which was brought it into control model.
3. The parameters of important parts were selected, and it was transferred into model based on Matlab/Simulink software. For example, IC engine’s Engine speed characteristics model, Ni-MH battery capacity’s Resistance model, the motor’s Output characteristics and efficiency characteristics model.
4. In order to meet the vehicle need, hardware and software was designed for the ECU. The principle of the sensors and executants were introduced in this thesis. Some circles were designed about these parts, for example, digital signals input circles, analog signals input circles, communicate circles, clock circles and restoration circles etc. The main program combining with interrupt program was used in the control strategy. And every function was designed by using blocking program in order to be modified easily.
5. Three kinds of control strategy of SHEV were designed to make the vehicle work well. The balance control strategy has a simple principle, however, it does badly to battery’s life, vehicle’s cost and total fuel consume. The power flow control strategy has a better fuel consume and lower vehicle cost, but a bad emission. Fuzzy control algorithm joints the advantages of the two foregoing algorithms.
6. Several driver cycles were analyzed, and SFTPUS06 and SFTPUS06HWYwere selected to test for the SUV’s SHEV test. The driver cycles were designed based on Simulink.
7. The program that displays the experimental data was designed based on Lab VIEW software. The hybrid electric vehicle was tested by the professional instrument. After compare the result and the simulation’s result, the error is undertaken. Some conclusions can be made as follows through the experimental study on the SHEV:
1. The PID algorithm of driver model in the foreward simulation of hybrid electric vehicle can meet the SHEV accurately. It transfers the speed’s error between the two pedometers into the vehicle’s torque what was the drive torque for the simulation, and then provided itself used by the controller to determine the next step.
2. In order to meet the driver cycle for SUV, the fuzzy control strategy can be better than power flow strategy and balance strategy. Based on the battery SOC, the required driving torque as fuzzy inputs, the actual output torque of IC Engine is determined by FLC principle. And the overall optimization on fuel consumption of complete vehicle is finally realized. The comparison of simulation model for the control strategy established by software shows that the FLC is more effective for improving fuel economy of complete vehicle and reducing cycle times of batteries.
3. Study on some other driver cycles, for example, Beijing bus cycle, was established with fuzzy control strategy established. The results show that the batteries’SOC change strongly and the IC engine work well. So it was got that different cycle needs different control strategy.
引文
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[30] Tae-Uk Jung etc. The Development of Hybrid Electric Compressor Motor Drive System for 1EV. IEEE, 2007
[31] Yiran Hu etc. Model-Based Calibration for Battery Characterization in HEV Applications[C]. IEEE 2008
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[35] Bosch公司,吴森等译.汽油机管理系统[M].北京:北京理工大学出版社,2002,9
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[2]陈清泉,孙逢春.混合动力车辆基础[M].北京:北京理工大学出版社,2001
[3]王庆年.混合动力汽车技术的创新性研究[R].奖励与进步,2008: 14-15
[4]于秀敏,曹珊,李君,高莹,杨世春,钟祥麟,孙平.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)
[5]杨世春.混合动力汽车发动机功率管理系统开发[D].长春:吉林大学学,2008
[6] Fazal Syed and John Czubay. Improving the Efficiency of Production Level Algorithm Development for an SUV HEV Powertrain[C].SAE paper 2004-01-3039
[7] NEWS U.S. Military Goes For Hybrid Vehicles-Experimental Marine Corps armored vehicle has diesel-electric driver train [J]. IEEE Spectrum March, 2004
[8]国家高技术研究发展计划(863计划)现代交通技术领域“节能与新能源汽车”重大项目2008年度第一批课题申请指南.2008
[9] Floyd A. Wyczalek. HYBRID ELECTRIC VEHICLES (EVS-13 OSAKA). IEEE, 1992
[10] Fazal U. Syed etc. Derivation and Experimental Validation of a Power-Split Hybrid Electric Vehicle Model. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. 2006, 55 (6): 1731-1747
[11] Joint Advisor/PSAT Vehicle Systems Modeling User Conference. August 28-29 ,2001
[12]李晓英,于秀敏,李君,吴志新.串联混合动力汽车控制策略[J].吉林大学学报(工学版), 2005
[13] Xin Li etc. Comparative Investigation of Series and Parallel Hybrid Electric Vehicle (HEV) Efficiencies Based on Comprehensive Parametric Analysis. IEEE, 2007
[14] Cui Shumei etc. Control Strategy for Double Shaft Parallel Hybrid Electric Vehicle. IEEE, 2008
[15] Floyd A. Wyczalek etc. HYBRID ELECTRIC VEHICLES IN EUROPE AND JAPAN. IEEE, 1998: 96480-96485
[16]马路,刘慧敏. Matlab7.0/Simulink6.0建模仿真开发与高级工程应用[M].北京:清华大学出版社,2005
[17]曾小华,于永涛,王加雪,王庆年等.基于CRUISE软件的混合动力客车主动同步换档的建模与仿真[J].吉林大学学报(工学版), 2008,38(5):1015-1019
[18]曾小华,王庆年,李胜,王伟华.正向仿真模型与反向软件ADVISOR的集成开发[J].汽车工程, 2007,29(10): 851-854
[19] Ding Huajie, Yu Xiumin, Li Junjie etc. Study on Effects of Driving Style on Vehicle Performance for Econopower Competition,SAE paper,2008-01-1781
[20]郭孔辉.汽车操纵动力学[M].长春:吉林科学技术出版社,1991
[21]于永涛,曾小华,王庆年,李俊,王伟华.混合动力汽车性能仿真软件的可用性仿真验证[J].系统仿真学报,2009,21(2):380-384
[22]曾小华,王庆年,王伟华,初亮.基于ADVISOR软件的双轴驱动混合动力汽车性能仿真模块开发[J].汽车工程,2003,25(5):424-427
[23] 863计划先进能源技术领域2008年度专题课题申请指南. 2008
[24]周龙保.内燃机学(第2版)[M].北京:机械工业出版社,2005
[25]陈家瑞.汽车构造[M].北京:机械工业出版社,2000
[26] Karen L. Butler etc. A Matlab-Based Modeling and Simulation Package for Electric and Hybrid Electric Vehicle Design [J].IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 1999,48(6): 1770-1778
[27] Xiaoling He etc. Modeling and Simulation for Hybrid Electric Vehicles—Part I: Modeling[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2002, 3 (4):235-243
[28] Patricia Caratozzolo etc. Design and Control of the Propulsion System of a Series Hybrid Electric Vehicle[C]. IEEE,2006
[29] Sheldon S. Williamson etc. Comprehensive Drive Train Efficiency Analysis of Hybrid Electric and Fuel Cell Vehicles Based on Motor-Controller Efficiency Modeling. IEEE TRANSACTIONS ON POWER ELECTRONICS[J], 2006,21 (3): 730-741
[30] Tae-Uk Jung etc. The Development of Hybrid Electric Compressor Motor Drive System for 1EV. IEEE, 2007
[31] Yiran Hu etc. Model-Based Calibration for Battery Characterization in HEV Applications[C]. IEEE 2008
[32]毕道治.电动车电池的开发现状及展望[J].电池工业. 2000, 5(2):56-63
[33]曹珊,于秀敏,李君,杨世春,钟祥麟,孙平.混合动力汽车辅助动力单元控制器接口设计[J].计算机测量与控制,2006
[34]杨世春,于秀敏,董伟,钟祥麟,唐睿. LPG发动机怠速控制的研究[J].汽车工程,2006
[35] Bosch公司,吴森等译.汽油机管理系统[M].北京:北京理工大学出版社,2002,9
[36] Hyun-Soo Hwang etc. Development of HILS System for Testing Embedded System of the BCU for HEV. IEEE, 2008
[37]曹珊,于秀敏,周学文,赵强,陈燕春,赵东风.混合动力汽车CAN总线系统智能节点设计[J].计算机工程与应用,2006
[38]曹珊,于秀敏,高莹,孙平.李颖CAN总线在混合动力电动公共汽车中的应用[J].汽车技术, 2005
[39] Wu Qing-yu etc. EMC Design for HEV Drive System. IEEE 2007 International Symposium on Microwave, Antenna, Propagation, and EMC Technologies For Wireless Communications
[40] Mehrdad Ehsani etc. Evaluation of Soft Switching for EV and HEV Motor Drives. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2001, 48(1): 82-91
[41] Jianmin Duan etc. Framework of CANopen Protocol for a Hybrid Electric Vehicle. IEEE, 2007
[42]曾小华,王庆年,李骏,王伟华,初亮.基于ADVISOR2002混合动力汽车控制策略模块开发[J].汽车工程,2004,26(4):394-397
[43]董伟,于秀敏,张友坤.汽车下长坡时发动机制动CVT控制策略[J].吉林大学学报(工学版),2006
[44] H. Moghbeli etc. Sensorless Vector Control of PMSM Drive Using Fuzzy Logic for EV/HEV Applications. SAE paper 2003-01-1207
[45] Yu Xiumin etc. Study of Conversion Characteristics of the three way catalytic converter of the electric controlled engines. Proceedings of Actual problems of internal combustion engines construction and maintenance, Far Eastern Scientific Engineering Conference, Russion, 2002
[46]孟祥萍.智能控制基础理论及应用[M].北京:机械工业出版社,2005
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