纯电动汽车经济性换挡规律驱动力波动控制研究
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摘要
针对纯电动汽车以经济性换挡规律运行时,换挡前后存在驱动力波动较大的现象,提出驱动力波动控制策略.根据驱动电机电流与电机输出转矩具有较强的关联度,设计出基于径向基神经网的驱动电机输出转矩估测模型,利用估测转矩计算车辆驱动力,分析出驱动电机消除驱动力波动需要补偿的转矩,得出补偿后的驱动控制策略.通过AMESim软件建立纯电动汽车动力仿真系统,验证估测转矩精确度,并对比驱动力波动控制策略使用前后的车速变化曲线.结果表明,估测转矩误差率小于0.09,在使用驱动力波动控制策略后,换挡前后车速过渡更平滑,整车动力性和驾驶舒适性得到了改善.
Driving force fluctuates as a pure electric vehicle shifts with the shift schedule of fuel economy.For this reason,the tractive effort fluctuation control strategy was proposed.There was a correlation between the driving motor current and the output torque of the motor.A model of motor output torque estimation based on radial basis neural network was designed.According to the torque estimation,the driving force was calculated.Compensation torque required by driving motor to eliminate driving force fluctuation was analyzed.The dynamic simulation system of pure electric vehicle was established by AMESim software to verify the accuracy of torque estimation,and experimental results used control strategy was compared with unused.The experimental results show that the error rate of torque estimation is less than 0.09.The curve of vehicle speed data change is smooth before and after the shift,and the power and driving comfort of the vehicle is improved.
Driving force fluctuates as a pure electric vehicle shifts with the shift schedule of fuel economy.For this reason,the tractive effort fluctuation control strategy was proposed.There was a correlation between the driving motor current and the output torque of the motor.A model of motor output torque estimation based on radial basis neural network was designed.According to the torque estimation,the driving force was calculated.Compensation torque required by driving motor to eliminate driving force fluctuation was analyzed.The dynamic simulation system of pure electric vehicle was established by AMESim software to verify the accuracy of torque estimation,and experimental results used control strategy was compared with unused.The experimental results show that the error rate of torque estimation is less than 0.09.The curve of vehicle speed data change is smooth before and after the shift,and the power and driving comfort of the vehicle is improved.
引文
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[14]陈清洪,秦大同,叶心.AMT汽车动态模糊神经网络三参数换挡策略研究[J].汽车工程,2010,32(6):506-509.Chen Qinghong,Qin Datong,Ye Xin.A study on the three parameter shift schedule of AMT vehicle based on dynamic fuzzy neural network[J].Automotive Engineering,2010,32(6):506-509.(in Chinese)
[15]傅洪,王艳静,冯超,等.一种纯电动汽车的电机-变速器动力系统[J].汽车工程,2016,38(8):996-1000.Fu Hong,Wang Yanjing,Feng Chao,et al.A motor transmission power train for pure electric vehicles[J].Automotive Engineering,2016,38(8):996-1000.(in Chinese)
[16]Kouroussis G,Dehombreux P,Verlinden O.Vehicle and powertrain dynamics analysis with an automatic gearbox[J].Mechanis and Machine Theory,2015,8:109-124.
[2]Liu H,Lei Y,Li Z,et al.Gear-shift strategy for a clutchless automated manual transmission in battery electric vehicles[J].SAE International,2012,5(1):57-62.
[3]孙冰,熊会元,于丽敏,等.两挡AMT换挡模式对电动汽车性能影响的研究[J].机械传动,2015,39(10):43-47.Sun Bing,Xiong Huiyuan,Yu limin,et al.Research of the effect of two-speed AMT shift mode on electric vehicle performance[J].Journal of Mechanical Transmission,2015,39(10):43-47.(in Chinese)
[4]江昊,赵韩,黄康,等.纯电动汽车经济性换挡规律仿真研究[J].汽车工程,2015,39(10):43-47.Jiao Hao,Zhao Han,Huang Kang,et al.A simulation study on the shift schedule of electric vehicle aiming at fuel economy[J].Automotive Engineering,2015,39(10):43-47.(in Chinese)
[5]晏伟清,赵韩.基于支持向量机的纯电动汽车经济性换挡控制[J].合肥工业大学学报,2016,39(4):451-456.Yan Weiqing,Zhao Han.Economic shift strategy of pure electric vehicle based on SVM[J].Journal of Hefei University of Technology,2016,39(4):451-456.(in Chinese)
[6]周云山,杨克锋.两挡纯电动汽车传动系换挡规律及速比优化研究[J].机械传动,2015,39(12):12-16.Zhou Yunshan,Yang Kefeng.Research of the shift schedule and ratio optimization for the transmission system of a two-speed electric vehicle[J].Journal of Mechanical Transmission,2015,39(12):12-16.(in Chinese)
[7]Liu D,Yang G H.Neural network-based event-triggered MFAC for nonlinear discrete-time processes[J].Neurocomputing,2018,272:356-364.
[8]Alexandridis A,Chondrodima E,Giannopoulos N,et al.A fast and efficient method for training categorical radial basis function networks[J].Transactions on Neural Networdks and Learning Systems,2017,28(11):2831-2836.
[9]Jing Y H,Yang G H.Neural-network-based adaptive fault-tolerant tracking control of uncertain nonlinear time-delay systems under output constraints and infinite number of actuator faults[J].Neurocomputing,2018,272:343-355.
[10]Talkhoncheh M K,Shahrokhi M,Askari M R.Observer-based adaptive neural network controller foruncertain nonlinear systems with unknown control directions subject to input time delay and saturation[J].Information Sciences,2017,418:717-737.
[11]Sorniotti A,Holdstock T,Pilone G L,et al.Analysis and simulation of the gearshift methodology for a novel two-speed transmission system for electric powertrains with a central motor[J].Automobile Engineering,2012,226(7):915-929.
[12]Tseng C Y,Yu C H.Advanced shifting control of synchronizer mechanisms for clutchless automatic manual transmission in an electric vehicle[J].Mechanism and Machine Theory,2015,84:37-56.
[13]Hu J J,Ran H L,Pang T.Parameter design and performance analysis of shift actuator for a two-speed automatic mechanical transmission for pure electric vehicles[J].Advances in Mechanical Engineering,2016,8(8):1-15
[14]陈清洪,秦大同,叶心.AMT汽车动态模糊神经网络三参数换挡策略研究[J].汽车工程,2010,32(6):506-509.Chen Qinghong,Qin Datong,Ye Xin.A study on the three parameter shift schedule of AMT vehicle based on dynamic fuzzy neural network[J].Automotive Engineering,2010,32(6):506-509.(in Chinese)
[15]傅洪,王艳静,冯超,等.一种纯电动汽车的电机-变速器动力系统[J].汽车工程,2016,38(8):996-1000.Fu Hong,Wang Yanjing,Feng Chao,et al.A motor transmission power train for pure electric vehicles[J].Automotive Engineering,2016,38(8):996-1000.(in Chinese)
[16]Kouroussis G,Dehombreux P,Verlinden O.Vehicle and powertrain dynamics analysis with an automatic gearbox[J].Mechanis and Machine Theory,2015,8:109-124.
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