第36卷第10期 北京科技大学学报 Vol.36 No.10 2014年10月 Journal of University of Science and Technology Beijing 0ct.2014 纯电动汽车车载电源性能在环测试平台研究 李 勇”，Mehrdad Kazerani2,马飞) 1)北京科技大学机械工程学院，北京1000832)滑铁卢大学电气与计算机系，滑铁卢N2L3G1 ☒通信作者，E-mail:yeke@ustb.edu.cm 摘要为研究纯电动汽车车载电源性能，提出并搭建了由异步电动机和直流电动机组成的在环测试平台.异步电动机用来 模拟纯电动汽车的牵引电动机，直流电动机用来模拟汽车行驶时的阻力和惯量，对异步电动机和直流电动机分别实施转速控 制和转矩控制.分析了电动汽车行驶工况，给出了简单循环工况下参考转速、转距和功率.设计了异步电动机调速系统转速 控制器和电流控制器，建立了异步电动机调速系统的数学模型，提出了基于自适应模糊神经网络控制的异步电动机调速系 统。仿真和实验结果表明，基于自适应模糊神经网络控制的调速系统明显优于PD控制的交流调速系统，在环测试平台能够 较好跟踪参考转速和参考转距的变化. 关键词电动汽车：复合电源：在环测试：自适应：模糊控制：神经网络 分类号U469.72 Hardware-in-the-oop test bench research of hybrid energy storage systems in electric vehicles LI Yong,Mehrdad KAZERANP,MA Fei 1)School of Mechanical Engineering,University of Science and Technology Beijing.Beijing 100083,China 2)Department of Electrical and Computer Engineering,University of Waterloo,Waterloo N2L 3G1,Canada Corresponding author,E-mail:yeke@ustb.edu.cn ABSTRACT Hybrid energy storage systems (HESS)play an important role in electric vehicles.This paper mainly focuses on a hardware-in-the-oop (HIL)test bench for testing the performance of HESS.The scenario of an induction motor and a DC motor was proposed.The induction motor was used as a traction motor while the DC motor worked as the load and moment of inertia of the vehi- cle.Speed control was implemented on the induction motor while torque control was applied to the DC motor.The speed,torque and power of the traction motor were obtained from a simple drive cycle based on real parameters.The motor speed was given as a reference of the induction motor while the load torque was used as a reference of the DC motor.The speed control system of the induction motor and the torque control of the DC motor were analyzed and designed.Meanwhile,the speed control system of the induction motor was modeled.Adaptive fuzzy neural-network control was proposed to achieve high accuracy due to the low accuracy of PID control.Simula- tion and experimental results agreed with the proposal.The test bench follows the reference speed and reference torque well. KEY WORDS electric vehicles;hybrid energy storage systems;hardware-in-theoop tests;adaptive:fuzzy control:neural networks 随着电动汽车技术的发展，车载电源的性能逐 电源作为电动汽车能量存储装置，一方面为电动汽 渐成为决定整车性能的关键因素.电池作为电动汽 车提供驱动能量，同时为车辆辅助系统提供电能，其 车的动力源泉，始终制约着电动汽车的发展，电动汽 应具备优良的充放电特性、稳定的使用性能以及较 车的未来关键在于能否研发出高能量密度、高功率 长的使用寿命.锂离子电池和超级电容均可作为电 密度和使用寿命长的高效电池·-刀.电动汽车车载 源使用，但任何一种单一的能量源都不能满足电动 收稿日期：2013-12-24 基金项目：国家高技术研究发展计划资助项目(2011AA060403):北京市科技计划资助项目(Z121100003012016) DOI:10.13374/j.issn1001-053x.2014.10.014:http://journals.ustb.edu.cn第 36 卷 第 10 期 2014 年 10 月 北京科技大学学报 Journal of University of Science and Technology Beijing Vol． 36 No． 10 Oct． 2014 纯电动汽车车载电源性能在环测试平台研究 李 勇1) ，Mehrdad Kazerani2) ，马 飞1)  1) 北京科技大学机械工程学院，北京 100083 2) 滑铁卢大学电气与计算机系，滑铁卢 N2L 3G1  通信作者，E-mail: yeke@ ustb． edu． cn 摘 要 为研究纯电动汽车车载电源性能，提出并搭建了由异步电动机和直流电动机组成的在环测试平台． 异步电动机用来 模拟纯电动汽车的牵引电动机，直流电动机用来模拟汽车行驶时的阻力和惯量，对异步电动机和直流电动机分别实施转速控 制和转矩控制． 分析了电动汽车行驶工况，给出了简单循环工况下参考转速、转距和功率． 设计了异步电动机调速系统转速 控制器和电流控制器，建立了异步电动机调速系统的数学模型，提出了基于自适应模糊神经网络控制的异步电动机调速系 统． 仿真和实验结果表明，基于自适应模糊神经网络控制的调速系统明显优于 PID 控制的交流调速系统，在环测试平台能够 较好跟踪参考转速和参考转距的变化． 关键词 电动汽车; 复合电源; 在环测试; 自适应; 模糊控制; 神经网络 分类号 U 469. 72 Hardware-in-the-loop test bench research of hybrid energy storage systems in electric vehicles LI Yong1) ，Mehrdad KAZEＲANI2) ，MA Fei1)  1) School of Mechanical Engineering，University of Science and Technology Beijing，Beijing 100083，China 2) Department of Electrical and Computer Engineering，University of Waterloo，Waterloo N2L 3G1，Canada  Corresponding author，E-mail: yeke@ ustb． edu． cn ABSTＲACT Hybrid energy storage systems ( HESS) play an important role in electric vehicles． This paper mainly focuses on a hardware-in-the-loop ( HIL) test bench for testing the performance of HESS． The scenario of an induction motor and a DC motor was proposed． The induction motor was used as a traction motor while the DC motor worked as the load and moment of inertia of the vehi￾cle． Speed control was implemented on the induction motor while torque control was applied to the DC motor． The speed，torque and power of the traction motor were obtained from a simple drive cycle based on real parameters． The motor speed was given as a reference of the induction motor while the load torque was used as a reference of the DC motor． The speed control system of the induction motor and the torque control of the DC motor were analyzed and designed． Meanwhile，the speed control system of the induction motor was modeled． Adaptive fuzzy neural-network control was proposed to achieve high accuracy due to the low accuracy of PID control． Simula￾tion and experimental results agreed with the proposal． The test bench follows the reference speed and reference torque well． KEY WOＲDS electric vehicles; hybrid energy storage systems; hardware-in-the-loop tests; adaptive; fuzzy control; neural networks 收稿日期: 2013--12--24 基金项目: 国家高技术研究发展计划资助项目( 2011AA060403) ; 北京市科技计划资助项目( Z121100003012016) DOI: 10． 13374 /j． issn1001--053x． 2014． 10． 014; http: / /journals． ustb． edu． cn 随着电动汽车技术的发展，车载电源的性能逐 渐成为决定整车性能的关键因素． 电池作为电动汽 车的动力源泉，始终制约着电动汽车的发展，电动汽 车的未来关键在于能否研发出高能量密度、高功率 密度和使用寿命长的高效电池［1 － 2］． 电动汽车车载 电源作为电动汽车能量存储装置，一方面为电动汽 车提供驱动能量，同时为车辆辅助系统提供电能，其 应具备优良的充放电特性、稳定的使用性能以及较 长的使用寿命． 锂离子电池和超级电容均可作为电 源使用，但任何一种单一的能量源都不能满足电动