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作 者:李勇[1] 马飞[1] Kazerani Mehrdad
机构地区:[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
出 处:《农业机械学报》2014年第7期35-40,共6页Transactions of the Chinese Society for Agricultural Machinery
基 金:国家高技术研究发展计划(863计划)资助项目(2011AA060403);北京市科技计划资助项目(Z121100003012016)
摘 要:为研究纯电动汽车车载电源性能在环测试,提出了由异步电动机-直流电动机组成的测试平台,是集机、电、磁于一体的复杂机电耦合系统。首先对该测试平台进行了机电耦合分析,建立了其机电耦合模型。根据α阶积分逆系统原理构建了伪线性系统,实现了对该复杂机电耦合系统的线性化。在此基础上,将自适应模糊神经网络与逆系统结合,构造出自适应模糊神经网络逆系统对原系统进行解耦控制。仿真和实验结果表明:自适应模糊神经网络逆系统控制取得了较好的解耦效果;异步电动机的反馈转速和直流电动机的反馈转矩均较好地跟踪了参考转速和参考转矩。此外,通过该测试平台可得到在整个循环工况中与异步电动机相连的电池电压、电流以及功率的变化曲线,为复合电源的在环测试提供了理论依据。A test bench composed by induction motor and dc motor is proposed to test the performance of power source on EVs. The test bench is a complex electromechanical coupling system with mechanical, electrical and magnet fields. The electromechanical coupling model of the system was built. The nonlinear system was linearized with the help of a-order integration inverse system. The adaptive fuzzy- neural network control was applied to the system based on the inverse system control. That also leads to a better decoupling simulation and experimental results. Both of the feedback of AC motor speed and DC motor torque follow the targets. The variations of voltage, current and power on the DC bus of the battery connected with induction motor can be observed, which provides the theoretical foundation for the research on the hybrid energy storage system.
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