摘要
混合动力汽车因其显著节省燃料、按需动力、降低排放和运行安静平稳、无排放等优点成为目前最受欢迎的汽车类型。混合汽车中应用较多的电机有无刷直流电机(BLDC)和永磁同步电机(PMSM)两大类电机,由于PMSM具有较高的效率和其固有的高功率密度,可以最大限度地减少了BLDC电机的缺点,被认为具有巨大的潜力。然而,PMSM也存在非线性的驱动特性的缺点,采用传统的比例-积分-微分控制器(PID)难以进行高效的控制。基于此,本文提出了一种用于混合动力车用永磁同步电机的在线神经网络控制器,用于对负载扰动期间速度控制策略进行优化。采用Matlab进行了对比仿真,验证了该方法的有效性及优越性。仿真结果表明,采用在线神经网络控制器可以减少超调量和上升时间,较传统PID控制响应速度快,使得整车性能得到了提高。
Hybrid electric vehicles have become the most popular type of vehicles because of their significant fuel saving,on-demand power,emission reduction,quiet and smooth operation,and no emissions.The most popular motor in hybrid vehicles has a brush DC motor(BLDC)and permanent magnet synchronous motor(PMSM)two categories of motors,PMSM has high efficiency and its inherent high power density,can minimize the shortcomings of BLDC motor,is considered to have great potential.However,PMSM also has the disadvantage of non-linear driving characteristics,and it is difficult to control efficiently with the traditional proportional-integral-differential controller(PID).Based on this,this paper proposed an online neural network controller for permanent magnet synchronous motor for hybrid vehicles to optimize the speed control strategy during load disturbance.A comparative simulation using Matlab to verify the effectiveness and superiority of this method.The simulation results show that the online neural network controller can reduce the overshoot and rise time,which is faster than the traditional PID control,and improves the vehicle performance.
作者
单莹
唐百胜
SHAN Ying;TANG Baisheng(The Sixth Military Representative Office of the Naval Equipment Department in Beijing,Beijing 100037,China)
出处
《微电机》
2023年第7期29-33,共5页
Micromotors
