Research On Current Distribution And Control Strategy Of Hybrid Excitation Synchronous Motor Speed Control System

The hybrid excitation synchronous motor(HESM),which is a new type of motor,provides the advantages of high load carrying capacity,wide speed range and high power density,and has good prospects for application as a drive motor for new energy vehicles.It is important to study the control strategy to improve the motor performance.In this paper,we take HESM as the research object to improve the load carrying capacity in low speed region and widen the speed range in high speed region,and study the current distribution,speed loop control and current loop decoupling control aspects in the speed control system as follows:(1)In response to the problem that the conventional current distribution control strategy only considers the q-axis counter-electromotive force in the high-speed region of the weak magnetic control,the paper designs an improved current control strategy that considers the d-axis counter-electromotive force based on the principle of constant counter-electromotive force.The simulation verifies that the designed current distribution control strategy increases the electromagnetic torque output in the high speed region of the motor and effectively improves the load carrying capacity.(2)In response to the problems of nonlinearity and tedious calculation of the proposed improved current distribution control strategy,the current distribution equation is firstly approximated nonlinearly by using BP neural network to simplify the current control model.Secondly,the initial weights and thresholds of the neural network are optimized using the mind evolution algorithm to reduce the approximation error of the network.Finally,in order to improve the robustness of the network,the network is trained several times using noisy and non-noisy sample data to address the problem that the output of the current divider is jittered when the inductor parameters are mismatched,which affects the output current of the motor.It is verified that the BP neural network current distribution controller significantly reduces the jitter of each current component and electromagnetic torque of the motor when the inductor parameters are mismatched.(3)In response to the problems of poor speed dynamic response,static error and oscillation of electromagnetic torque and current during sudden torque change,the speed loop controller is designed based on speed partitioning,with a sliding mode control strategy in the low speed region and a self-turbulence control strategy in the high speed region.The simulation shows that the designed speed-loop control strategy reduces the speed overshoot,regulation time and static error,suppresses the oscillation of electromagnetic torque and current components during sudden load changes,and enhances the dynamic and static performance of the system.(4)A multi-vector model predictive current control strategy based on fast vector selection is proposed to address the problem of poor motor output performance due to inter-variable coupling in current loop control.The simulation verifies that the method effectively reduces the current and torque pulsations and improves the current following capability.