Improved loss minimisation control for interior permanent magnet synchronous motor based on loss angle optimisation

Due to their high power density and superior drive performance, permanent magnet synchronous motors (PMSM) are extensively utilised in the mobile machine traction systems. Traditional id = 0 control produces relatively low torque per unit of current and is suitable for non-flux-weakening control. Traditional maximum torque per ampere (MTPA) control can enhance the torque output capability per unit of current, and is mainly used for interior PMSMs (IPMSMs) with salient poles. However, neither id = 0 control nor MTPA control fully considers the impact of copper losses, iron losses, and variations in motor parameters, resulting in suboptimal control efficiency of the PMSM. In this paper, to further enhance the energy efficiency of IPMSMs, models for iron loss and copper loss in IPMSMs are constructed and analysed. Compared to existing minimum loss optimisation algorithms, a minimum loss angle vector control method based on the loss models is proposed. The particle swarm optimisation algorithm is employed to achieve globally optimal d-q axis current distribution. In addition, considering the influence of parameter variations during the operation of IPMSMs on the efficiency improvement control, online parameter identification of the motor is investigated. Consider the impact of parameter variations on motor performance when using traditional proportional integral (PI) control, a neural network is employed for online tuning of the speed loop of IPMSMs. Experimental research is conducted to verify the effectiveness of the proposed control algorithm. The experimental results demonstrate that the proposed online tuning control algorithm exhibits superior control performance compared to the traditional PI control. Specifically, during the startup phase, the overshoot is reduced by 61.54%, and the adjust time is decreased by 33%. When load variations cause changes in rotational speed, the overshoot is red uced by 33%–60%, and the adjust time is shortened by 34%–50%. Furthermore, the minimum loss angle control can improve energy efficiency by more than 20% compared to id = 0 control, and by 6%–10% compared to MTPA control.