Yunfei Zhang

This paper presents a flux-weakening model predictive control (FW-MPC) for the interior permanent magnet synchronous motor (IPMSM) drive system. The FW control is a strategy to extend the IPMSM’s operating region. However, the primary FW needs to track the torque reference and maximize the electrical torque per current amplitude with the current and voltage limitations. The two objects make it impossible to solve the FW problem using the optimization method. We proposed an equivalent optimization problem to simplify the complex FW problem, including two objective functions. The MPC is selected as the controller due to its high robustness and transient performance. The constraints from the equivalent optimization problem are added in the MPC to control the IPMSM in the FW region. The simulation and experiment results indicate that the proposed FW-MPC is feasible and effective in driving the IPMSM in the FW region. The proposed FW-MPC can find the optimal point with the maximum electrical torque satisfying the current and voltage limitations. Therefore, the proposed FW-MPC can extend the IPMSM’s operating region, benefiting the IPMSM’s application.

This paper proposes a high-efficiency flux weakening drive based on the model predictive control (HEFW-MPC) for the interior permanent magnet synchronous motor (IPMSM). It is of great significance to improve the IPMSM’s efficiency due to its wide application and the urgent need for emission reduction. The flux weakening drive can extend the speed range of IPMSM and reduce the gear ratio. The lower gear ratio is helpful to improve the mechanical transfer efficiency. However, the IPMSM’s loss has often been ignored. Therefore, the high-efficiency algorithm (HEA), concerning the copper and iron loss of IPMSM, is introduced to improve efficiency. Besides, the model predictive control (MPC) is utilized as the controller to handle complex nonlinearities and constraints. But it is difficult to directly solve the FW problem with multiple constraints, e.g., voltage limitation, current limitation, HEA, etc. Hence, the equivalent optimization is proposed to simplify the primal problem. The simulations and experiments verify that the presented HEFW-MPC is effective in driving IPMSM. What’s more, the efficiency maps demonstrate that HEFW-MPC is helpful to improve the efficiency and extend the high-efficiency region of IPMSM.