Current Injection-Based Multi-parameter Estimation for Dual Three-Phase IPMSM Considering VSI Nonlinearity

To develop a high-performance and reliable control for dual three-phase interior permanent magnet synchronous motor (IPMSM), accurate knowledge of machine parameters is of significance. This paper proposes an improved recursive least square (RLS) algorithm and a current injection-based parameter estimation method for dual three-phase PMSM with consideration of inverter nonlinearity and magnetic saturation. First, the vector space decomposition (VSD)-based dual three-phase PMSM model is established. The inverter nonlinearity model for dual three-phase PMSM is derived, and the cross saturation and the self-saturation of DQ1-axis inductances are modeled to improve the estimation accuracy. Finally, the machine parameters, including winding resistance, rotor flux linkage, and varying DQ1-axis inductances under different operating conditions, are estimated using the proposed current injection-based method with the RLS algorithm. Compared with existing methods, the proposed approach can achieve better estimation performance and is validated on a laboratory dual three-phase IPMSM under different temperature and operating conditions.