Injection-Free Rotor Position Estimation Error Compensation for Simplified Salient High-Speed Permanent Magnet Synchronous Machine Sensorless Drive

High power density is the distinguished advantage of high-speed permanent magnet synchronous machines (HSPMSMs), which will even be improved by the saliency introduced due to the artificially asymmetric magnetic circuit, namely, different d- and q-axis inductances (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{d}$ </tex-math></inline-formula>/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{q}$ </tex-math></inline-formula>). Furthermore, for the salient PMSM sensorless drive, the low switching-to-fundamental frequency ratio (SFFR) makes the accurate rotor position estimation more complicated. Present algorithms require extensive nonlinear matrix computations, which are not convenient for large-scale applications. Although silicon carbide (SiC) devices are employed to address the low SFFR issue, the improved cost usually limits its applications. As a compromise, a salient PMSM can be assumed as a nonsalient one, and consequently, the phase winding inductance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{s}$ </tex-math></inline-formula> is approximately calculated by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{s}=(L_{d}+L_{q})$ </tex-math></inline-formula>/2. Such assumptions will inevitably cause rotor position estimation errors, and hence, in this article, a current ripple sampling (CRS)-based method is proposed to identify the error. It should be noted that such a method is injection-free, dead-time effect (DTE)-immune, and detection-free. Furthermore, the identified position errors can be smoothly compensated by noise suppression filters [e.g., recursive autoregressive least-squares method (LSM)] and closed-loop regulations (e.g., PI controllers). Finally, experimental validations are conducted on a prototype with 45 kr/min used for hydrogen pumps.