Traditional quasi-type-I phase-locked loops (QT1-PLLs) in sensorless control systems for permanent magnet synchronous motors (PMSMs) suffer from decreased rotor position estimation accuracy as operating conditions change. They also struggle to balance dynamic response speed and steady-state accuracy. To address these challenges, we propose a parameter-adaptive phase-locked loop (PLL) method based on an improved QT1-PLL structure. Building on the conventional QT1-PLL topology, we introduce a frequency-adaptive hybrid filtering mechanism by cascading an adaptive notch filter with a moving average filter. This combination effectively suppresses estimation errors and noise disturbances caused by frequency fluctuations while maintaining high filtering efficiency under complex operating conditions. By coupling this hybrid filter with the QT1-PLL, we create the adaptive hybrid-filtering QT1-PLL (AHF-QT1-PLL), which coordinates back-EMF filtering and harmonic suppression. This significantly enhances the system′s robustness and stability, especially under low-speed operation, wide speed variations, and load disturbances. Compared to the traditional QT1-PLL, the proposed method significantly improves dynamic tracking performance during fast speed changes and ensures high rotor position estimation accuracy during steady-state operation, effectively balancing dynamic and steady-state performance. Simulation and experimental results show that the AHF-QT1-PLL outperforms the traditional QT1-PLL across a range of operating conditions, demonstrating higher rotor position estimation accuracy, reduced steady-state errors, faster dynamic adjustment, and stronger disturbance rejection and harmonic suppression capabilities. These results confirm the effectiveness and reliability of the AHF-QT1-PLL under both dynamic and steady-state conditions, offering strong engineering application potential and practical value for optimizing sensorless control strategies in PMSM.