<p> Rotor position information obtained through a position sensor is crucial for proper field-oriented control (FOC) of permanent magnet synchronous machine based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding positions sensors to fail, introducing error to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness. </p>

<p> Rotor position information obtained through a position sensor is crucial for proper field-oriented control (FOC) of permanent magnet synchronous machine based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding positions sensors to fail, introducing error to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness. </p>

<p> Rotor position information obtained through a position sensor is crucial for proper field-oriented control (FOC) of permanent magnet synchronous machine based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding positions sensors to fail, introducing error to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness. </p>

Rotor position information obtained through a position sensor is crucial for proper fieldoriented control (FOC) of permanent magnet synchronous machine-based high dynamic energy conversion applications. In applications such as transportation and industrial, PMSM energy conversion systems are subjected to harsh environmental conditions such as vibration, shock, and thermal shock causing mechanical interfaces holding position sensors to fail, introducing errors to the position measurement. A dynamic position sensor offset error (DPSOE), being such a failure mode has the potential to degrade system torque output or more adversely, reverse machine torque output that may cause catastrophic outcomes. This paper evaluates different DPSOE scenarios, presents an approach to model the failure mode for analysis and proposes two novel, and robust DPSOE detection methods for PMSM drive systems. The proposed detection methods are analytically proven and supported by simulation and experimental results under multiple operating conditions proving robustness.