To reduce common-mode voltage (CMV), various reduced CMV pulse width modulation (RCMV-PWM) algorithms have been proposed, including active zero state PWM (AZSPWM) algorithms, remote state PWM (RSPWM) algorithms, and near state PWM (NSPWM) algorithms. Among these algorithms, AZSPWM algorithms can reduce CMV, but they increase the number of switchings compared to the conventional space vector PWM (CSVPWM). This paper presents a new AZSPWM algorithm for reductions in both the CMV and total number of switchings in BLAC motor drives. Since the proposed AZSPWM algorithm uses only active voltage vectors for motor control, it reduces CMV by 1/3 compared to CSVPWM. The proposed AZSPWM algorithm also reduces the total number of switchings compared to existing AZSPWM algorithms by eliminating the switchings required from one sector to the next. The performance of the proposed algorithm is verified by analyses, simulations, and experimental results.
A minimum root mean square (RMS) torque ripple-remote-state pulse-width modulation (MTR-RSPWM) technique is proposed for minimizing the RMS torque ripple under reduced common-mode voltage (CMV) condition of three-phase voltage source inverters (VSI)-fed brushless alternating current (BLAC) motor drives. The q-axis current ripple due to an error voltage vector generated between the reference voltage vector and applied voltage vector is analyzed for all pulse patterns with reduced CMV of the RSPWM. From the analysis result, in the MTR-RSPWM, a sector is divided into five zones, and within each zone, pulse patterns with the lowest RMS torque ripple and reduced CMV are employed. To verify the validity of the MTR-RSPWM, theorical analysis, simulation, and experiments are performed, where the MTR-RSPWM is thoroughly compared with RSPWM3 that generates the minimum RMS current ripple. From the analytical, simulation, and experimental results, it is shown that the MTR-RSPWM significantly reduces the RMS torque ripple under a reduced CMV condition at the expense of an increase in the RMS current ripple, compared to the RSPWM3.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.