TY - GEN

T1 - Reduced Observer for Anisotropy-Based Position Estimation of PM Synchronous Machines Using Current Oversampling

AU - Weber, Bastian

AU - Lindemann, Georg

AU - Mertens, Axel

N1 - Funding information: IV. CONCLUSIONS A novel approach on anisotropy-based position estimation for PM synchronous machines using a reduced observer and FPGA-operated current oversampling is presented. During time spans of the inverter’s zero voltage vectors, a least mean squares regression is performed by FPGA. Using this information, current slopes during active voltage vectors are computed and evaluated for sensorless control. The position estimation approach is based on a reduced observer. This decreases the extent of parameter dependency and leads to a high dynamic for position estimation. The oversampling also creates a high signal-to-noise ratio considering current measurement noise, and high dynamic dead-time compensation [1] is used. All units, e.g. speed controller, field-oriented control, observer are implemented on the FPGA part of a Zynq 7000 system on-chip device. The experimental results substantiate a high dynamic of the closed loop sensorless control. V. ACKNOWLEDGMENT This work was supported by the German Research Foundation (DFG).

PY - 2017

Y1 - 2017

N2 - Using field-programmable gate array (FPGA) and current oversampling, a novel approach for anisotropy-based position estimation of PM synchronous machines is presented. A least mean squares regression of the current samples is performed by an FPGA during the inverter's passive switching states to compute current slopes at active voltage vectors and evaluate them for position estimation. Using the predictive dead-Time compensation as in [1], the inverter's nonlinearity effects are compensated with a high dynamic. The oversampling also creates a high signal-To-noise ratio in view of current measurement noise. Compared to [2], the novel approach of sensorless control is designed as a reduced observer in the estimated reference frame. This leads to high dynamics and a reduced parameter dependency. Experimental results show the high performance of the novel approach in closed loop sensorless control.

AB - Using field-programmable gate array (FPGA) and current oversampling, a novel approach for anisotropy-based position estimation of PM synchronous machines is presented. A least mean squares regression of the current samples is performed by an FPGA during the inverter's passive switching states to compute current slopes at active voltage vectors and evaluate them for position estimation. Using the predictive dead-Time compensation as in [1], the inverter's nonlinearity effects are compensated with a high dynamic. The oversampling also creates a high signal-To-noise ratio in view of current measurement noise. Compared to [2], the novel approach of sensorless control is designed as a reduced observer in the estimated reference frame. This leads to high dynamics and a reduced parameter dependency. Experimental results show the high performance of the novel approach in closed loop sensorless control.

KW - Current oversampling

KW - FPGA-based control

KW - Sensorless control

UR - http://www.scopus.com/inward/record.url?scp=85039915317&partnerID=8YFLogxK

U2 - 10.1109/SLED.2017.8078441

DO - 10.1109/SLED.2017.8078441

M3 - Conference contribution

AN - SCOPUS:85039915317

T3 - Symposium on Sensorless Control for Electrical Drives

SP - 121

EP - 126

BT - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th International Symposium on Sensorless Control for Electrical Drives, SLED 2017

Y2 - 18 September 2017 through 19 September 2017

ER -