Variable Bias Current in Magnetic Bearings for Energy Optimization

2007 ◽  
Vol 43 (3) ◽  
pp. 1052-1060 ◽  
Author(s):  
M. Necip Sahinkaya ◽  
Ahu E. Hartavi
Keyword(s):  
Energy Optimization ◽  
Bias Current ◽  
Magnetic Bearings ◽  
Variable Bias

scholarly journals A Parametric Solution to the Generalized Bias Linearization Problem

Actuators ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 14 ◽  
Author(s):  
David Meeker ◽  
Eric Maslen
Keyword(s):  
Analytical Solution ◽  
Bias Current ◽  
Magnetic Bearings ◽  
Parametric Solution ◽  
Equal Area ◽  
Analytical Computation ◽  
Linearization Problem

Previously, a generalized bias current linearization was presented for the control of radial magnetic bearings. However, a numerically intensive procedure was required to obtain bias linearization currents. The present work develops an analytical solution to the generalized bias linearization problem in which solutions are indexed by a small number of parameters. The formulation also permits the analytical computation of bias linearization currents for faulted-coil cases. A limitation of the solution presented is that it only applies to stators with an even number of evenly spaces poles of equal area.

scholarly journals Low power 9-bit 500 kS/s 2-stage cyclic ADC using OTA variable bias current

2020 ◽  
Vol 105 (1) ◽  
pp. 45-55
Author(s):  
José Ángel Díaz-Madrid ◽  
Ginés Doménech-Asensi ◽  
Ramón Ruiz-Merino ◽  
Juan Zapata ◽  
José Javier Martínez
Keyword(s):  
Low Power ◽  
Bias Current ◽  
Variable Bias ◽  
Cyclic Adc

scholarly journals An Appraisal of Power-Minimizing Control Algorithms for Active Magnetic Bearings

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Seong-yeol Yoo ◽  
Myounggyu D. Noh
Keyword(s):  
Power Consumption ◽  
Magnetic Bearing ◽  
Magnetic Bearings ◽  
Active Magnetic Bearing ◽  
Control Algorithms ◽  
Active Magnetic Bearings ◽  
Consistent Model ◽  
Complex Power ◽  
Derivative Type ◽  
Variable Bias

Active magnetic bearings consume much less power than conventional passive bearings, especially when power-minimizing controllers are employed. Several power-minimizing controllers have been proposed, such as variable bias controllers and switching controllers. In this paper, we present an appraisal of the power-minimizing control algorithms for active magnetic bearings in an attempt to provide an objective guideline on the merits of the control algorithms. In order for the appraisal, we develop an unified and consistent model of active magnetic bearing systems. The performances of the power-minimizing controllers are assessed through this model. The results show that the power-minimizing controllers indeed save considerable power when the machine state is relatively steady. However, a simple proportional-derivative type controller is on a par with the much more complex power-minimizing controllers in terms of power consumption when the machine is experiencing transient loads.

scholarly journals Evaluation of the Topology of Switching Power Amplifiers for Active Magnetic Bearings

Proceedings ◽  
2020 ◽  
Vol 64 (1) ◽  
pp. 25
Author(s):  
Yefa Hu ◽  
Kezhen Yang ◽  
Xinhua Guo ◽  
Jian Zhou ◽  
Huachun Wu
Keyword(s):  
Power Amplifier ◽  
Power Amplifiers ◽  
Comprehensive Evaluation ◽  
Magnetic Bearing ◽  
Bias Current ◽  
Magnetic Bearings ◽  
Active Magnetic Bearing ◽  
Active Magnetic Bearings ◽  
Switching Power ◽  
Bearing System

A switching power amplifier is a key component of the actuator of an active magnetic bearing, and its reliability has an important impact on the performance of a magnetic bearing system. This paper analyzes the topologies of a switching power amplifier of an active magnetic bearing. In the case of different coil pair arrangements and bias current distributions, comprehensive evaluation of the different topologies of switching power amplifiers is introduced. This evaluation has a guiding role in the design of a switching power amplifier of an active magnetic bearing.

Reducing Energy Consumption in Active Magnetic Bearings by a Nonlinear Variable Bias Controller

2012 ◽  
Author(s):  
Satoshi Ueno ◽  
M. Necip Sahinkaya
Keyword(s):  
Energy Savings ◽  
Magnetic Bearing ◽  
Bias Current ◽  
Active Magnetic Bearing ◽  
Current Controller ◽  
Wide Range ◽  
Bearing Force ◽  
Variable Bias ◽  
Bearing Dynamics ◽  
Magnetic Center

This paper presents a nonlinear variable bias controller for an active magnetic bearing (AMB). The nonlinear bearing force is analyzed theoretically and the control current for various bias current settings is derived from the nonlinear bearing equation. Then the power consumption is minimized to obtain the optimum bias current expression analytically. Results show that the optimum bias current can be calculated from the demand bearing force and the instantaneous rotor displacement. Moreover, the influences of magnetic bearing parameter errors are investigated and correction methods are introduced. Results of experimental rotational tests show that the rotor dynamics are not altered under variable bias currents if the proposed correction for parameter errors is implemented. The magnetic center of misalignment is also detected and compensated for. The proposed variable bias current controller provides not only significant energy savings, but also it is simple to implement and applicable to wide range of magnetic bearing systems without deterioration of the bearing dynamics.

scholarly journals Self-Sensing Active Magnetic Bearings with Zero-Bias-Current Control

2006 ◽  
Vol 126 (10) ◽  
pp. 1399-1405 ◽  
Author(s):  
Yuki Kato ◽  
Toshiya Yoshida ◽  
Katsumi Ohniwa
Keyword(s):  
Bias Current ◽  
Current Control ◽  
Magnetic Bearings ◽  
Active Magnetic Bearings ◽  
Zero Bias

Self‐sensing active magnetic bearings with zero‐bias‐current control

2008 ◽  
Vol 165 (2) ◽  
pp. 69-76 ◽  
Author(s):  
Yuki Kato ◽  
Toshiya Yoshida ◽  
Katsumi Ohniwa
Keyword(s):  
Bias Current ◽  
Current Control ◽  
Magnetic Bearings ◽  
Active Magnetic Bearings ◽  
Zero Bias

scholarly journals Research on Hysteresis Modeling and Compensation Method of Giant Magnetostrictive Force Sensor

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Chuanli Wang ◽  
Rui Shi ◽  
Caofeng Yu ◽  
Zhuo Chen ◽  
Yu Wang
Keyword(s):  
Neural Network ◽  
Magnetic Flux ◽  
Flux Density ◽  
Neural Network Model ◽  
Force Sensor ◽  
Bias Current ◽  
Compensation Method ◽  
Magnetic Flux Density ◽  
Input Force ◽  
Variable Bias

Linearity is an important index for evaluating the performance of various sensors. Under the Villari effect, there may be some hysteresis between the input force and the output voltage of a force sensor, meaning that the output will be multivalued and nonlinear. To improve the linearity and eliminate the hysteresis of such sensors, an output compensation method using a variable bias current is proposed based on the bidirectional energy conversion mechanism of giant magnetostrictive material. First, the magnetization relationship between the input force, bias current, and flux density is established. Second, a nonlinear neural network model of the force-magnetization hysteresis and a neural network model for the compensation control of the force sensor are established. These models are trained using the magnetic flux density-force curve and the magnetic flux density-current curve, respectively. Taking the optimal linearity as the objective function, the bias current under different input forces is optimized. Finally, a bias current control system is developed and an experimental test platform is built to verify the proposed method. The results show that the proposed variable bias current hysteresis compensation method enables the linearity under the return of the force sensor to reach 1.6%, which is around 48.3% higher than under previous methods. Thus, the proposed variable bias current method effectively suppresses the hysteresis phenomenon and provides improved linearity for giant magnetostrictive force sensors.

Sign in / Sign up

Export Citation Format

Share Document