An online nonlinear identification method for estimation of magnetizing curve and parameters of an induction motor * *Research by Y. Kouhi has been supported by the Federal Ministry for Economic Affairs and Energy under Project no. 01MY14007A.

Kouhi, Y.; Kertzscher, Jana

doi:10.1016/j.ifacol.2017.08.312

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…At present, the commonly used online identification methods include the leastsquares method, Kalman filter method, model reference adaptive method, state observer method, gradient algorithm, and so on. Wang and Kertzscher [14] proposed a nonlinear leastsquares parameter identification method, which minimizes the residual by eliminating the theoretically calculated parameter vector and realizes the real-time update of the inertia valve in a system with slow speed changes. Li et al [15] proposed a direct power control and adaptive online parameter identification technology based on predictive control, which reduces the uncertainty of the predictive model without the need for additional sensors estimated parameters.…”

Section: Introductionmentioning

confidence: 99%

An optimization method of acceleration and deceleration time of feed system based on load inertia

Zhou,

Yang,

Guo

et al. 2024

Meas. Sci. Technol.

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The acceleration and deceleration time is usually a constant value in the process of computer numerical control (CNC) machine tool processing, which cannot adapt to the change of external load and greatly affects processing efficiency. This paper proposes an optimization method for the acceleration and deceleration time of the feed system based on load inertia, which provides the basis for the adaptive adjustment of the acceleration and deceleration time of the feed system. Firstly, by establishing the dynamic model of the servo system, the acceleration and deceleration method is used to identify the external load inertia under different working conditions. The prediction model of the current variance based on load inertia and acceleration and deceleration time parameters is established by using the response surface method, and then the multi-objective particle swarm optimization algorithm is used to build the acceleration and deceleration time optimization model based on the load inertia. At the same time, the inertia identification part is compared with the model reference adaptive system method and the empirical formula estimation method based on current and velocity, the simulation and cutting experiment results show that the inertia identification method based on acceleration and deceleration optimizes the other method. Finally, the machining experiments are carried out on three-axis and five-axis machine tools with the same machine tool type, and by adding different counterweight blocks to change the external load. The test proves that the acceleration and deceleration adaptive adjustment strategy based on load inertia can effectively improve processing efficiency and reduce the fluctuation of the processing load.

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Section: Introductionmentioning

confidence: 99%

An optimization method of acceleration and deceleration time of feed system based on load inertia

Zhou,

Yang,

Guo

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

Pulse-width modulation in the autonomous voltage inverter in identifying parameters of the three-phase asynchronous motor

2021

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This paper deals with control algorithm of a two-level autonomous voltage inverter with pulsewidth modulation in forming test phase voltages for identification of parameters of a three-phase asynchronous motor. Necessary conversion is carried out, the laws of change of phase voltages of an autonomous inverter are obtained. The feasibility of using third order active Butterworth filters for determining first harmonics of phase voltages is shown. By means of computer simulation and experimental research, it is revealed that the required shapes of phase voltages can be implemented in a twolevel autonomous voltage inverter with pulse-width modulation, and the presence of Butterworth filters does not introduce significant distortion and allows to obtain necessary phase voltage shapes in the generalized electric machine.

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Performance of Recursive Least Squares Algorithm Configurations for Online Parameter Identification of Induction Machines in an Automotive Environment

Nachtsheim¹,

Ernst²,

Endisch

et al. 2023

IEEE Trans. Transp. Electrific.

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An online nonlinear identification method for estimation of magnetizing curve and parameters of an induction motor * *Research by Y. Kouhi has been supported by the Federal Ministry for Economic Affairs and Energy under Project no. 01MY14007A.

Cited by 3 publications

References 7 publications

An optimization method of acceleration and deceleration time of feed system based on load inertia

An optimization method of acceleration and deceleration time of feed system based on load inertia

Pulse-width modulation in the autonomous voltage inverter in identifying parameters of the three-phase asynchronous motor

Performance of Recursive Least Squares Algorithm Configurations for Online Parameter Identification of Induction Machines in an Automotive Environment

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