Multiparameter identification for SPMSMs using NLMS adaptive filters and extended sliding‐mode observer

Abstract

The authors propose a parameter identification method for sequential identification of electrical and mechanical parameters of surface-mounted permanent magnet synchronous motors (SPMSMs). Two normalised least mean square (NLMS) adaptive filters (AFs) are designed for identifying the electrical parameters, where the first AF identifies the stator inductance and the second AF identifies the stator resistance and rotor flux linkage. The NLMS AFs achieve faster transient responses than recursive least squares (RLS) AFs owing to lower computing load and smaller memory size. Regarding mechanical parameters, an extended sliding-mode mechanical parameter observer (ESMMPO) is employed to estimate the system disturbance and angular velocity, from which the rotational inertia, viscous damping coefficient, and load torque are identified. The rotor flux linkage identified from the second NLMS AF is used for estimating the real-time system disturbance of the ESMMPO, which enables the identification of mechanical parameters with higher accuracy. The proposed method effectively integrates the NLMS AFs and ESMMPO into a single framework to identify both electrical and mechanical parameters of the SPMSMs. The experimental results of the proposed method are compared with those of RLS AFs and the conventional ESMMPO, which demonstrates the faster response and less steady-state parameter errors of the proposed method.

CLB-Based Development of BiSS-C Interface Master for Motor Encoders

“…As the motor control scheme, we employ the well-known field-oriented control technique under the maximum torque per ampere strategy, where three proportional and integral controllers are implemented for the motor position, speed, and current control. The overall structure of the motor control scheme is depicted in Figure 18, where we intentionally omit the direct-quadrature-zero-transformation and space vector PWM functions to avoid the complex representation and focus on the BiSS-C interface [11,12]. The motor control frequency is set as 10 kHz, and at each cycle of motor control, the motor control program requests the motor encoder data to the BiSS-C interface by signaling the START_OPERATION.…”

“…To verify the performance and practical usefulness of the developed BiSS-C interface master, we build a motor control system consisting of the motor drive installed with the developed master and an AC motor with a BiSS-C encoder [11,12]. We perform various experiments and verify the normal operation of the developed master by measuring the actual clock and data signals.…”

Parameter independent speed estimation technique for PMSM drive in electric vehicle

“…Various speed estimation algorithms are presented in the literature 2‐30 . These estimation algorithms are categorized into back EMF based method, 11,14,23,31 Observer‐based method, 6,12,25,26,32‐35 signal injection (SI) based approach, 4,24,36‐39 model‐based approach, 7,10,40‐43 and artificial intelligence‐based methods 8,16,23,44 . Some estimation algorithms are dependent on parameters and hence fail to estimate the speed/position under any variation in these parameters.…”

Research on Dynamic Identification of Servo Motor Load Inertia Based on the Error Gain Factor Model

“…The authors of [23] proposed a method for identifying the moment of inertia based on the reduced-order extended Luenberger observer (ROELO), which is very sensitive to changes in the machine parameters and effectively solves the problem of inaccurate moment of inertia identification when the motor is running at a low speed. The authors of [24] proposed an extended sliding mode mechanical parameter observer (ESMMPO) that can simultaneously estimate the system disturbance and angular velocity; identify system moment of inertia, viscous damping coefficient, and load torque; and realize multi-parameter identification. Existing online identification algorithms have a certain impact on the identification effect of the sudden moment of inertia, and cannot take into account both speed and accuracy.…”