Abstract
This paper presents an improved model-based predictive direct torque control (MPDTC) to improve torque accuracy and reduce torque ripples which is a major issue in conventional direct torque control (DTC). Hysteresis controllers and traditional DTC switching tables are replaced by a model predictive controller to achieve an online optimization for voltage space vector selection and optimal duty ratio modulation method for torque ripple reduction. In order to provide an accurate motor model for MPDTC, novel offline and online motor parameter estimation methods are proposed to improve performance of the proposed MPDTC. The proposed parameter estimation adopts Popov's hyper stability theorem to estimate accurate motor parameters, such as stator resistance, stator inductance and rotor flux linkage, which are critical for torque and flux estimation. The parameter adaptive MPDTC is verified by a hardware in the loop emulation platform, and experiment result is demonstrated using a dynamometer test bench, which therefore proves the feasibility of the proposed method.
Highlights
In modern industry, the interior permanent magnet synchronous motor (IPMSM) has been widely used in dynamic systems due to its high power and torque densities as well as efficiency
In order to make the parameter estimator insensitive to the rotor position error, this paper proposes a modified motor parameter estimation method which will be explained
An advanced model-based predictive direct torque control (MPDTC) for a IPMSM is proposed by introducing the duty ratio modulation which controls the operating time of the optimal voltage vector to improve the torque steady-state performance and minimize switching frequency
Summary
The interior permanent magnet synchronous motor (IPMSM) has been widely used in dynamic systems due to its high power and torque densities as well as efficiency. To make the torque ripple of DTC as low as FOC, the cost function is redefined and a duty ratio modulation algorithm of active vector during one control period is applied as presented in [8], [9]. RLS is based on linear model without considering practical nonlinearity of motor, and EKF need many CPU resources to implement higher order matrix inversion calculation, which are not feasible for accurate and low cost solution. Most importantly, all these algorithms are based on dq coordinate and become unstable due to high rotor position error.
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