Abstract
Sensorless machine drives in vehicle traction frequently experience rapidly-changing load disturbance and demand fast speed dynamics. Without gain-scheduling or compensation, conventional quadrature phase-locked-loop (Q-PLL) is unable to accurately estimate the rotor position and speed for these systems. In this paper, a third-order nonlinear extended state observer (TNESO) is proposed for position and speed estimation for sensorless interior permanent magnet synchronous motor drives. TNESO has the power of nonlinear feedback and takes the advantages of fast convergence and disturbance rejection. An optimized parameter configuration method is deployed to extend the disturbance observation bandwidth of the TNESO. Both steady state and transient performance of TNESO are verified through the experimental tests. In comparison with the performance of conventional Q-PLL scheme, the proposed observer is proved to be capable of delivering higher precision of position and speed estimation against rapidly varying disturbance in wide operating range.
Highlights
Permanent Magnet Synchronous Motors (PMSMs) are widely used in the applications where require high precision and high dynamic performance
Interior Permanent Magnet Synchronous Motor (IPMSM) have been commercialized as the main traction motors for hybrid electric vehicles (HEVs) and electric vehicles (EVs)
This paper proposes a Third Order Nonlinear ESO (NESO) (TNESO) with a non-linear feedback structure
Summary
Permanent Magnet Synchronous Motors (PMSMs) are widely used in the applications where require high precision and high dynamic performance. Apart from closed-loop sensorless schemes, open-loop methods that do not need sensorless observers such as V/f or I/f [25] have been proposed They might not be able to deal with the controlled drive system that requires high-quality transient profile. The control performance of NESO is obvious but the parameter tuning method is very different from the counterpart linear observer [19]. For NESO [19], it is proposed that the parameters can be dynamically determined by setting the poles of compensation matrix This method is only suitable for the ESO with smooth differentiable nonlinear functions and cannot be applied to the ESO having non-smooth function. The current issues to be solved are how to analyze control performance, find out the relationship between parameters and performance and put forward the optimization method
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