Robust DSP-based efficiency optimization of a variable speed induction motor drive

Abstract

This paper proposes a practical digital-signal-processor (DSP)-based algorithm for the online efficiency optimization of induction motor drives. The algorithm combines good features of the search control and loss-model-based control, while simultaneously eliminating their major drawbacks. It ensures very fast convergence without the need for any a priori knowledge of the motor loss-related parameters. The minimum loss operating point is decided from a functional approximation of the motor and the power converter losses, in the form of a suitably defined loss function. The loss function parameters are obtained online from input power measurement and a dedicated identification routine acting in conjunction with the common drive control functions. Proposed online identification of the loss function parameters relies upon the signals and states readily available within the drive controller memory and does not involve the user entry nor the initialization procedure. The proposed controller is coded into a conventional low-cost 16-bit DSP and verified on a 2.2-kW induction motor drive prototype. Index Terms-Digital signal processors (DSPs), induction motor drives (IMDs), minimum energy control, power conversion.

New Trends in Efficiency Optimization of Induction Motor Drives

“…Motor losses: These losses consist of hysteresis and eddy current losses in the magnetic circuit (core losses), losses in the stator and rotor conductors (copper losses) and stray losses. At nominal operating point, the core losses are typically 2-3 times smaller then the cooper losses, but they represent main loss component of a highly loaded induction motor drives (Vukosavic & Levi, 2003). The main core losses can be modeled by (Blanusa, et al, 2006):…”

“…Considering also, that the stray losses are of importance at high load and overload conditions, while the efficiency optimizer is effective at light load, the stray losses are not considered as a separate loss component in the loss function. Formal omission of the stray loss representation in the loss function have no impact on the accuracy algorithm for on-line optimization (Vukosavic & Levi, 2003). Based on previous consideration, total flux dependent power losses in the drive are given by the following equitation: …”

A Study on Fast Maximum Efficiency Control of Stator-Flux-oriented Induction Motor Drives

“…At light loads, however, the rated flux operation causes excessive core loss, thus impairing the efficiency of the motor. Therefore, a control technique that maximizes efficiency by adjusting the flux level is highly required at light loads [9]- [23].…”

“…In [22] and [23], a hybrid method combining the Loss Model and the Search Method is proposed for convergence improvement. In [22], the first optimum flux was estimated using the LMC method.…”

“…However, the authors did not clearly present the current step for the SC method, which was adjusted adaptively. In [23], the operating point for the minimum loss was rapidly computed using a functional approximation of the motor and power converter losses. The loss function parameters were obtained from the measured input power.…”