Abstract
This paper presents a new, computationally modest on-line identification method for the simultaneous estimation of the rotor resistance and magnetizing inductance of an induction machine suitable for electric drives that use an indirect field-oriented control strategy (IFOC), and their control hardware is equipped with a resource-constrained microcontroller. Such drives can be found both in the manufacturing industry and railway traction vehicles in the thousands, having either older control hardware that cannot cope with computationally excessive identification methods or being in cost-sensitive applications, thus being equipped with a low-cost microcontroller. IFOC is a very common control strategy for such drives due to its good dynamic properties and comparatively simple implementation. However, it is sensitive to inaccuracies of rotor resistance and magnetizing inductance. These two parameters change during the operation of the drive, being influenced by the temperature, frequency, and saturation of the magnetic circuit. Improper values of parameters in the controller can degrade the performance of IFOC, resulting in slower acceleration or unnecessary oversaturation of the machine. Respecting these changes can therefore bring significant benefits such as the good dynamic properties of the drive, which can shorten operations in the manufacturing industry or travel times of vehicles. A number of on-line identification methods for monitoring the parameter changes have been published so far, but the majority of them are demanding on microcontroller time or its memory. The proposed method, on the contrary, is comparatively simple and thus easy for implementation with low requirements to the microcontroller. Therefore, it is suitable for both upgrades of existing drives or new low-cost applications. Derivation of the method from the mathematical model and the final algorithm for the microcontroller are presented. The performance of the proposed method is validated with experimental results obtained with a 3.5 kW induction machine drive with an industrial microcontroller during a warming test and under various loads and frequencies.
Highlights
Induction machines have many favorable properties such as robustness, reliability, and low maintenance cost, which have caused them to become one of the most widespread types of electromechanical converters in industrial and railway applications
The proposed method is designated for machines that can be described by a model in the form of a T-equivalent circuit, as presented in Figure 2, which is the majority of induction machines used in industry or traction
When the machine conforms to the stated criterion, the results should be correct regardless of the construction details of the machine
Summary
Induction machines have many favorable properties such as robustness, reliability, and low maintenance cost, which have caused them to become one of the most widespread types of electromechanical converters in industrial and railway applications. An adaptive observer for stator and rotor resistance was utilized in [28] These observer-based methods need matrix calculations in their algorithms, which can be a limiting point for their deployment in a microcontroller with resource-constrained hardware. In [40], the authors used voltage-model-derived differential equations to calculate rotor resistance and magnetizing inductance. Based on the temperature change, they calculated the values of both stator and rotor resistances assuming that the temperature of the whole machine is the same. A number of drives are still equipped with a speed sensor, which can be used to help with parameter identification Such examples can be found in the manufacturing industry [42,43,44] or railway traction vehicles (locomotives, EMUs) [45], where induction machines are still the dominant type of electromechanical converter. As deriving the calculation is based on a vector description that can be in the scale of both maximum values (amplitudes) or RMS values, the calculation gives the same results both for maximum or RMS input values
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