Magnetization-Dependent Core-Loss Model in a Three-Phase Self-Excited Induction Generator

Abstract

Steady-state, transient, as well as dynamic analyses of self-excited induction generators (SEIGs) are generally well-documented. However, in most of the documented studies, core losses have been neglected or inaccurately modeled. This paper is concerned with the accurate modeling of core losses in SEIG analysis. The core loss is presented as a function related to the level of saturation. This relation is determined experimentally and integrated into a nonlinear model of the SEIG. The nonlinear model is solved using a mathematical optimization scheme to obtain the performance parameters of the SEIG. A new set of curves describing accurate behavior of the SEIG parameters is produced and presented in this paper. The computed parameters of the model are validated experimentally, and the agreement attained demonstrates the functionality and accuracy of the proposed core-loss model.Energies 2018, 11, 3228 2 of 12 variable function of the level of saturation in the generator. This can be extremely important, especially in the modern, well-designed SEIGs with accurate high-saturation designs. This paper derives a mathematical model for core loss as a function of saturation in the SEIG based on experimental measurements. Consequently, an accurate representation for the SEIG for advanced theoretical analysis is re-developed. The computed parameters of the model are validated experimentally, and the agreement attained demonstrates the functionality and accuracy of the proposed core-loss model. AnalysisThe system used to investigate SEIG is shown schematically in Figure 1. A three-phase synchronous motor was used as a prime mover during experimental tests.The per-phase equivalent circuit of a three-phase SEIG under R-L load is shown in Figure 2. The effect of the saturation is considered for the core loss resistance, R c , and the magnetizing reactance, X m . To determine the values of the circuit parameters, the generator is conventionally tested under DC, locked rotor, and no load [3][4][5][6][7][8]. Values of R s , R r , X s , and X r are found from the DC and locked rotor tests. The magnetization curve of the machine, which includes the relation of R c and X m against air-gap voltage (or magnetization current), is obtained from a no load test (at slip = 0), as shown in Figure 3. As clearly shown, X m and R c are variable according to the level of saturation as it is linked with the air-gap voltage. The magnetization curve of the machine in Figure 3 is redeveloped and depicted in Figure 4a, to be used with the circuit shown in Figure 2 to yield the SEIG performance measures. As the saturation level in the generator is variable, X m is obviously variable and R c must also be variable. To the best of the authors' knowledge, this fact has been ignored in all the published research concerning SEIGs [5][6][7][8][9][10][11][12][13].

Monitoring of the Efficiency and Conditions of Induction Motor Operations by Smart Meter Prototype Based on a LoRa Wireless Network

“…To measure the physical variables of the IM in [15], an electronic circuit is developed which is located inside the motor; this circuit has an integrated wireless communications chip NRF24L01, which allows communicating with another similar module connected to a PC that collect and stores the engine data.…”