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This is the first part of the article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its offline identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel nonlinear control techniques, nonlinear observers as well as electrical losses minimization techniques. Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined effects of the dynamic end-effects and the iron losses on the main electrical quantities of the LIM.

This is the second part of an article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the offline identification of its parameters. This second part is devoted to the description of an identification technique that has been suitably developed for the estimation of the electrical parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses. Such an identification technique is strictly related to the state formulation of the proposed model and exploits genetic algorithms for minimizing a suitable cost function based on the processing of both the primary current and speed estimation errors. The proposed parameters’ estimation technique has been validated experimentally on a suitably developed test set-up. It has been further validated by a finite element analysis model of the LIM.

This is the second part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the off-line identification of its parameters. The first part has treated the theoretical framework of the model. This second part is devoted to the description of an identification technique which has been suitably developed for the estimation of the parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses, described in the first part of the paper. Such an identification technique is strictly related to the state formulation of the proposed model and exploits Genetic Algorithms (GA) for minimizing a suitable cost function. The proposed dynamic model and its related parameters estimation technique have been validated comparing its results with those obtainable experimentally on a suitably developed test set-up as well as with those obtainable by a Finite Element Analysis (FEA) model of the LIM.

This is the first part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its off-line identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel non linear control techniques, non-linear observers as well as electrical losses minimization techniques (ELMTs). Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined effects of the dynamic end-effects and the iron losses on the main electrical quantities of the LIM.