Speed Sensorless Model Predictive Current Control of Linear Induction ‎Machines in Urban Transit

Document Type : Original Article

Authors

1 Process Control Technology Dept., Faculty of Technology and Education, Beni-Suef University, Beni-Suef, Egypt

2 Electrical Engineering Dept., Faculty of Engineering, Beni-Suef University, Beni-Suef, Egypt

3 Electrical Engineering Dept., Faculty of Engineering, Minia University, Egypt

4 Faculty of Engineering Minia University

Abstract

There is an increasing interest in achieving global goals of mitigating climate changes that target ‎environment protection. Thus, electric vehicles (as linear metros) were elaborated to avoid greenhouse ‎gas emissions which negatively impact climate. Hence, in this paper, a finite control set-model ‎predictive current control (FCS-MPCC) method of linear induction machine (LIM) was proposed for ‎linear metro drives to achieve lower thrust ripples and eliminate the selection of weighting factor (WF), ‎the main limitation of conventional finite control set-model predictive thrust control (FCS-MPTC). ‎Also, a model reference adaptive system (MRAS) was used for speed estimation due to some ‎environmental considerations and cost-effectiveness. The proposed method used a single cost function ‎that avoided the existence of WF and consisted of primary current errors between the predicted values ‎and their references in αβ-axes. A comparison between the FCS-MPTC and the suggested control ‎method was conducted using Matlab/Simulink under a wide range of operating circumstances and via ‎uncertainty validations issues, on the basis of one 3 kW arc induction machine (which constructed to ‎imitate the actual behavior of the LIM). The extensive simulation results revealed that the proposed ‎FCS-MPCC method can lead to much lower thrust ripples without heavy calculation steps. Moreover, ‎the speed error between the estimated and actual speeds is about 0.025% of the reference value which ‎validates the speed estimation scheme.‎

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