Date of Award


Degree Type


Degree Name



Electrical and Computer Engineering

First Advisor

Narayan C. Kar


Applied sciences, Distribution transformers, Electric vehicles, Load management, Optimization, Permanent magnet synchronous motor




The growing concern about CO 2 emissions and dependency on foreign oil contributes to the increasing application of electric vehicles (EVs). EV battery chargers are non-linear loads and large-scale application of EVs increases the grid harmonics significantly. The grid harmonics have negative impacts on the components of the power system including distribution transformers. In this thesis, the potentials for EVs to penetrate the transportation market are studied and the additional load demand when EV penetration achieves its full potential is estimated. Loss and thermal modeling of distribution transformers incorporating EV penetration are presented and the impacts of additional EV load demand on load loss, temperature and aging acceleration factor of a sample 100 kVA distribution transformer is estimated. The ability of the existing power system to accommodate the additional EV load demand without threatening the safe operation of distribution transformers (DTs) is evaluated based on the calculation results.

To increase the capacity of the existing power system in accommodating the new EV load demand, an optimal charging schedule based on optimization of negative impacts on DTs is proposed. In this regard, EV charging load is formulated as an optimization problem and Newton Method and Karush-Kuhn-Tucker (KKT) optimality conditions are investigated as effective optimization algorithms for solving the developed optimization problem. Using the proposed charging schedule, the impacts of EV penetration on a sample 100 kW distribution transformer is studied and the effectiveness of the proposed charging schedule is validated through a comparative study.

Moreover, this thesis investigates application of permanent magnet synchronous motors (PMSMs) in EVs as a second approach for reducing the negative impacts of EV charging on DTs. Controlling PMSMs based on their efficiency maps contributes to increasing the efficiency of EV powertrain and consequently reducing the EV load demand. Considering the significance of accurate modeling in the control of PMSM, this thesis focuses on accurate modeling of PMSM and the sources of error in PMSM steady-state performance estimation.

Inaccuracy in the PMSM steady-state performance calculation corresponds to the parameter error and model imprecision. Accurate determination of the PMSM parameters may encounter various complications due to its rotor structure and drive design. Therefore, the PMSM performance calculation is generally vulnerable to inaccuracy because of the parameter error. This thesis studies the effect of parameter error on the inaccuracy of the performance calculations. Several methods for determining the PMSM armature resistance, flux linkage constant and d- and q-axis inductances with varying level of accuracy are proposed. The presented methods are applied to a laboratory PMSM and the sensitivity of the PMSM output power to the equivalent circuit parameters is analyzed based on the experimental results. In addition, this thesis contributes to accurate performance estimations of the PMSM by developing a precise model that incorporates the saturation saliency and core losses. The accuracy of the proposed model is compared with the conventional dq-axis model and its higher accuracy is validated through experimental results.

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