The study provides an extensive overview of on-board integrated chargers for electric vehicles that are based on multiphase (more than three phases) machines and power electronics. A common attribute of all discussed topologies is that they do not require a charger as a separate device since its role is transferred to the already existing drivetrain elements, predominantly a multiphase machine and an inverter. The study demonstrates how additional degrees of freedom that exist in multiphase systems can be conveniently utilised to achieve torque-free charging operation. Therefore, although three-phase (or multiphase) currents flow through machines' stator windings, they do not generate any torque; thus the machines do not have to be mechanically locked. Cost and weight saving is achieved in this way, while the available space is increased. For each topology operating principles are explained, and its control elaborated in detail for both charging and vehicle-to-grid mode. Finally, the validity of theoretical considerations and control algorithms of some of the existing charging solutions is experimentally verified and experimental performance of all discussed topologies is compared.

No abstract

To achieve EU targets for 2020, internal combustion engine cars need to be gradually replaced with hybrid or electric ones, which have low or zero GHG emission. The paper presents a short overview of dynamic history of the electric vehicles, which led to nowadays modern solutions. Different possibilities for the electric power system realizations are described. Electric vehicle (EV) operation is analyzed in more details. Market future of EVs is discussed and plans for 2020, up to 2030 are presented. Other effects of electrification of the vehicles are also analyzed.

No abstract

Expanding the number of photovoltaic (PV) systems integrated into a grid raises many concerns regarding protection, system safety, and power quality. In order to monitor the effects of the current harmonics generated by PV systems, this paper presents long-term current harmonic distortion prediction models. The proposed models use a multilayer perceptron neural network, a type of artificial neural network (ANN), with input parameters that are easy to measure in order to predict current harmonics. The models were trained with one-year worth of measurements of power quality at the point of common coupling of the PV system with the distribution network and the meteorological parameters measured at the test site. A total of six different models were developed, tested, and validated regarding a number of hidden layers and input parameters. The results show that the model with three input parameters and two hidden layers generates the best prediction performance.