Research Interests:
This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of... more
This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of artificial neural networks. It is possible to design control processes of railway traction effectively, based on these models. Real data of electric power consumption of traction substations in the Czech Republic within one year of train diagram 2006/2007 validity are used for verification of the models. These models can build support for e-energy telematic systems.
Research Interests:
In this paper, capacity fade of LiFeYPO4/graphite commercial cells during 116 cycles under different temperatures is studied. The cells were discharged in two modes, during Drive Cycle (DrC) discharge cycles the cell was discharged with... more
In this paper, capacity fade of LiFeYPO4/graphite commercial cells during 116 cycles under different temperatures is studied. The cells were discharged in two modes, during Drive Cycle (DrC) discharge cycles the cell was discharged with current waveform calculated for example battery electric vehicle (BEV) under WLTC 3b drive cycle conditions, whereas during Constant Current (CC) discharge cycles the cell was discharged with a constant current of the same root mean square of the current, as the WLTC 3b current waveform and with the same depth of discharge. All the cells were charged in constant current/constant voltage mode. Two fresh cells were used for each discharge mode at 25 °C and as the results were similar, only one cell per discharge mode was used at the other temperatures 5 °C and 45 °C. Furthermore, simulation P2D model of calendar and cycle life was calibrated based on experimental data. SoC floating was observed during cycling for both discharge modes, accompanied with ...
Research Interests:
Research Interests:
Research Interests:
This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of... more
This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of artificial neural networks. It is possible to design control processes of railway traction effectively, based on these models. Real data of electric power consumption of traction substations in the Czech Republic within one year of train diagram 2006/2007 validity are used for verification of the models. These models can build support for e-energy telematic systems.