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In order to perform an energy management strategy in hybrid electrical vehicles containing fuel cells, based on a power supply linking ultra-capacitors, batteries and fuel cells, time series prediction based on wavelet transform and auto-regressive integrated moving average is proposed in this paper. By wavelet denoising, the noise is removed from a part of the signal, by the auto-regressive integrated moving average method; a modeling and a prediction are done and thanks to the wavelet transform, the different frequency bands existing in the signal are attributed to the different power sources on board. The low frequency signal is attributed to the fuel cell and/or the batteries and the high frequency signal to the UC. Simulation results show the efficiency of the proposed method.

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The performance of the pantograph–catenary system is very significant in supplying reliable electrical power for the operation of trains. Many problems arise due to the increase in temperature inside the pantograph strip. More research works have been done to study the temperature extrema of the system but it is quite difficult to obtain the experimental values during a real-time train operation. Moreover, performing experimental tests needs a representative test bench of the system or a real train. This is challenging owing to the time and availability of materials and taking into account the number of physical phenomena to control and measure. To address this problem, the authors of this study present an electro-thermal modeling tool. The heat sources which characterize the system are analyzed to generate a heat equation formulation. This equation is solved with the finite differences numerical method in order to obtain the temperature distribution in the pantograph strip. In addition, some specifications such as computation time or required memory are taken into account. More precisely, mathematical and numerical optimizations are proposed to improve these specifications. The tool is validated by comparing the simulated results with the experimental tests obtained from a test bench located at POLIMI (Polytechnico Di Milano, Milan). Finally, thermal interpretations as well as relative gap analyses are done in different situations.