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The paper deals with the design by optimization in pre-sizing step of a drive system that combines a switched capacitor system and a permanent magnet synchronous machine (PMSM). The sizing of the converter and the machine are considered strongly dependent due to the series quasi-resonant topology. The system modelling is based on a semi-analytical approach validated by finite element (FE) simulations. It involves an analytical modelling of the electrical machine and a numerical time solving of the electrical circuit sub-model because of the natural switching events of diodes. The optimization is carried out by SQP (Sequential Quadratic Programming). The model gradients are computed combining mathematical laws, symbolic derivation and automatic differentiation. Finally, trade-offs and gains on the machine power density, the magnet volume and the efficiency are investigated through a Pareto approach. [ABSTRACT FROM AUTHOR]

In France, most of the trains are electrical and some are fed by 1500 V DC voltage. When a train is traveling, the power consumption creates a voltage drop. Therefore, below a certain limit, the train has to slow down its speed. This limitation prevents the increase of traffic in some area that needs an electric reinforcement. This paper proposes to use embedded storage systems to support the voltage of the catenary. The main issue is how to size such an energy storage system? In this way, several aspects (e.g.: the energy management strategy) have to be taken into account. The paper deals with an optimization-based sizing method for the embedded energy storage systems. The proposed method takes into account the energy management strategy in the sizing by optimization. A comparison is made between the use of batteries or supercapacitors. [ABSTRACT FROM AUTHOR]

The paper proposes an optimization approach to address the modeling and sizing complexities of Brushless Doubly-Fed Reluctances Machines. A semi-analytical model and a reluctance network model are coupled to a deterministic optimization algorithm where several inputs and outputs parameters can be constrained to solve sizing equations iteratively by maximizing or minimizing an objective function. A Pareto Front strategy is used to illustrate the models capabilities, highlighting the trade-offs on the design of this kind of electrical machines. The optimization model provides fast results to define a first design, reducing the number of unknown parameters of early development stages. This saves computation time and computer resources in the design process compared to Finite Element Analysis. [ABSTRACT FROM AUTHOR]

Hybrid electrical vehicles involve two sources of energy, usually gasoline and electricity. The energy management determines the power sharing between the internal combustion engine and the electrical machine (EM). It is highly dependent on the driving cycle (i.e. the use of the vehicle). In this context, the optimal sizing of the EM is determined by: the driving cycle, the power-train characteristics (i.e. ratios and physical limitations e.g. maximum torque available) and the energy management. The key idea of this work is to involve the driving cycle and the environment of the electrical machine in a global multi-objective optimization process taking into account an optimal energy management and an accurate model of the EM based on magnetic circuit equivalent model. [ABSTRACT FROM AUTHOR]

Fuel consumption of a hybrid electrical vehicle (HEV) depends on the driving cycle (i.e. the use of the vehicle), on the powertrain components and on the energy management. The paper proposes an optimal component sizing process taking into account the entire system. An optimal energy management is used in order to minimize the fuel consumption on a driving cycle. This optimization approach of the HEV uses Radial Basis Function models which allow a fast constrained optimization. [ABSTRACT FROM AUTHOR]