Multiphysical approach including equivalent circuit models for the sizing by optimization

Abstract

Purpose Multiphysical models are often useful for the design of electrical devices such as electrical machines. In this way, the modeling of thermal, magnetic and electrical phenomena by using an equivalent circuit approach is often used in sizing problems. The coupling of such models with other models is difficult to take into account, partly because it adds complexity to the process. The paper proposes an automatic modelling of thermal and magnetic aspects from an equivalent circuit approach, with its computation of gradients, using selectivity on the variables. Then, it discusses the coupling of various physical models, for the sizing by optimization algorithms. Sensibility analyses are discussed and the multiphysical approach is applied on a permanent magnet synchronous machine. Design/methodology/approach The paper allows one to describe thermal and magnetic models by equivalent circuits. Magnetic aspects are represented by reluctance networks and thermal aspects by thermal equivalent circuits. From circuit modelling and analytical equations, models are generated, coupled and translated into computational codes (Java, C), including the computation of their jacobians. To do so, model generators are used: CADES, Reluctool, Thermotool. The paper illustrates the modelling and automatic programming aspects with Thermotool. The generated codes are directly available for optimization algorithms. Then, the formulation of the coupling with other models is studied in the case of a multiphysical sizing by optimization of the Toyota PRIUS electrical motor. Findings A main specificity of the approach is the ability to easily deal with the selectivity of the inputs and outputs of the generated model according to the problem specifications, thus reducing drastically the size of the jacobian matrix and the computational complexity. Another specificity is the coupling of the models using analytical equations, possibly implicit equations. Research limitations/implications At the present time, the multiphysical modeling is considered only for static phenomena. However, this limit is not important for numerous sizing applications. Originality/value The analytical approach with the selectivity gives fast models, well-adapted for optimization. The use of model generators allows robust programming of the models and their jacobians. The automatic calculation of the gradients allows the use of determinist algorithms, such as SQP, well adapted to deal with numerous constraints.

Approach for sizing by optimization of an electrical drive considering a multiphysics and multidynamics behaviour

“…After computing the value of the equivalent thermal circuit elements, the circuit is put into equations by an automatic model generation tool (Bordry and Foch, 1985; Baraston et al , 2016). Due to the size of the circuit, putting it into equations is very complex and this tool is used to write the numerical state matrices from the thermal circuit netlist, and to modify them if component values have changed.…”

Calculation approach of reluctance in the magnetic circuit of transformer employed to convert into equivalent electric circuit

“…To validate the approach for reluctance calculation, the equivalent electric circuits are simulated in Simplorer, and the results are compared with the circuit-FEM analysis. In the circuit-FEM coupled simulation, the transformer is modeled in ANSYS, and the external excitation circuit is established in Simplorer (Baraston et al , 2016). By setting different switching angles of the voltage source, the coupled circuit-FEM simulation can accurately reflect the surge state.…”

Design technique for leakage current reduction in surge arrester using gravitational search algorithm and imperialist competitive algorithm

“…The interest in algorithms has been increasing among researchers since many years before. The behaviours of natural phenomena have motivated the researchers to explain complex computational difficulties (Alotto et al, 2014;Baraston et al, 2016;Caner et al, 2016;Golak and Kordos, 2016). Many researchers have studied on design optimisation of surge arresters to improve their performance.…”