Arnaud Baraston, Laurent Gerbaud, Vincent Reinbold, Thomas Boussey and Frédéric Wurtz
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…
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.
Robin Thomas, Laurent Gerbaud, Herve Chazal and Lauric Garbuio
This paper aims to describe a modelling and solving methodology of a (static converter–electric motor–control) system for its sizing by optimization, considering the dynamic…
Abstract
Purpose
This paper aims to describe a modelling and solving methodology of a (static converter–electric motor–control) system for its sizing by optimization, considering the dynamic thermal heating of the machine.
Design/methodology/approach
The electrical drive sizing model is composed of two simulators (electrical and thermal) that are co-simulated with a master−slave relationship for the time step management. The computation is stopped according to simulation criteria.
Findings
This paper details a methodology to represent and size an electrical drive using a multiphysics and multidynamics approach. The thermal simulator is the master and calls the electrical system simulator at a fixed exchange time step. The two simulators use a dedicated dynamic time solver with adaptive time step and event management. The simulation automatically stops on pre-established criteria, avoiding useless simulations.
Research limitations/implications
This paper aims to present a generic methodology for the sizing by optimization of electrical drives with a multiphysics approach, so the precision and computation time highly depend on the modelling method of each components. A genetic multiobjective optimization algorithm is used.
Practical implications
The methodology can be applied to size electrical drives operating in a thermally limited zone. The power electronics converter and electrical machine can be easily adapted by modifying their sub-model, without impacting the global model and simulation principle.
Originality/value
The approach enables to compute a maximum operating duration before reaching thermal limits and to use it as an optimization constraint. These system considerations allow to over constrain the electrical machine, enabling to size a smaller machine while guaranteeing the same output performances.