Nicolas Labbe

A new modelling of DC machines taking into account commutation effects

In some specific manufactured electromechanical applications, power electronic converters must be avoided due to hostile environment. In such a context, stand-alone DC machines are good candidates because of their high reliability and low cost. However, the mechanical commutation is a big problem in this kind of machine especially in high current and low voltage applications. Losses due to arching contacts can be significant. The authors present an original technique to take into account every electrical aspect of brushes contacts (mechanical sliding contact and arching contact). The aim of this study is to determine currents and voltages of conductors during commutation in order to reduce significantly losses due to sliding contact. These evolutions are very important data for finite element analysis too.

Innovative permanent-magnet starter motors for automotive micro-hybrid applications

This paper provides a review of several original improvements of 6-ferrite 12-V brushed DC starters, based on unconventional uses of Halbach arrays. Electromagnetic behaviors are firstly analyzed, especially when specific to this saturated high-current automotive application; hence the armature magnetic reaction and its link to commutation. After explaining which properties of Halbach arrays can be exploited, each novel design is detailed. Prototypes have been built and tested, so all three variants of motors are validated, whatever the type of material implemented, sintered or bonded magnets, even combined with an ironless armature instead of the usual slotted and laminated one. The proposals appear more expensive, but occur to be a great help to applications, showing enhancements in dynamic performance and brush durability, as two mandatory key features for modern starting systems.

A Fast Finite Element Model Taking Into Account 3-D Effects for the Optimal Design of Micro-Hybrid Starters

This paper presents a fast design method taking into account 3-D effects in a reinforced brushed dc motor used as starter in automotive application. Because of their low cost and simplicity, reinforced starters are used in micro-hybrid vehicles. The specific geometry of such devices induces an axial component of the flux which cannot be accounted for by 2-D models. 3-D finite element (FE) models are suitable for this purpose but their excessive need of CPU time complicates their use in an automatic optimization procedure. We propose to identify the overhang effects by using an adapted and corrected 2.5-D FE model which is validated by 3-D computations and experiments. Finally, the 2.5-D model is implemented in a multiobjective optimization procedure.

Torque modeling and optimization of DC machine based on reluctance network taking into account armature reaction magnetic field

In this paper, the main objective is to develop a fast analytical model to be used in optimization process or coupled with other fast analytical models. A reluctance network of DC series machine is developed and shows its accuracy and robustness thanks to the consideration of the armature magnetic reaction (AMR) which is an important phenomenon in high saturated DC motors. This model is validated by a statistical way and presents a fast computation time thanks to an equivalent symmetrical machine. The optimization is used with RN and FE models and shows the efficiency of the RN to find an optimum without needing the FE final step optimization.

Hybrid Analytical Model Coupling Laplace’s Equation and Reluctance Network for Electrical Machines

This paper presents a hybrid magnetic model combining reluctance network and Laplaces equation resolution using magnetic vector potential in the air gap. The coupling of the two models is performed by introducing fictive equivalent magnetomotive forces in the air gap. The model is applied to the study of dc machines used as a starter in automotive application. Good results are obtained compared with finite-element model and experimental measurements.

Optimization of DC Starters Based on Reluctance Network Accounting for Armature Reaction Magnetic Field

Abstract In the new generation of “Stop & Start” starters, a DC series motor with high power density is used. In this application, non-symmetrical machines are used due to the single wave winding in brushed motors. The saturation of the iron core in this application reaches a really high level. Moreover, armature reaction in DC machine with a large stator pole spans makes this phenomenon even more enhanced. All these criteria lead to model the whole machine in highly saturated conditions which is time consuming. In this paper, a fast reluctance network (RN) model for an equivalent machine is proposed. It takes into account the armature reaction in high saturation conditions. It also allows a good accuracy and permits us to show the relevance of taking into account this phenomenon in torque calculation. This model is validated by a finite element (FE) method in many operating points, and by a statistical approach. It shows high robustness and low computation time. Finally, an optimization procedure using this reluctance network model and FE is presented in order to show the accuracy of the RN compared to FE model.

Optimized innovative improvements to automotive current-limited micro-hybrid starter motors

This paper is the sequel of a previous one [1] that introduced an innovative concept, validated both through modeling in time/frequency domains, and measuring its electrical effects on a prototype. This work finds here an outcome with the complete design of a product which turns to be mass-manufactured for the micro-hybrid or Stop-Start automotive market, after satisfying multiple requirements under harsh and contradictory constraints. From initial concept to a final definition, it was necessary to implement innovations from the field of electrical engineering, and to operate specific processes of numerical optimization suited to that kind of devices. The patented improvements are described, then several optimization processes are shown, that illustrate how too simple approaches lead to no solution, while implementing a multiply-constrained and multi-objective modern method, with the right tuning of its parameters, is successful.

Hybrid analytical model coupling Laplace's equation and reluctance network for electrical machines

This paper presents a hybrid magnetic model combining reluctance network (RN) and Laplaces equation resolution using magnetic potential vector in the air gap. The coupling of the two models is done by introducing fictive equivalent magneto-motive forces (MMFs) in the air-gap. Good results are obtained compared to finite element model.

Behavior analysis of a DC brush machine by space vector theory

The authors show that the space vector modelling, classically used for synchronous or asynchronous machines, can be applied with profit to DC machines. By leaning on the example of a permanent magnets machine and by comparing the results of the modelling with the experimental measurements, we notice that this process applies perfectly and allows taking into account the effects of the saturation or the possible effects of salience on the armature. This modelling constitutes an effective tool to analyze the role of every element of the machine and to lead an optimization approach.