Optimization of DC Starters Based on Reluctance Network Accounting for Armature Reaction Magnetic Field. Issue 16 (2nd October 2017)

• Record Type: Journal Article
• Authors: Bazhar, Sara; Fontchastagner, Julien; Takorabet, Noureddine; Labbe, Nicolas; Andreux, Raphaël
• Is Part Of: Electric power components and systems. Volume 45:Issue 16(2017)
• Page Start: 1822
• Page End: 1831
• Publication Date: 2017-10-02
• Subjects: micro-hybrid starter -- brushed DC motor -- reluctance network -- global optimization; Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2017.1402394
• Languages: English
• ISSNs: 1532-5008

Abstract

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.