Identification of sensitive R-L parameters of a Multi-phase drive by a vector control

This paper focuses on an experimental method to determine the electric parameters of a seven-phase low-voltage multiphase drive. The drive is a belt driven starter-alternator for powerful cars with Hybrid Electrical Vehicles (HEV) functions. The resistive and inductive parameters are necessary to obtain the six characteristic time constants of the control modeling. Classical direct measurements lead to imprecise results because of very low values for the windings electric resistance (a few mΩ) and inductance (a few μH). Effects of the imprecision on the measurements are all the more important that time constants are obtained by a ratio of cyclic inductances by resistance, with cyclic inductances being a linear combination of seven measured inductances. The methodology for identification detailed in this paper is based on a stator current vector control, in a multi-reference frame. This methodology allows us to get directly these time constants. Numerous measurements allow the robustness of the method to be evaluatedThis work was supported by the French car supplier Valeoand the regional council of France Region-Nord-Pas-De-Calais

Modeling and Control of a 7-phase Claw-pole Starter-alternator for a Micro-hybrid Automotive Application

This paper deals with the modeling and the control of a new high power 12V Integrated Starter Alternator (ISA). This system is used to bring micro-hybrid functions to standard Internal Combustion Engine (ICE) vehicles. The drive is composed of a seven-phase synchronous claw-pole machine with separate excitation, supplied with a seven-leg Voltage Source Inverter (VSI) designed for low voltage and high current. The system is modeled in a generalized Concordia frame and a graphical description is used to highlight energetic properties of such a complex system. A control scheme is then deduced from this graphical description. Two controls are achieved in generator mode and compared: one is using the VSI in a square-wave mode, the other in a Pulse Width Modulation (PWM) mode. Experimental results are provided.This work was supported by the French car supplier Valeoand the regional council of France Region-Nord-Pas-De-Calais

Face recognition in different subspaces - A comparative study

Face recognition is one of the most successful applications of image analysis and understanding and has gained much attention in recent years. Among many approaches to the problem of face recognition, appearance-based subspace analysis still gives the most promising results. In this paper we study the three most popular appearance-based face recognition projection methods (PCA, LDA and ICA). All methods are tested in equal working conditions regarding preprocessing and algorithm implementation on the FERET data set with its standard tests. We also compare the ICA method with its whitening preprocess and find out that there is no significant difference between them. When we compare different projection with different metrics we found out that the LDA+COS combination is the most promising for all tasks. The L1 metric gives the best results in combination with PCA and ICA1, and COS is superior to any other metric when used with LDA and ICA2. Our results are compared to other studies and some discrepancies are pointed ou