München, Germany


München, Germany
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Tong Q.,Huazhong University of Science and Technology | Chen C.,Huazhong University of Science and Technology | Zhang Q.,IMRA Europe S.A.S. | Zou X.,Huazhong University of Science and Technology
Sensors (Switzerland) | Year: 2015

To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm. © 2015 by the authors; licensee MDPI, Basel, Switzerland.

Vrazic S.,IMRA Europe SAS | Sugae I.,Aisin Seiki | Niwa E.,Aisin Seiki | Murakami Y.,Aisin Seiki
21st World Congress on Intelligent Transport Systems, ITSWC 2014: Reinventing Transportation in Our Connected World | Year: 2014

This paper describes a processing system that recognizes and localizes emergency vehicles. The system brings more safety by informing the driver of the type of emergency vehicles (ambulance, police and fire brigade), the location, distance and speed. The car environment is adverse, with noise, background music and occupants talking. The technology uses a reduced to the 3-microphones array for multiple simultaneous sources localization based on Direction-Of-Arrival estimation. The sources are segmented in time, and the type of emergency vehicle is identified. The music does not need to be muted. The assessment is done using an out-of-vehicle and in-vehicle setups.

Shu L.,Zhejiang University | Zhang J.,Zhejiang University | Peng F.,Michigan State University | Chen Z.,IMRA Europe S.A.S.
2014 IEEE Energy Conversion Congress and Exposition, ECCE 2014 | Year: 2014

To reduce the power dissipation and switching stress of high power IGBTs during switching transient, a new active gate drive method based on voltage controlled current source (VCCS) is proposed in this paper. Compared to the conventional gate drive (CGD) for IGBTs, the proposed current source gate drive (CSD) method achieves faster switching speed and effective control on current overshoot at turn-on and voltage overshoot at turn-off. Thus the capacity utilization of IGBT devices can be improved. The detailed operation principle of the proposed CSD method is presented, and the experiment results based on a 1200V/200A IGBT module are also provided. © 2014 IEEE.

Vrazic S.,IMRA Europe SAS | Sugae I.,Aisin Seiki | Inaba H.,Aisin Seiki | Murakami Y.,Aisin Seiki
20th ITS World Congress Tokyo 2013 | Year: 2013

This paper describes a pre-processing system that allows robust Automatic Speech Recognition (ASR) in car adverse environment. The pre-processing with only 3 microphones allows that only the driver provides commands to the car, the passenger voice is cancelled or reduced depending the situation and music does not need to be muted. An adaptive beamformer is combined with sources localization based on Direction-Of-Arrival (DOA) estimation. Additional specific adaptive filters are combined to remove remaining noises (engine, road, wind, music, etc.). The evaluation is done using real driving situations on a Toyota RAV4 car and with the Dragon Naturally Speaking (DNS) software in French to assess the recognition rate. The results show a recognition rate drastically improved.

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