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Data Fusion Modeling for an RT3102 and Dewetron System Application in Hybrid Vehicle Stability Testing

Zhibin Miao, Hongtian Zhang

Algorithms · 2015

doi:10.3390/a8030632 (opens in a new tab)

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Abstract

More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

Abstract licence: CC BY

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