AAC 2019 Paper Abstract

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Paper MoAT3.3

SOLANO-ARAQUE, Edwin (Université d'Orléans, PRISME; Renault S.A.S.), Colin, Guillaume (Univ. Orléans), Cloarec, Guy-Michel (Renault SA), ketfi-cherif, Ahmed (Renault), CHAMAILLARD, Yann (University of Orléans)

Determining Vehicle Acceleration from Noisy Non-Uniformly Sampled Speed Data for Control Purposes

Scheduled for presentation during the Regular Session "Control & Estimation I: Vehicle Dynamics" (MoAT3), Monday, June 24, 2019, 11:50−12:10, Chamerolles

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 24, 2024

Keywords Vehicle State Estimation: Sensor Development, Sideslip Angle Observation, Tire and Friction Estimation, Human Factors in Driver Dynamics or Driver Assistance Systems, Plant Modelling and System Identification

Abstract

Vehicle acceleration is an important variable for many automotive control applications. In this paper, we present an approach to estimate vehicle acceleration from vehicle speed data coming from the CAN (Controller Area Network) bus. The proposed method, which can be seen as an extension of the Savitzky-Golay filter to non-uniformly sampled signals, re-samples them to a constant period while filtering noise coming from different sources and also provides a proper estimation of vehicle acceleration. We also consider the frequency response of the filtering effect of the method. Finally, some practical considerations for efficient implementation of the algorithm are given.

 

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