Implementation and testing of a sideslip estimation for a formula student prototype

Abstract This document details the implementation and test of a self-calibrating estimation architecture for the sideslip of a Formula Student prototype. The proposed algorithm fuses several sensors being the most relevant an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). It is presented a comparison between a linear and a non-linear estimators, and their consequences. The algorithm is tested with real data from a Formula Student vehicle, and validated with a differential GPS. It is also reported an implementation of the proposed algorithm in a micro-controller, and tested with a radio-controlled (RC) vehicle. These results are also validated with the data from a more accurate indoor motion system.

[1]  H.F. Grip,et al.  Vehicle sideslip estimation , 2009, IEEE Control Systems.

[2]  Jon Rigelsford,et al.  Automotive Control Systems: For Engine, Driveline and Vehicle , 2004 .

[3]  Patrick Gruber,et al.  Comparison of Feedback Control Techniques for Torque-Vectoring Control of Fully Electric Vehicles , 2014, IEEE Transactions on Vehicular Technology.

[4]  Carlos Cardeira,et al.  Sideslip estimation of Formula Student prototype through GPS/INS fusion , 2017, 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

[5]  Carlos Silvestre,et al.  Geometric Approach to Strapdown Magnetometer Calibration in Sensor Frame , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Corina Sandu,et al.  Vehicle Dynamics: Theory and Applications , 2010 .

[7]  Reza N. Jazar,et al.  Vehicle Dynamics: Theory and Application , 2009 .

[8]  Yoichi Hori,et al.  Estimation of Sideslip and Roll Angles of Electric Vehicles Using Lateral Tire Force Sensors Through RLS and Kalman Filter Approaches , 2013, IEEE Transactions on Industrial Electronics.

[9]  Ali Charara,et al.  Onboard Real-Time Estimation of Vehicle Lateral Tire–Road Forces and Sideslip Angle , 2011, IEEE/ASME Transactions on Mechatronics.

[10]  Robert Grover Brown,et al.  Introduction to random signals and applied Kalman filtering : with MATLAB exercises and solutions , 1996 .

[11]  Kyongsu Yi,et al.  Design and evaluation of side slip angle-based vehicle stability control scheme on a virtual test track , 2006, IEEE Transactions on Control Systems Technology.

[12]  Carlos Cardeira,et al.  Application of Sideslip Estimation Architecture to a Formula Student Prototype , 2017, ROBOT.

[13]  David M. Bevly,et al.  Integrating INS Sensors With GPS Measurements for Continuous Estimation of Vehicle Sideslip, Roll, and Tire Cornering Stiffness , 2006, IEEE Transactions on Intelligent Transportation Systems.

[14]  Mujahid Abdulrahim,et al.  On the Dynamics of Automobile Drifting , 2006 .

[15]  Eric J. Rossetter,et al.  Vehicle Sideslip and Roll Parameter Estimation using GPS , 2002 .

[16]  Yoichi Hori,et al.  Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer , 2009, IEEE Transactions on Industrial Electronics.