Supplementary data for “Optimization-Based Tuning of a Hybrid UKF State Estimator with Tire Model Adaption for an All Wheel Drive Electric Vehicle”

Abstract

Training and test data for vehicle state estimator optimization and validation are included as MATLAB-files. The data was captured with the all-wheel drive electric vehicle “BugEE” of the Otto-von-Guericke-University Magdeburg and IKAM GmbH during different severe driving maneuvers on wet and dry road surfaces. Training data contains: Acceleration on wet road surface, slalom on wet road surface, steady state circular driving on dry road surface. Test data contains: Acceleration and emergency evasion on wet road surface, steady-state circular driving and slalom on dry road surface. Furthermore, results shown in “Optimization-Based Tuning of a Hybrid UKF State Estimator with Tire Model Adaption for an All Wheel Drive Electric Vehicle” are included.