Experimental verification of an online traction parameter identification method

Traction parameters, that characterize the ground-wheel contact dynamics, are central factor in energy efficiency of vehicles. To optimize fuel consumption, reduce wear tires, increase productivity etc., knowledge current traction parameters is unavoidable. Unfortunately, these difficult to measure and require expensive force torque sensors. An alternative way use system identification determine them. In this work, we validate such a method field experiments with mobile robot. The based on an adaptive Kalman filter. We show how it estimates online, during motion field, compare them their values determined via 6-directional force-torque sensor installed for verification. Data adhesion slip ratio curves recorded compared from literature additional validation method. results can establish foundation number optimal methods.