Extending Battery Usage Time of a Heavy‐Duty Mecanum‐Wheeled Autonomous Electric Vehicle Used in Iron–Steel Industry by Considering Wheel Slippage

Abstract

Mecanum‐wheeled autonomous electric vehicles are preferred to use in industrial applications to carry loads. To be able to reach a maximum travel distance in one turn of work with a full battery charge, the vehicle should follow the reference route with minimum tracking errors. One of the reasons which prevents a good path tracking is the slippage because slippage causes tracking errors in both longitudinal and lateral directions. Herein, a modeling structure for a mecanum‐wheeled autonomous electric vehicle used for the heavy duties in iron–steel industry is proposed by taking the slippage information into account. The objective is to reach more travel distance and reduce the energy loss of the battery which causes to carry load less than planned. The modeling structure proposed is adapted and tested for an autonomous path tracking task in a galvanization line of an iron–steel industry. Five tons of zinc ingots are carried from the storage area to the melting pot using an autonomous electric vehicle in a predefined reference route. More than 5 km autonomous drive is performed and the experiments show that slippage causes an energy loss of 6.1786%, which means battery allows 6.1786% less distance than planned travel.