Advanced finite control set model predictive control with multi-step horizon for electric towing vehicles in airport...

Electric towing vehicles (ETVs) are increasingly deployed in airport environments to replace diesel tractors and reduce emissions. However, they must balance conflicting requirements: torque accuracy, energy efficiency, and strict compliance with hardware constraints (current, voltage, state of charge). This paper presents a new advanced predictive control strategies based on a Multi-Step Finite Control Set (FCS-MPC) for three-phase induction motor drives in ERVs, specifically designed to address these challenges. The method leverages a complete dynamic model of the traction system, including the asynchronous motor, the battery model, and the mechanics of the actual commercially available tractor. The controller evaluates eight inverter commutation vectors over a three-step horizon (N = 3) at a sampling frequency of 10 kHz, optimizing a multi-objective cost function subject to current, voltage, torque, and state-of-charge (SOC) constraints. The proposed control strategy was first evaluated through simulations in the MATLAB/Simulink environment using two typical speed profiles that represent realistic operating conditions. It was then implemented in real-time on a dSPACEDS1104 platform, with automatic code generation via Simulink Coder and RTI, and experimentally validated on a full hardware-in-the-loop configuration. The results demonstrate fast torque and speed tracking (settling time < 150 ms, steady-state error < 2%), a state of charge maintained between 25% and 75% and a system efficiency of 92%, a 7% improvement over a conventional PI controller. The proposed MS-FCS-MPC provides a robust and energy-efficient solution for real ETV applications.