Intelligent traction motor control techniques for hybrid and electric vehicles

Abstract

This thesis presents the research undertaken by the author within the field of intelligent traction motor control for Hybrid Electric Vehicle (HEV) and Electric Vehicle (EV) applications. A robust Fuzzy Logic (FL) based traction motor field-orientated control scheme is developed which can control multiple motor topologies and HEV/EV powertrain architectures without the need for re-tuning. This control scheme can aid in the development of an HEV/EV and for continuous control of the traction motor/s in the final production vehicle. An overcurrent-tolerant traction motor sizing strategy is developed to gauge if a prospective motor’s torque and thermal characteristics can fulfil a vehicle’s target dynamic and electrical objectives during the early development stages of an HEV/EV. An industrial case study is presented. An on-line reduced switching multilevel inverter control scheme is investigated which increases the inverter’s efficiency while maintaining acceptable levels of output waveform harmonic distortion. A FL based vehicle stability control system is developed that improves the controllability and stability of an HEV/EV during an emergency braking manoeuvre. This system requires minimal vehicle parameters to be used within the control system, is insensitive to variable vehicle parameters and can be tuned to meet a vehicle’s target dynamic objectives

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