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Title: Intelligent traction motor control techniques for hybrid and electric vehicles
Author: Cash, Scott
ISNI:       0000 0004 7972 6858
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2019
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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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TJ Mechanical engineering and machinery ; TK Electrical engineering. Electronics Nuclear engineering ; TL Motor vehicles. Aeronautics. Astronautics