Intelligent traction motor control techniques for hybrid and electric vehicles

Cash, Scott ORCID: https://orcid.org/0000-0002-3905-2065 (2019). Intelligent traction motor control techniques for hybrid and electric vehicles. University of Birmingham. Ph.D.

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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.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):