Process forces arising during Friction Stir Welding (FSW) have become of interest to investigators interested in obtaining weld quality information from recorded weld data. Successful analysis of process forces require the separation of force signals stemming from material flow mechanisms within the weld from signals influenced by the FSW machine. Three modes of FSW control were characterized for system response: Servo Position (SPC), Electronic Deflection Compensation (EDC), and Constant Load Control (CLC). The gain value of the feedback loops associated with EDC and CLC modes were altered and characterized. SPC mode response to vertical changes in the tool position was also characterized. Machine-specific force signatures associated with the motor transmission assembly and spindle resonance were also identified. Characterization of the influence of machine control modes and other machinespecific frequencies on process force signals will allow future investigators to identify segments of welds during which machine actions influenced recorded force data.

United States government data shows AWD EV production increasing over 376 % from 2020 to 2023. The literature highlights energy savings from mixed-type dual EM powertrains and optimization-based energy management strategies (EMS), compared to single-type dual-motors and rule-based control. Other trends include the adoption of silicon carbide (SiC) based inverter devices and 800 V systems. Axial-flux machines have seen increased traction, with implementations in Ferrari’s SF90 Stradale, Lamborghini’s Revuelto, and Mercedes-Benz’s acquisition of YASA Ltd. These findings motivated the study of dual-motor AWD EV thermally constrained energy management. Using McMaster Automotive Resource Centre’s (MARC’s) facilities, accurate modeling of powertrain components was pursued to contribute realistic results. Firstly, inverter device materials and voltage ratings were studied in a Chevrolet Bolt EV model. Experimental validation was conducted on 1200 V inverters, powering 160+ kW traction machines. The model’s loss error was mostly within 100 W of measured loss. An empirical loss model revealed the analytical model estimates range within 6 km. This work highlighted the benefits of 800 V DC buses and SiC inverters. Secondly, experimental characterization of a yokeless and segmented armature (YASA) axial flux machine, by YASA Ltd., was documented. Dynamometer tests covered a wide torque, speed, and DC bus voltage range. The Bolt EV was modeled with the YASA machine, comparing its performance to the stock machine. All data was compiled and published in an online open-source repository. Lastly, thermally constrained energy management of various control strategies for a dual-motor AWD EV model were compared. Over two drive cycles, an MPC strategy ranked best in selected performance metrics. During a racetrack drive cycle, the MPC strategy kept the thermally limited motor cooler 246 % longer than a rule-based strategy. This work highlighted MPC’s potential in reducing total lifetime thermal wear of a dual-motor powertrain’s thermally limited motor. / Thesis / Doctor of Philosophy (PhD) / This thesis presents the experimental dynamometer work behind the accurate modeling of electric powertrain components, specifically the electric machine (EM) and inverter. The analytical inverter model is experimentally validated using electric machines as loads. The electric machine model is constructed from its experimental characterization data. Together, these models form a near-completely experimental-based electric drive unit (EDU). From this foundation, a dual-motor all-wheel-drive (AWD) electric vehicle (EV) model is built for the purpose of evaluating various control strategies’ thermally constrained energy management abilities. The control methods are ranked with respect to key performance indicators (KPIs) over the course of two drive cycles. Results from these drive cycles point to the model predictive control (MPC) strategy achieving the control objectives with the best quantified KPIs. Most importantly, it was able to keep the powertrain's thermally limited motor cooler 246 % longer than the second-best performing control strategy, a rule-based method applying a torque-split ratio algorithm.