This study describes the development of the Propulsion Supervisory Controller for an independent axle All-Wheel Drive Electric Vehicle, using a model-based approach. The vehicle has a main rear motor and a smaller front motor. Features like power moding, transmission range selection and torque architecture are discussed. For the torque architecture, different torque distribution strategies are explored in detail. Initially, a comparison of torque distribution strategies considering positive torques only, is used to assess the impact on the vehicle's energy consumption. Firstly, an optimal strategy with and without power-rate penalties is explored, which distributes the torque request to minimize the losses in both drive-units. Secondly, a fixed-ratio strategy is considered where both axles contribute with a predetermined torque ratio to meet the total torque demand. Thirdly, a torque-assist approach is examined, wherein only the rear motor contributes to the torque demand till it is operating at instantaneous maximum torque, after which the front motor starts contributing. Similar evaluations are then performed including regenerative braking or negative torque domain. Additionally, the performance of the penalized optimal strategy (PO) for positive torques is evaluated when combined with the torque assist regenerative braking strategy, where the front motor is primarily used for regenerative braking. The performance of PO combined with the ideal regenerative braking strategy is also assessed. This study aims to provide an overview of the controller development approach and an insight of the feasibility of deploying sophisticated computational algorithms for enhanced efficiency on it. / Master of Science / This study focuses on the development of a propulsion controller for a modified all-electric 2023 Cadillac LYRIQ. The Sport Utility Vehicle (SUV) is equipped with a main rear motor and a smaller front motor. Functional features such as the power-up and power-down sequence and vehicle range selection are discussed along with performance features like torque control. The objective is to enable safe vehicle functionality and enhance the vehicle's powertrain efficiency through the development of software for its Propulsion Supervisory Controller (PSC). The study initially evaluates various strategies for distributing torque during forward acceleration. Three primary strategies are analyzed: an optimal approach aimed at minimizing overall energy losses, a fixed-ratio strategy where torque ratios are predetermined to meet the total demand, and a torque-assist method where the front motor provides torque only after the rear motor reaches its instantaneous maximum torque, triggered by the accelerator pedal input exceeding a threshold. Similarly, these strategies are examined within the context of regenerative braking to assess their impact on range. Finally, the penalized optimal torque distribution strategy is combined with a torque assist regenerative braking strategy as well as a strategy that adheres to the ideal braking distribution. This study provides an overview of the vehicle controller development and demonstrates the feasibility and benefits of employing advanced computational algorithms in the propulsion controller to achieve enhanced efficiency and an improved range in electric vehicles.