Energy efficient torque allocation strategy for all-wheel drive battery electric vehicle

The increasing interest in fully electric vehicles (FEVs) is driven by concerns about the availability and long-term viability of fossil fuels as well as the potential environmental benefits of electric vehicles. Electric vehicles offer several advantages over traditional internal combustion engine vehicles, including reduced greenhouse gas emissions, lower operational costs, and improved energy efficiency. A significant factor driving the shift towards FEVs is the global effort to reduce carbon emissions and combat climate change. Governments and organizations worldwide have set ambitious targets to decrease reliance on fossil fuels and promote cleaner energy sources. The transportation sector, being one of the largest contributors to greenhouse gas emissions, plays a crucial role in this transition. This thesis investigates an energy-efficient torque allocation strategy for all-wheel-drive battery electric vehicles. The study focuses on reducing power losses arising from both the powertrain and tire slip while optimizing vehicle dynamics to enhance performance. The proposed strategy employs advanced control techniques within a low-level allocator that ensures computational feasibility for real-time implementation on a Vehicle Control Unit (VCU). The research methodology includes a comprehensive case study involving a high-performance sport utility vehicle (SUV) equipped with four in-wheel electric motors, utilizing a dual-track vehicle model to simulate dynamic behavior and control scenarios. The torque vectoring control system integrates a high-level controller, which includes an Adaptive Linear Quadratic Regulator (A-LQR) and a model-based feedforward controller, with a low-level torque allocator. This integrated approach aims to enhance vehicle handling, stability, and energy efficiency by controlling the yaw moment generated by the four e-motors and selecting optimal torque distribution. The control system's performance is evaluated through co-simulation environments using CarSim and Simulink, enabling detailed vehicle dynamics modeling and control system development under various driving conditions. Results from standard maneuvers, including Double Lane Change (DLC) and Slow Ramp Steer (SRS) tests, demonstrate the allocator's effectiveness in improving both vehicle dynamics and energy efficiency. The TV controller shows significant improvements in tracking reference yaw rates, sideslip angles, and faster response times in corners, along with reduced Normalized Root Mean Square Error (NRMSE) in vehicle trajectory tracking. Additionally, the implementation of the eco allocator results in notable reductions in total energy losses during both DLC and SRS maneuvers, validating its potential to optimize energy consumption and extend vehicle range. Overall, this research underscores the importance of advanced control strategies in enhancing the performance and sustainability of electric vehicles. The proposed torque allocation strategy not only optimizes power usage and reduces energy consumption but also contributes to safer and more efficient vehicle handling, aligning with global efforts to promote sustainable and eco-friendly transportation solutions.