System-Level Performance of Torque Vectoring Controllers for Electric Vehicles with In-Wheel Motors

Torque Vectoring (TV) is a critical control technology for enhancing the vehicle dynamics and stability of electric vehicles equipped with four-wheel-independent-drive (4WID) systems. A central challenge in TV design is managing the trade-off between maximizing handling performance and minimizing energy consumption, a crucial factor for EV range. While numerous advanced TV control strategies have been proposed, a comprehensive and comparative benchmark of foundational controllers evaluated on a platform that captures this trade-off is notably absent from the literature. Among the numerous TV control strategies proposed in literature, they are typically evaluated using simplified vehicle models that neglect the detailed dynamics and efficiency losses of the electric powertrain. This study addresses this gap by presenting a comprehensive comparison of six distinct TV control strategies—PID, LQR, two first-order Sliding Mode Controls (SMC), and two second-order SMCs. The controllers are evaluated on a high-fidelity, multi-domain simulation platform that integrates a detailed 14-DOF vehicle dynamics model with electro-thermal models of the motors and energy storage system. The findings reveal a clear, quantifiable trade-off between control precision and energy efficiency. The LQR and suboptimal SOSM controllers delivered superior yaw rate tracking and vehicle stability but incurred a measurable energy penalty. In contrast, the PID and continuous FOSM controllers provided a robust balance of performance and efficiency. More than an exercise on application of different control methods, this research highlights the necessity of using integrated simulation methodologies for the practical design and calibration of active chassis systems, ensuring that gains in dynamic performance do not come at an unacceptable cost to vehicle range and powertrain reliability.