Hierarchical NMPC for energy-efficient torque vectoring in four in-wheel motor electric vehicles

Abstract

This paper presents a hierarchical torque vectoring (TV) framework that integrates vehicle dynamics enhancement and energy efficiency improvement using nonlinear model predictive control (NMPC) for four in-wheel motor electric vehicles (4WMEVs). TV systems offer significant potential for enhancing both handling performance and energy economy by optimally distributing torque among the wheels. However, effectively balancing these two objectives remains a critical challenge. To address this, we propose a simplified hierarchical control structure that simultaneously improves handling performance and reduces energy consumption. The top-layer controller computes the desired longitudinal tire forces to generate accurate yaw moments, enhancing handling performance. The bottom-layer controller ensures energy-optimal torque allocation while preserving the control objectives of the top-layer. Simulation results demonstrate that the proposed strategy achieves a 11.27% reduction in energy consumption without compromising handling performance.