Efficient Optimization-Based Control of a Fuel Cell Hybrid Electric Vehicle with Torque Vectoring

Abstract

This paper proposes a practical strategy to easily take advantage of both torque allocation and power split toward low hydrogen consumption and component degradation for multi-motor hydrogen hybrid electric vehicles. Sigmoid-shaped functions are identified from optimal torque allocation maps using torque vectoring to reduce tire losses. A predictive rule-based power split controller is derived from optimal control, only necessitating an estimate of the cycle power distribution. The proposed method is analyzed and compared to the strategies of other participants of the 2023 IEEE VTS Motor Vehicles Challenge, revealing that despite its simplicity, the proposed strategy is robust and efficient.