Computationally Efficient Nonlinear Model Predictive Controller for Energy Management of Tracked Hybrid Electric Vehicles

Abstract

This paper proposes a computationally efficient energy management strategy of tracked hybrid electric vehicles (THEV) based on nonlinear model predictive control (NMPC). First, the powertrain of THEV is introduced in detailed. Then, the model predictive control problem is illustrated with series of constraints. To improve the computational efficiency in NMPC controller, a nonlinear programming method, continuation/ generalized minimum residual (C/GMRES) algorithm is adopted. Finally, numerical simulation validations are conducted and the in-depth analysis is also demonstrated, which yields the superior computational efficacy and control performance of the proposed strategy.