Non-symmetric charge sustaining strategy for supervisory predictive control of batteries in hybrid electric vehicles

Abstract

A non-symmetric charge sustaining strategy (CSS) for regulating the battery system in a bi-modal hybrid electric vehicle (HEV) is presented in this paper. The non-symmetric penalty on the deviation on the battery's state-of-charge (SOC) is implemented as a soft constraint in the performance index (PI) at the supervisory level. The PI in concert with other HEV dynamical equations and operational constraints are used to formulate the power flow control problem. Due to several numerical advantages, the problem is formulated as the model predictive version as opposed to the complete time horizon problem. Further, the embedded optimal version of the problem allows for faster computation for the solution. The numerical solution is found via a sequential quadratic programming based subroutine. In this study, the controller for a parallel HEV is to track the standard (United States) HWFET, or so called the EPA highway driving velocity profile. The driving profile is also modulated with a sinusoidal road grade, putting more aggressive demand on the HEV's contoller. The performances of the optimal controllers developed via the non-symmetric and a traditional symmetric CSS are compared. The simulation results show that the optimal controller developed via the non-symmetric strategy is superior to the traditional symmetric one in regulating the battery's SOC in this case study. Hence, the strategy can be used to improve the battery management system in a HEV.