Nonlinear Optimal Control of a Power-Split Hybrid Electric Vehicle with Electrochemical Battery Model

Paper #:
  • 2017-01-1252

Published:
  • 2017-03-28
Abstract:
This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model of Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model has been replaced by a single particle electrochemical lithium ion battery model with battery thermal aging features. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller. This study provides a sound basis for the further study of NMPC for the HEVs with the consideration of battery aging and thermal performance.
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