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

Paper #:
  • 2017-01-1252

Published:
  • 2017-03-28
Citation:
Cheng, M., Feng, L., and Chen, B., "Nonlinear Model Predictive Control of a Power-Split Hybrid Electric Vehicle with Electrochemical Battery Model," SAE Technical Paper 2017-01-1252, 2017, https://doi.org/10.4271/2017-01-1252.
Pages:
9
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 from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. 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 stochastic MPC and NMPC for the HEV power management with the consideration of battery aging and thermal performance.
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