Computationally Efficient Li-Ion Battery Aging Model for Hybrid Electric Vehicle Supervisory Control Optimization

Paper #:
  • 2017-01-0274

Published:
  • 2017-03-28
Affiliated:
Abstract:
This paper presents the development of an electrochemical aging model of LiFePO4-Graphite battery. It is designed for power management optimization of heavy-duty hybrid electric trucks. The model enables to assess the battery aging rate by considering instantaneous lithium ion surface concentration rather than average concentration, and an approximate analytical method is used to speed up calculations while preserving required accuracy. The side reaction of electrolyte decomposition is considered as the main aging mechanism. First, the side reaction rate is built based on a single particle (SP) model. Next the particle differential equations of solid-phase lithium ion diffusion is solved by approximate analytical solution. The SP model with analytical solutions is compared with two models, namely SP model with finite difference method (FDM) and equivalent circuit model (ECM). The current profile from the simulation of series HEV under Urban Assault driving cycle is used as input. Comparing with FDM, analytical solution reduced the number of state from 86 to 7, while reserves the prediction accuracy. Comparing with the equivalent circuit model, the prediction accuracy increases by 11% under high c-rate while with slightly penalty on computation load. Improved computation speed and prediction accuracy makes this model a promising candidate for supervisory control optimization and system-level analysis of series HEV with aggressive driving missions.
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