State-of-Health Estimation of Li-ion Batteries: Ageing Models
Doctoral thesis, 2014

Significant research efforts are being made to understand, and ultimately mitigate, the degradation of Li-ion batteries upon usage. Currently, battery ageing models are used in order to optimise the battery usage and to achieve robust battery solutions. The purpose with this work is to obtain deeper understanding of the ageing factors for high-power graphite || LiFePO4 cells and to develop a semi-empirical ageing model suitable for use in the full-vehicle simulations. Extensive laboratory tests of commercially available graphite || LiFePO4 cells were conducted with special focus on high charge and discharge rates at temperatures between +23 °C and +53 °C. Furthermore, cells were aged according to measured and simulated load profiles from heavy-duty HEVs and PHEVs. The results were analysed using ex situ techniques such as incremental analysis and fitted towards half-cells voltage profiles. Specifically, ageing tests with 4 C-rate charge rate in combination with 1 C-rate discharge, and cycles with pauses between steps, were found to degrade the cells significantly faster than cycles with 4 C-rate in both charge and discharge. This behaviour was also observed for the PHEV cycles with charging at 4 C-rate. In addition, post mortem analyses were performed on selected cells, both on electrodes and electrolytes, suggesting that the electrode degradation is unevenly distributed. A segmented 1D semi-empirical lumped-circuit cell model was designed and coupled to a state-of-health ageing algorithm based on the test results. This model was subsequently used to forecast ageing rates and showed promising results for HEV load cycles, indicating that the cell degradation is unevenly distributed with the most severe ageing occurring close to the separator. In contrast, the model could not forecast the ageing accurately for some specific cases with high charge rates combined with low discharge rates, indicating that additional ageing mechanisms must be included to model the ageing at such severe load conditions.

State-of-health

lithium-ion battery

EV

PHEV

cycle life test

impedance spectroscopy

DVA

battery testing

ICA

battery model

HEV

Division of Electric Power Engineering, Chalmers University of Technology, Room EB
Opponent: Dr. Simona Onori, Clemson University, USA

Author

Jens Groot

Chalmers, Energy and Environment, Electric Power Engineering

Battery Benchmarking and Cyclelife Test Methods

Transport Research Arena Europe 2010, Brussels, 2010-06-07...2010-06-10,;(2010)

Paper in proceeding

Impact of Periodic Current Pulses on Li-Ion Battery Performance

IEEE Transactions on Industrial Electronics,;Vol. 59(2012)p. 3481-3488

Journal article

Statistic Method for Extraction of Synthetic Load Cycles

24th International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition 2009, EVS 24; Stavanger; Norway; 13 May 2009 through 16 May 2009,;Vol. 2(2009)p. 1336-1343

Paper in proceeding

Driving Forces

Sustainable development

Areas of Advance

Transport

Energy

Subject Categories

Other Electrical Engineering, Electronic Engineering, Information Engineering

ISBN

978-91-7597-134-6

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 3815

Division of Electric Power Engineering, Chalmers University of Technology, Room EB

Opponent: Dr. Simona Onori, Clemson University, USA

More information

Created

10/7/2017