Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis. Issue 8 (27th May 2016)
- Record Type:
- Journal Article
- Title:
- Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis. Issue 8 (27th May 2016)
- Main Title:
- Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis
- Authors:
- Samad, Nassim A.
Kim, Youngki
Siegel, Jason B.
Stefanopoulou, Anna G. - Abstract:
- Abstract : Traditionally health monitoring techniques in lithium-ion batteries rely on voltage and current measurements. A novel method of using a mechanical rather than electrical signal in the incremental capacity analysis (ICA) method is introduced in this paper. This method derives the incremental capacity curves based on measured force (ICF) instead of voltage (ICV). The force is measured on the surface of a cell under compression in a fixture that replicates a battery pack assembly and preloading. The analysis is performed on data collected from cycling encased prismatic Lithium-ion Nickel-Manganese-Cobalt Oxide (NMC) cells. For the NMC chemistry, the ICF method can complement or replace the ICV method for the following reasons. The identified ICV peaks are centered around 40% of state of charge (SOC) while the peaks of the ICF method are centered around 70% of SOC indicating that the ICF can be used more often because it is more likely that an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV) will traverse the 70% SOC range than the 40% SOC. In addition the Signal to Noise ratio (SNR) of the force signal is four times larger than the voltage signal using laboratory grade sensors. The proposed ICF method is shown to achieve 0.42% accuracy in capacity estimation during a low C-rate constant current discharge. Future work will investigate the application of the capacity estimation technique under charging and operation under high C-rates by addressing theAbstract : Traditionally health monitoring techniques in lithium-ion batteries rely on voltage and current measurements. A novel method of using a mechanical rather than electrical signal in the incremental capacity analysis (ICA) method is introduced in this paper. This method derives the incremental capacity curves based on measured force (ICF) instead of voltage (ICV). The force is measured on the surface of a cell under compression in a fixture that replicates a battery pack assembly and preloading. The analysis is performed on data collected from cycling encased prismatic Lithium-ion Nickel-Manganese-Cobalt Oxide (NMC) cells. For the NMC chemistry, the ICF method can complement or replace the ICV method for the following reasons. The identified ICV peaks are centered around 40% of state of charge (SOC) while the peaks of the ICF method are centered around 70% of SOC indicating that the ICF can be used more often because it is more likely that an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV) will traverse the 70% SOC range than the 40% SOC. In addition the Signal to Noise ratio (SNR) of the force signal is four times larger than the voltage signal using laboratory grade sensors. The proposed ICF method is shown to achieve 0.42% accuracy in capacity estimation during a low C-rate constant current discharge. Future work will investigate the application of the capacity estimation technique under charging and operation under high C-rates by addressing the transient behavior of force so that an online methodology for capacity estimation is developed. … (more)
- Is Part Of:
- Journal of the Electrochemical Society. Volume 163:Issue 8(2016)
- Journal:
- Journal of the Electrochemical Society
- Issue:
- Volume 163:Issue 8(2016)
- Issue Display:
- Volume 163, Issue 8 (2016)
- Year:
- 2016
- Volume:
- 163
- Issue:
- 8
- Issue Sort Value:
- 2016-0163-0008-0000
- Page Start:
- A1584
- Page End:
- A1594
- Publication Date:
- 2016-05-27
- Subjects:
- Capacity estimation -- Force -- Incremental capacity analysis -- State of health -- Stress
Electrochemistry -- Periodicals
541.3705 - Journal URLs:
- https://iopscience.iop.org/journal/1945-7111?gclid=EAIaIQobChMI4Y-UmqGC7wIVFeDtCh0VQAo7EAAYASAAEgLW8_D_BwE ↗
- DOI:
- 10.1149/2.0511608jes ↗
- Languages:
- English
- ISSNs:
- 0013-4651
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 15515.xml