Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis

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 the transient behavior of force so that an online methodology for capacity estimation is Lithium-ion (Li-ion) batteries have been one of the most popular choices for use as power sources in electric vehicles (EVs) and hybrid electric vehicles (HEVs). Their popularity stems from their high energy and power densities and their ability to achieve long driving ranges. However, their performance suffers from aging and degradation 1,29,33 that should be recognized and accounted for to achieve efficient long term performance. Thus significant research has been focused on trying to understand the aging mechanisms in Li-ion cells and connect them with measurable and identifiable features in an effort to improve the utilization and reliability of these cells through the battery management system (BMS). The power capability and capacity are both important factors used to determine the state of health (SOH). The SOH of a battery is usually quantified using either resistance growth 3,8,17,18,25,32 or capacity loss. 9,13,35,36 This paper focuses on the capacity fading dimension of SOH.Several methods haven been introduced in literature for the evaluation of the aging in battery. Traditional and conventional methods rely on voltage measurements. In Cyclic Voltammetry (CV), the electrode potential is ramped linearly versus time.12 And the resulting current is plotted vs voltage. Peaks in the CV indicate reactions and, a shift in their location is correlated with aging. The probability density function (PDF) method applies a histogram to the charge/discharge voltage data o...

Understanding Full-Cell Evolution and Non-chemical Electrode Crosstalk of Li-Ion Batteries

“…electrochemical resistances, [10][11][12][13][14][15][16] the size of the battery, [17][18][19][20][21][22] and the stresses within the battery. [23][24][25][26][27][28] While existing studies have provided useful information about the progression of battery properties during cycling, questions still remain as to the root cause of capacity variation as a function of operation. In addition, they often fail to address an important question associated with battery reliability: is it possible to detect early on when a battery will fail?…”

Hybrid nonlinear observer for battery state‐of‐charge estimation using nonmonotonic force measurements

“…Hence, if the bulk force can be measured, the SOC could potentially be estimated from it in real time. The use of bulk force measurements by some of the authors of this article and by others has been previously reported in References [4,[8][9][10][11][12][13]. Model development and validation can be seen in References [12][13][14].…”

Material Characterization and Analysis on the Effect of Vibration and Nail Penetration on Lithium Ion Battery

“…Apart from material and electrochemical behavioural study, in recent times, various researchers have started to use mechanical behavior as an indicator of cell status [30][31][32]. Hooper et al claimed that the natural frequency of a li-ion cell is independent of its state of charge (SoC), but frequency information of the same cells with various SoCs was not investigated in his work [33].…”