Indirect State-of-Health Estimation for Lithium-Ion Batteries under Randomized Use

Abstract

Lithium-ion batteries are widely used in many systems. Because they provide a power source to the whole system, their state-of-health (SOH) is very important for a system's proper operation. A direct way to estimate the SOH is through the measurement of the battery's capacity; however, this measurement during the battery's operation is not that easy in practice. Moreover, the battery is always running under randomized loading conditions, which makes the SOH estimation even more difficult. Therefore, this paper proposes an indirect SOH estimation method that relies on indirect health indicators (HIs) that can be measured easily during the battery's operation. These indicators are extracted from the battery's voltage and current and the number of cycles the battery has been through, which are far easier to measure than the battery's capacity. An empirical model based on an elastic net is developed to build the quantitative relationship between the SOH and these indirect HIs, considering the possible multi-collinearity between these HIs. To further improve the accuracy of SOH estimation, we introduce a particle filter to automatically update the model when capacity data are obtained occasionally. We use a real dataset to demonstrate our proposed method, showing quite a good performance of the SOH estimation. The results of the SOH estimation in the experiment are quite satisfactory, which indicates that the method is effective and accurate enough to be used in real practice.

Critical Review of Ageing Mechanisms and State of Health Estimation Methods for Battery Performance

“…Ageing causes the battery to lose its capacity and increase its internal resistance. Jinsong Yu et al [32], define the battery internal resistance based on changes in the voltage curve while applying a discharge current, and by using Ohm's law, the internal resistance can be approximated as follow:…”

A State of Health Estimation Method for Lithium-Ion Batteries Based on Voltage Relaxation Model

“…Therefore, the key step of a SOH estimation method is to accurately obtain the SOH evaluation parameter of the battery. Considering that the main behavior of the aging phenomenon of a lithium-ion battery is the attenuation of energy and power performance, most of the SOH estimation methods select the decrease of capacity [7][8][9][10][11][12][13][14][15][16] and/or the increase of impedance [17][18][19][20][21][22][23][24] as the evaluation parameter.…”

“…The indirect group of methods is based on the relationship of the capacity and several characteristics of the battery. It utilizes the obtained value of the characteristics and estimates the capacity indirectly [13][14][15][16]. Typically, the terminal voltage curve of the battery during charging or discharging is used.…”

Incremental Capacity Analysis on Commercial Lithium-Ion Batteries Using Support Vector Regression: A Parametric Study

“…The SOH is 'a state' that reflects the aging condition in comparison with Energies 2018, 11, 2323 2 of 21 a fresh battery. The quantitative definition of SOH can be founded on the battery capacity [10,11] or the impedance [12][13][14]. The SOH monitoring is regarded as one of the key problems for battery management, because the SOH affects the accurate estimation of battery states, thereby determining the capability of power output of the battery system [15][16][17].…”