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Batteries are crucial to our transition to clean energy and mobility. They are also one of the most expensive components in the products we rely on, such as electric vehicles (EVs) and energy storage systems that balance our electricity grids. Given their critical importance and high cost, it’s a priority for many transportation and energy service providers to ensure the longevity and optimal performance of their batteries. By better understanding battery aging we can learn how to prolong the lifespan of batteries, making them more sustainable, cost-effective, and profitable.
This article will explain aging in lithium-ion batteries, which are the dominant battery type worldwide with a market share of over 90 percent for battery energy stationary storage (BESS) and 100 percent for the battery electric vehicle (BEV) industry.1, 2 Other battery types such as lead-acid chemistries age very differently.
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This article will introduce many new terms around lithium-ion battery aging. Because not everyone is a battery expert, let me explain a few foundational terms to help us ease into the subject of battery aging:
Battery aging is very complex, non-linear and influenced by many parameters. It can be observed for example, that batteries age even if they are not used. But, in general, batteries age faster if they are used. To manage the complexity, it is common practice to split aging into three buckets: calendric, cyclic, and reversible aging:
When batteries age, different aging mechanisms take place simultaneously. Each aging mechanism has an impact on the behavior of the battery. The impact can be broken down into two performance parameters: capacity and internal resistance.
Batteries lose capacity when they age. For an electric vehicle, losing capacity means the EV cannot drive as far as it used to without stopping for a recharge. And for stationary energy storage, it means the battery can store less energy and thus generate less revenue. How fast the capacity decreases depends on a number of factors including the type of battery, the charging and discharge rates, the temperatures it is exposed to, and the number of cycles it has undergone.
Looking at the aging of a lithium-ion battery, the aging trend can roughly be split into three phases, as illustrated in Figure 1:
In contrast to capacity loss, the internal resistance of a battery increases over time, which conversely leads to power reduction. This is especially relevant for hybrid electric vehicles (HEV). Increasing internal resistance in an HEV means you cannot accelerate as fast as before and they reclaim less energy from braking. For stationary storage operators this means reduced efficiency and power capability.
The main cause of aging in lithium-ion batteries is the growth of the Surface Electrolyte Interphase (SEI). The SEI layer forms on the negative electrode during the first charging cycle, commonly referred to as the formation cycle. The SEI gets thicker over time and is mainly influenced by the electrolyte chemistry and mechanical stress of active materials. The SEI is typically formed on the anode, which is mostly made of graphite, sometimes mixed with silicon.
As the Surface Electrolyte Interphase grows it binds Lithium. Subsequently, less lithium-ions participate in the charging and discharging reactions and the battery capacity decreases. The lithium-ions also pass through the SEI layer when the battery is charged and discharged. The thicker the SEI, the harder it is for the ions to move through it. This is why internal resistance increases: the SEI grows as the battery ages.
In addition to the SEI growth there are numerous additional processes such as cracking and corrosion that influence battery aging, but we will cover those in a different article.
The main drivers of calendric aging are temperature and state of charge (SOC). Overall, at higher temperatures and SOCs batteries age faster. An average decrease of 10°C or 50°F can double a battery’s lifespan as illustrated in Figure 2. However, remember not to operate your batteries at too low temperatures because of lithium plaiting.
With higher SOCs – especially above 90 percent – battery aging increases rapidly as illustrated in Figure 3.3, 4, 5
Cyclic aging is dominated by the energy throughput – the amount of energy that moves through the battery in a specific period of time – so the number of cycles plays a key role. However, small cycles are less harmful than big ones, as shown in Figure 4 (below). For example, three cycles with 20% depth of discharge (DOD) are less harmful compared to one cycle with 60% DOD, even though the total energy throughput is the same. This means the battery can sustain more cycles if the depth of discharge remains within a limited range.
Additionally, the charging power influences the cyclic lifespan. A higher charging power or “fast charging” leads to increased aging. One reason is that charging a battery with high power raises the temperature, which leads to accelerated aging. Another reason is the increased risk of lithium plating.
Besides temperature, charging power, throughput, and depth of discharge, other effects such as phase shifts also accelerate battery aging. To get deeper insights ask-a-battery-expert[at]ACCURE.net 😉
Using the insights about aging effects described above, intelligent operation strategies can be developed to easily prolong battery lifetime. Below are some recommendations for different applications. But the most important thing to remember is to only operate batteries within the given supplier boundaries. For example, do not charge batteries at temperatures that are too cold or too hot.
It is especially important to operate electric vehicles in a lifetime-friendly way because one-third to half of the price of the EV is for the battery. Do not fully charge the battery directly after coming home when only a small part of the full range was driven. Keeping the battery fully charged accelerates aging so much that many car manufacturers require users to manually agree to charge the battery to 100 percent.
Some apps for electric vehicles offer smart features where the user enters the time when they need the car to be charged to avoid high SOCs for prolonged periods of time. For example, the user needs to get to work at 7 AM, then the car will start charging at 4am even if the car is plugged in earlier.
Finally, it’s recommended to only fast-charge the EV when needed. Fast charging uses high currents, which can result in high temperatures. Both are very costly in terms of aging.
In the utility-scale storage sector battery aging is often overlooked. Most large-scale storage systems operate with software lacking functionality that comprehensively takes battery aging into account. For example, the software is designed to optimize the income generated but neglects the degradation costs of market participation.
To optimize the total cost of ownership (TCO) of utility-scale storage systems the degradation costs of different cycles must be factored in. With a digital twin, the costs of each cycle can be tracked and consolidated across systems to compare. With knowledge of both revenue and costs of market participation, the overall operation can be optimized to get the maximum total value of the asset.
Private households with rooftop photovoltaic (PV) systems use home battery energy storage systems to increase the self-consumption of power. These battery systems cost thousands and are increasingly in demand. Last year in the United States the residential storage market had two record quarters of 375 (Q2) and 400 (Q4) MWh installed.6 In Germany alone there’s an estimated 700,000 individual home storage systems.7
Most days, home battery systems store more energy than is consumed. As a result, the storage systems are cycled at high SOC ranges of 50 to 100 percent, which causes increased aging. To reduce the aging, system settings should delay charging the batteries until later in the day. This way the batteries spend less time overall at higher states of charge.
Additionally, predictive battery analytics can calculate a maximum needed SOC based on actual usage behavior over time. With this information, the system can be set to maintain the user-specific SOC to considerably reduce the average state of charge and prolong the lifetime.
One common mistake is keeping lithium-ion batteries fully charged most of the time. Here are recommendations to adjust the charging routine to extend the battery life and increase safety:
The New York City Fire Department has a helpful overview of safety tips for charging lithium-ion devices here.
How batteries are used and the conditions they operate under have a significant impact on aging. This means businesses that control operations and maintenance can prolong the battery lifetime with simple but intelligent adjustments. Every battery ages differently, which is why we recommend a battery business intelligence solution that analyzes operation data to help determine the safest and most profitable operating strategy for your specific situation. There is much more you can do to prolong the lifetime of batteries when you turn data into actions.
1 Amrita Dasgupta, Max Schoenfisch. Grid-Scale Storage Infrastructure deep dive, International Energy Association. Date of last revision: September 2022. Date retrieved: 8 March 2023 [https://www.iea.org/reports/grid-scale-storage]
2 Martin Placek. Metals & Electronics › Electronics, Different types of EV batteries' market share worldwide 2020-2050, statista. Date of last revision: 6 January 2023. Date retrieved: 8 March 2023 [https://www.statista.com/statistics/1248519/distribution-of-different-electric-vehicle-batteries-on-the-global-market/]
3 Peter Keil et al 2016. Calendar Aging of Lithium-Ion Batteries, Journal of The Electrochemical Society, Soc.163 A1872. Date retrieved: 3 April 2023 [https://iopscience.iop.org/article/10.1149/2.0411609jes]
4 Madeleine Ecker et al 2014. Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries, Journal of Power Sources, Volume 248, Pages 839-851, ISSN 0378-7753. Date retrieved: 3 April 2023 [https://doi.org/10.1016/j.jpowsour.2013.09.143]
5 Georg Angenendt, Hendrik Axelsen, Sebastian Zurmühlen, 2018. PV Home Storage System (PV-HOST) Betriebsstrategien und Systemkonfigurationen für Batteriespeicher für Einfamilienhäuser mit Photovoltaikanlagen" : Bericht zum Teilvorhaben der RWTH Aachen : Abschlussbericht (German), ISEA, RWTH Aachen University. Date retrieved: 3 April 2023 [https://www.tib.eu/en/suchen/id/TIBKAT:1016723725/]
6 Q3 U.S. grid-scale energy storage market sets new record, Wood Mackenzie. Date of last revision: 15 December 2022. Date retrieved: 08 March 2023 [https://www.woodmac.com/press-releases/q3-us-grid-scale-energy-storage-market-sets-new-record/]
7 Sandra Enkhardt. 500.000 Photovoltaik-Heimspeicher mittlerweile in Deutschland installiert, PV Magazine. Date of last revision: 6 April 2022. Date retrieved: 8 March 2023 [https://www.pv-magazine.de/2022/04/06/500-000-photovoltaik-heimspeicher-mittlerweile-in-deutschland-installiert/]
Dr. Georg Angenendt is a scientist and entrepreneur with expertise in mobility and utility-scale battery energy storage systems (BESS). His research on testing, modeling, commissioning, and optimization of battery storage systems has been published in international journals and at conferences. Since 2020, he is the Chief Technology Officer at ACCURE Battery Intelligence, developing advanced analytics software to help companies assess battery risk, ensure safety, and maximize asset value. His personal passion is Martial Arts: mixed martial arts, luta livre, grappling, boxing and Brazilian jiu-jitsu.