Calendar Ageing

Calendar ageing, which refers to the capacity loss that lithium-ion batteries experience over time while in storage, is primarily measured by observing the capacity loss as a function of time under various storage conditions.

 

"Calendar ageing is a type of ageing that occurs in lithium-ion batteries over time, regardless of whether they are being used or not. It is caused by the gradual degradation of the battery's materials due to chemical reactions that occur over time. This type of ageing is different from cycle ageing, which occurs as a result of the battery being charged and discharged repeatedly."

 

How Does Calendar Ageing Occur?

Several factors contribute to calendar ageing:

• Chemical reactions: Spontaneous reactions within the cell, leading to material degradation.
• Temperature: Elevated temperatures accelerate ageing.
• Storage conditions: Improper storage, such as high temperatures or state of charge, exacerbates ageing.

Consequences of Calendar Ageing

• Capacity loss: Reduced energy storage capacity.
• Voltage drop: Decreased cell voltage.
• Increased internal resistance: Reduced efficiency.

Mitigating Calendar Ageing

• Optimal storage: Store cells at recommended temperatures (15°C - 20°C) and state of charge (40% - 60%).
• Regular maintenance: Monitor and balance cell voltages.
• Advanced materials: Research focuses on developing more resilient materials.

Conclusion

Calendar ageing is an inherent aspect of lithium-ion cells, but understanding its causes and consequences empowers us to take action. By adopting proper storage and maintenance practices, we can slow down calendar ageing and maximize the lifespan of these crucial energy storage devices. As we continue to innovate and improve lithium-ion technology, a sustainable energy future becomes increasingly within reach.

How does it is measured?

It can be measured by monitoring changes in the capacity and resistance over time. One common method of measuring calendar ageing is to charge the battery to a certain level, keep it idle for certain amount of time, and then measure its capacity and internal resistance. Another method of measuring calendar ageing is to use electrochemical impedance spectroscopy (EIS), which involves applying a small AC voltage to the battery and measuring the resulting AC current over a range of frequencies. The impedance can then be calculated from the measurements, and changes in impedance over time can indicate changes in the battery's internal resistance and other properties. Measuring calendar ageing can be challenging, as it is a complex process that depends on many factors, such as temperature, state of charge, and the specific chemistry of the battery's materials. Additionally, accurate measurements require specialized equipment and expertise.

Experimental Design: To accurately measure calendar ageing, researchers design experiments that involve storing the batteries under controlled conditions for a specific duration. These experiments typically involve:

• Multiple Storage Temperatures: Batteries are stored at different temperatures, often ranging from 0°C to 55°C, to assess the impact of temperature on degradation.
• Varied States of Charge: The batteries are charged to different SOC levels before storage, typically in increments of 12.5% from 0% to 100%, to evaluate the influence of SOC on calendar life.
• Periodic Capacity Measurement: At regular intervals, the batteries are removed from storage, and their capacity is measured using a standardized procedure. This usually involves a full charge-discharge cycle performed under controlled conditions, allowing researchers to track the capacity loss over time.

Data Analysis: Once the experimental data is collected, it is analyzed to quantify the rate of capacity loss and understand the influence of the chosen stress factors. This typically involves:

• Capacity Loss Calculation: The capacity loss is calculated relative to the initial capacity of the battery, providing a standardized metric for comparison.
• Modeling Degradation: Researchers often employ empirical or semi-empirical models to describe the capacity fade behavior observed in the experiments. These models incorporate the influence of temperature, SOC, and other relevant factors, enabling the prediction of calendar life under various conditions.