Analysis of SOC concept for lithium batteries

Dyness Knowledge | Lithium battery SOC concept analysis

Abstract: Lithium-ion batteries are increasingly widely promoted and used in modern life. A lithium battery's State of Charge (SOC) is equivalent to a car's fuel tank. Always remind the user how much power is currently available; for example, 100% power equals a full gas tank. 0% means that the battery is exhausted; that is, no gasoline is in the fuel tank.

Scientific, efficient, and relatively accurate measurement of SOC for lithium batteries not only requires scientific measurement methods but also advanced software algorithms as a necessary guarantee for battery companies to obtain real-time values. This requires battery manufacturers to continuously improve and upgrade the algorithm of their own battery management system (BMS) to obtain relatively accurate power information and understand the health status of the battery during user use. By writing corresponding programs in the BMS system in advance, the value of SOC can be calculated through the voltage method, Kalman filtering measurement method, or Coulomb counting method.

1. Lithium-ion batteries are essential in everyday life, powering consumer electronics from smartphones to electric cars.

SOC is one of the important indicators of battery performance and lifespan. SOC is defined as available capacity (in Ah-ampere-hours) and expressed as a percentage of its rated capacity. The SOC parameter can be seen as a thermodynamic quantity that enables people to evaluate the potential energy of the battery. Estimating the state of health (SOH) of the battery is also important, as it represents a measure of its ability to store and transmit electrical energy compared to new batteries (Ghazel, 2017).

If the battery is discharged too deeply or charged too frequently, it will affect its overall health and shorten its service life. To ensure the service life and optimal performance of the battery, it is particularly important to keep the SOC within a safe range. Generally, it is recommended to keep the SOC between 20% and 80%. Below 20% or above 80% will pressure the battery and shorten its overall service life. This is why some international manufacturers indicate in their consumer electronics battery column that when the SOC needs to be maintained in this range, the activity of lithium ions in the battery should be maintained as much as possible. The battery life should be extended as much as possible.

SOC %-100%

SOC≈20-80%

SOC＜20%

 

2. The measurement of SOC can be divided into an algorithm based on the measurement model or a method based on the battery charge and discharge throughput and the battery body voltage to obtain the value.

There are differences and emphases among the three. Therefore, the SOC values calculated by the three methods also have relative deviations.

 

3. Coulomb counting

Also known as ampere-hour counting and current integration. When the battery is charging and discharging, the SOC is estimated by accumulating the charged and discharged electricity. The calculation method is as follows:

I（now）*tC(max)SOC(now)=SOC(past)- ——C (max): battery (maximum) capacity; I (now) current (A); t: time

The disadvantages of this metering method are:

1. Errors are caused by current sampling.
2. The error was caused by the change in battery capacity.
3. Errors are caused by the estimation and selection of the SOC's initial and final values, which in turn affect the calculation of the overall value.

 

This method only crudely records the amount of electricity entering and leaving the battery from the outside. It ignores the attenuation caused by the replacement of lithium ions in the separator and the generation of lithium dendrites inside the battery, which affects the calculation of the battery's SOC from the inside out. This error will only increase over time. Due to this drawback, battery companies are required to continuously upgrade their BMS to reduce errors.

This method only roughly records the amount of electricity entering and exiting the battery from the outside. It ignores the attenuation caused by the replacement of lithium ions inside the battery, the generation of lithium dendrites, and other variables that affect the SOC calculation of the battery "from the inside out." The error will only get bigger and bigger as time goes by. Due to this disadvantage, battery companies are required to continuously upgrade their BMS to reduce errors.

 

4. Open circuit voltage method

The SOC of a battery, which refers to its remaining capacity, can be determined using discharge testing under controlled conditions. This rule converts the battery voltage reading into an equivalent SOC value using the known discharge curve (voltage and SOC) of the battery. However, due to the electrochemical kinetics and temperature of the battery, the voltage is more affected by the battery current. By compensating for the voltage reading with a correction term proportional to the battery current and using a lookup table of the battery pen circuit voltage (OCV) and temperature, this method can be made more accurate. Batteries require a stable voltage range, which makes the voltage method difficult to implement. In addition, discharge testing usually involves continuous charging, which makes most applications very time-consuming.

 

A battery's SOC, or its remaining capacity, can be determined using a discharge test under controlled conditions. This algorithm uses the battery's known discharge curve (voltage vs. SOC) to convert a battery voltage reading to an equivalent SOC value. However, the voltage is more affected by the battery current due to the electrochemical kinetics and temperature of the battery. This method can be made more accurate by compensating the voltage reading with a correction term proportional to the battery current and using a lookup table of the battery pen circuit voltage (OCV) and temperature. Batteries require a stable voltage range, which makes the voltage approach difficult to implement. Additionally, discharge testing often involves continuous charging, making most applications time-consuming.

 

In addition, the open-circuit voltage of lithium iron phosphate batteries is almost a straight line in the range of 30% to 80%, making it more difficult to find the corresponding value. Therefore, this method is suitable for long-term static batteries that are not frequently used.

 

5. Kalman filter method

A dynamic simulation algorithm for detecting the internal state of battery cells and applicable to calculating battery SOC values. The method provides dynamic error boundaries and adopts error correction mechanisms, and provides real-time prediction of SOC. Although Kalman filtering is an online and dynamic method, it requires a suitable battery model and accurate identification of its parameters. It also requires large computing power and accurate initialization.

A dynamic simulation algorithm for detecting the battery cell’s internal state is suitable for calculating the battery SOC value. The method itself provides dynamic error bounds, employs error correction mechanisms, and provides real-time prediction of SOC. Although Kalman filtering is an online and dynamic method, it requires a suitable battery model and precise identification of its parameters. It also requires large computing power and accurate initialization.

In summary, the SOC value is a relatively core consideration in battery manufacturing. It affects not only the user's intuitive experience of using the battery but also the battery life or the investment cost of customers purchasing the battery. Therefore, maintaining the battery SOC value within a recommended range during use and updating the firmware of the battery product in real time are important guarantees for ensuring product life and user experience.

Therefore, maintaining the battery SOC value within a recommended range during use and updating the battery product firmware in real time are important guarantees to ensure product life and user experience.

Cite works

Quotations

GhazelMurnane & AdelMartin. (2017). A Closer Look at State of Charge (SOC) and State of Health (SOH) Estimation Techniques for Batteries.

Minho KimKim, Jungsoo Kim, Jungwook Yu, Soohee HanKwangrae. (2018). State of Charge Estimation For Lithium Iion Batteries Based on Reinforcement Learning. ScienceDirect, pages 404-408.

 

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