배터리 팩 충전 상태 및 쿨롱 카운팅 이해하기

배터리 팩의 충전 상태(SOC)는 쿨롱 카운팅과 개방 회로 전압 조회를 통해 계산된 잔여 용량에 따라 결정됩니다.

### 배터리 관리 시스템(BMS)의 SOC(충전 상태) 이해하기
* 🔋 배터리 팩의 충전 상태(SOC)는 **총 용량의 백분율**로 표시되는 남은 용량으로, 일반적으로 암페어시 또는 쿨롱 단위로 측정됩니다.
* 📊 SOC는 방전 중 다양한 전압 레벨을 고려하기 때문에 전기차와 같은 애플리케이션에서 사용 가능한 에너지를 더 정확하게 측정하는 **에너지 상태(SOE)와는 다릅니다.**
* 🔄 쿨롱 카운팅은 BMS에서 SOC를 계산하는 데 주로 사용하는 방법으로, **시간에 따른 전류를 통합**하여 방전된 암페어 시간을 추정합니다.
* 📏 BMS의 전류 센서에는 드리프트 및 적분 오류가 있으므로 **개방 회로 전압(OCV) 룩업 테이블**을 사용하여 주기적으로 **SOC 계산을 재설정**하여 보정하는 경우가 많습니다.
* 🔋 정확한 배터리 관리를 위해서는 **SOC를 이해하는 것**이 중요하며, 이를 통해 운영상의 문제로 이어질 수 있는 **보고된 충전 수준의 급격한 저하**를 방지할 수 있습니다.
* 📈 "일반적으로 팩에서 용량을 방전할 때 **전압의 하향 경사**가 다양합니다."
* 🔢 "배터리 팩을 **100암페어 시간까지 완전히 충전**한 다음 **30암페어 시간을 방전**하면 **70암페어 시간, 즉 용량의 70%가 남게 됩니다**."
* 🔍 에릭 스토펠은 안정적이고 예측 가능한 배터리 팩 운영을 위해 **SOC 정확도의 중요성**을 강조합니다.

[Music] Welcome to the Stoffel Systems Insights video series. I'm Eric Stoffel, president of Stoffel Systems. The topic of today's video is the state of charge of a battery pack as estimated by a BMS. So what is the state of charge or SOC? So it's very simple. The state of charge is defined as the capacity remaining, so that total capacity in amp hours or coulombs that you can discharge over the total capacity of the battery pack. So let's give an example. So if we had a battery pack that was say 100 amp hour battery pack total capacity, and we had 70 amp hours left to discharge, that would give us a state of charge of 70%. So this would mean that if we fully charge the battery pack up to the 400 amp hours and then discharge 30 amp hours, we would have 70 amp hours or 70% of the capacity remaining. Now it's very important to note that this is in units of amp hours, not in units of energy. And why is that important? Well, if

we look at the discharge curve for a lithium-ion battery cell, or a battery pack for that matter, with voltage here on the y-axis and on the x-axis we have amp hour discharged. What does the curve typically look like? So for most lithium-ion batteries, for example, like an NMC or LCO type chemistry, you would expect to see a curve like this, and it falls off towards the end. And so typically this is about 4.2 volts per cell, and the end of discharge is 2.5 volts per cell. This could be a little different for different chemistries, but the point is the same. In general, you have a varying downward-facing slope for the voltage as you discharge capacity out of the pack. So for example, if I took the 50% point for the amp hours discharged, so if we took the example above and said that this was 100 amp hours or 100%, and this was 50 amp hours, this is 0, then this would be the 50% state of charge point, which means that we've discharged

50 amp hours out of a hundred amp hours, and we have 50 amp hours left to go before the battery reads reaches its termination voltage. So, one thing to notice is that look at the areas under these relative curves. One side is bigger than the other. So, for example, there's a lot more energy on the left side of this line than on the right side of the line. And why is that important? Because when you confuse state of charge with a fuel gauge algorithm, this happens, which is typically if you want to get a fuel gauge. If you want to use a fuel gauge, for example, from an electric vehicle application or most applications, you're more interested in the energy available as opposed to the capacity. So, for example, if we were doing an electric vehicle design and we were trying to determine, Okay, this is a 200-mile range. At what state of charge would you have a hundred miles of range remaining? Well, look at this. The balance between this side and this side is clearly imbalanced because the voltage is higher in the lower than the higher states of charge.

and the voltage is lower in the lower state to charge so it's important to introduce the concept of soe II or SOC based on energy so we denote this as follows. I use the black pen for this so SOC c4 capacity or SOC II for energy and these are different and this is actually what most applications are interested in because this is actually the more accurate fuel gauge algorithm that tells you how much expected runtime use distance range you ever made so let's look at look at this example again if we say okay where is the actual 50% SOC II point on this well that would be where we would have approximately 50% of the area under the curve on the left side of the line as on the right side that would be somewhere more like here say that this corresponds to a point of 42% SOC see but this equals 50% SOC II so it's very important to understand the distinction between energy state to charge fuel gauge algorithms and capacity states of charge in a future.

video. We'll discuss how the state of charge is actually calculated. It typically has a number of more sophisticated elements, but for the purposes of today, I do want to discuss Coulomb counting, which is the primary way that state of charge is calculated. So, as I mentioned earlier in this example, we have 100 amp hours, and we discharged 30 amp hours to have 70 amp hours remaining, which means we're at a 70% charge. But how did we determine that we discharged 30 amp hours? Well, from the first video, we can remember that a BMS typically has a current sensor, either a shunt or a Hall effect device, that can monitor the current flowing in or out of the battery pack. And what are you doing to determine amp hours? Since amp hours are in units of current times time, we are actually performing an integration called Coulomb counting. So, this is your current, and this is time. So, say that we have a curve that looks like this, that is how much charge, that's how much

current at any given time is coming out of the pack. The area under the curve corresponds to the actual capacity removed. So, this is in units of amp-hours, and this is what Coulomb counting does. Coulomb counting is basically looking at every single slice in a time slice integration fashion, multiplying the current times the time interval, and summing that up to get an approximation of the integral of this function. And what that does is that gives us an accurate estimate of amp-hours, which gives us a basis for SoC. Now, one of the things to note about Coulomb counting and current sensing is that the current sensor has drift and integration error. So, you're not going to get perfect alignment of all your sensing with the actual current spikes itself. So, it's important to note that oftentimes you also need what's called an OCV or open cell voltage lookup to compare what you're integrating with your actual voltage. So, we'll look over here. I'll draw on this plot voltage times I'm gonna introduce a new term.

called depth of discharge. Depth of discharge is the inverse of state of charge. So for example, at 70 percent SOC, you would have a depth of discharge of 30%. So for example, 30% SOC, right, depth of discharge 60%, depth of discharge, and say this is 100%, your voltage is gonna go like this. So when the PAC has been at rest for a considerable period of time, what you do is the BMS will look up with a lookup table or something similar to see what the open circuit voltage of the cell is for a given temperature, and then it will equate that or determine what the corresponding state of charge or depth of discharge is for that, and then it will reset the SOC function so that you have a basis upon which to get an accurate understanding of where you need to start Coulomb counting again. And this is very important because you don't want to have a fuel gauge algorithm that gets off. So you can imagine how frustrating it would be if you had, say, you're driving along.

and all of a sudden you went from 30% to 0% state of charge immediately because there is an inaccurate estimation. It would leave you stranded, at least anxiety, all sorts of problems like that. So the benefit of having both open circuit voltage lookup and accurate Coulomb counting is that you can actually ensure a high degree of accuracy for the state of charge algorithm and the state of charge energy algorithm, such that your results are expected in a reliable and predictable operation of your battery pack. That's all for today, thanks for watching, see you next time. [Music]

Calculating the State of Charge of a Lithium Ion Battery System using a Battery Management System

Stafl Systems

에릭 스토펠과 함께하는 배터리 팩 충전 상태 이해하기

배터리 팩의 충전 상태(SOC)는 일반적으로 암페어시 또는 쿨롱 단위로 측정되는 남은 용량입니다.

SOC는 에너지 단위가 아닌 암페어시 단위로 측정되며, 리튬 이온 배터리의 방전 곡선은 일반적으로 용량이 방전됨에 따라 전압의 하향 기울기가 달라진다는 점에 유의해야 합니다.

50% 충전 상태 지점은 일반적으로 배터리 팩에서 방전된 암페어 시간의 중간 지점입니다.

에너지 충전 상태와 용량 충전 상태 이해하기

배터리의 남은 에너지는 남은 용량과 다를 수 있으며, 충전 상태에 따라 전압의 불균형이 발생할 수 있습니다.

이는 특히 전기 자동차 설계에서 정확한 연료 게이지 알고리즘에 매우 중요합니다.

에너지에 기반한 충전 상태 II(SOC II)의 개념은 예상 주행 시간 또는 주행 거리를 결정하는 데 더 적합하며 용량 기반 SOC보다 더 정확한 연료 게이지 알고리즘을 제공합니다.

쿨롱 계수를 사용하여 전하 상태 계산하기

충전 상태(SoC)는 주로 배터리 팩에 유입되거나 유출되는 전류를 모니터링하고 시간에 따라 이를 통합하여 암페어 시간을 결정하는 쿨롱 카운팅을 사용하여 계산합니다.

쿨롱 카운팅은 정확한 암페어 시간 추정치를 제공하여 SoC의 기초를 형성하지만 전류 센서 드리프트 및 통합 오류의 영향을 받을 수 있습니다.

정확도를 높이기 위해 오픈 셀 전압 조회를 사용하여 통합 암페어 시간을 실제 전압과 비교하는 경우가 많습니다.

배터리 관리에서 방전 깊이 이해하기

방전 깊이는 충전 상태의 역수이며 배터리 전압에 영향을 미칩니다.

배터리 관리 시스템(BMS)은 룩업 테이블을 사용하여 셀의 개방 회로 전압을 기반으로 충전 상태 또는 방전 깊이를 결정하여 정확한 연료 게이지 알고리즘을 보장합니다.

이는 배터리의 에너지 수준을 정확하게 파악하고 중단을 방지하는 데 매우 중요합니다.

정확한 배터리 충전 상태 예측의 중요성

개방 회로 전압 조회와 정확한 쿨롱 카운팅을 모두 사용하면 충전 상태 알고리즘의 정확도가 높아집니다.

이 조합은 배터리 팩의 안정적이고 예측 가능한 작동을 제공하여 갑작스러운 충전 상태 저하와 좌초 위험을 방지하는 데 도움이 됩니다.