Battery balancing issues can sideline your battery asset for weeks and keep you from reaching nameplate capacity daily, costing you time, money, and efficiency. In this article we explain how unbalanced batteries cost money, demonstrate how modern Battery Management Systems (BMSs) get it wrong, and show you how continuous balancing with Zitara can make balancing issues a thing of the past.
A battery pack is composed of many battery cells linked together. A battery pack is out of balance when any property or state of those cells differs. Imbalanced cells lock away otherwise usable energy and increase battery degradation. Batteries that are out of balance cannot be fully charged or fully discharged, and the imbalance causes cells to wear and degrade at accelerated rates. This reduces both the revenue of every cycle and the lifespan of the battery.
Cell differences arise during both manufacturing and operation. During manufacturing, the pack may be assembled from cells with slightly different states of charge (SoCs), capacities, impedances, or age, meaning the assembled battery pack begins life out of balance. During operation, design factors such as the arrangement of cells and layout of current collectors, bus bars, and interconnects can cause a pack to get out of balance. For large packs, such as energy storage systems, even the amount of sun or shade the pack receives can cause the pack to become imbalanced.
Regardless of the cause, balance issues usually manifest as different SoCs across series connected cells. While it is possible for cells in parallel to dynamically get out of balance with each other, parallel cell imbalances tend to resolve naturally over time. This article will focus on the more common and correctable series cell balancing issues.
Out-of-balance batteries cost you money in the short and long term. When an out-of-balance battery is charged or discharged, it delivers less than the nameplate capacity, leaving revenue on the table in every cycle. In addition, getting the battery pack back into balance can take days or weeks of balancing downtime, during which the pack is out of commission. Also, battery packs that are regularly cycled while out of balance will degrade faster than packs that are kept balanced.
A simple example is a small energy storage system with 1000 kWh (1 MWh) of nameplate capacity. The battery pack is composed of 100 series cells, with each series cell storing 10 kWh of energy. All cells are fully charged at 100% SoC except for one cell that is out of balance and is only at 90% SoC.
As a result of this one cell, the entire pack is storing 999 kWh of energy, or 1000 kWh less the 1kWh from the cell that is not fully charged. Yet, due to the one weak cell, the pack can access only 900 kWh (90%) of energy. The remaining 99 kWh of capacity is stored but inaccessible. This unbalanced pack means that every cycle delivers 10% less than the nameplate capacity, locking away the capacity you paid for and increasing degradation on every cell.
The solution is battery balancing, or moving energy between cells to level them at the same SoC. In the above example, balancing would raise the cell at 90% SoC to match the other cells at 100% SoC. Thus, the previously locked-away energy is recovered, returning the pack to its nameplate capacity.
A BMS needs two key things to balance a battery pack correctly: balancing circuitry and balancing algorithms. While a few methods exist to implement balancing circuitry, they all rely on balancing algorithms to know which cells to balance and when.
So far, we have been assuming that the BMS knows the SoC and the amount of energy in each series cell. If true, the balancing algorithm could quickly identify which cells have too much or too little energy and continuously monitor and balance those cells. After correcting initial imbalances from manufacturing, the balancing algorithm could continuously correct minor imbalances as they arise, preventing pack imbalances in the future.
However, this is where most BMSs fall short. Even though they often report an SoC value, most onboard BMSs are highly inaccurate and cannot estimate the SoC of individual series cells. Because SoC cannot be directly measured, BMSs commonly look at cell voltage, which they can measure, as a simple stand-in for SoC.
Unfortunately, the voltage of a battery cell is susceptible to outside factors such as temperature, age, loading, charging, and even hysteresis, or how the cell was recently used. Cell voltage is, therefore, an unreliable substitute for SoC. Voltage as a measure of SoC is even less reliable with modern chemistries such as lithium-iron-phosphate (LFP), which has a highly non-linear relationship between voltage and SoC.
When using cell voltage to guess SoC, typical BMSs use algorithms called “top” or “bottom” balancing. In these algorithms, the BMS attempts to balance only when cell voltages are nearly maximized at 100% SoC or nearly minimized at 0% SoC. As a result, in typical usage patterns where batteries are usually not charged to 100% or discharged to 0%, the cell balancing algorithm rarely has an opportunity to balance during regular operations.
What’s more, balancing circuitry is typically sized to balance only 1% of the SoC of a series cell in 24-72 hours of balancing time. Consequently, many BMSs cannot keep up. The BMS can’t keep a pack balanced or correct a pack that is out of balance. The problem is not with the balancing circuitry but with the algorithms that cannot accurately estimate the SoC of series cells.
The only solution to balancing with these BMSs is dedicated downtime at regular operational intervals. This downtime keeps the pack fully charged or discharged for days or even weeks to allow for balancing. Since the battery will again become imbalanced in everyday use, downtime becomes a regular occurrence, costing you money in reduced capacity on every cycle and lost revenue during downtime.
Zitara flips this problem on its head. Instead of looking at voltage signals to find a narrow window for balancing, Zitara starts with an accurate model of the battery cells and tracks the SoC of each series cell in any condition.
With Zitara, balancing occurs continuously in any usage pattern. Whether the battery is charging, discharging, resting, hot, cold, full, empty, or anywhere in between, Zitara Live continuously and accurately tracks every cell’s SoC. With Zitara Live, continuous balancing eliminates downtime. Continuous balancing ensures that the total nameplate capacity of the battery is delivered on every cycle, leaving no energy or revenue locked away. You paid for the whole battery—Zitara lets you use it.
Batteries that are out of balance cause problems. They lock away otherwise usable energy and increase battery degradation. For example, when a BMS detects one cell reaching the end of its discharge, the BMS shuts down the entire pack, even if the other cells have additional capacity remaining. This reduces both the capacity of every cycle and the lifespan of the battery.
Battery cell balancing brings an out-of-balance battery pack back into balance and actively works to keep it balanced. Cell balancing allows for all the energy in a battery pack to be used and reduces the wear and degradation on the battery pack, maximizing battery lifespan.
Many battery packs come with underpowered balancing algorithms, causing them to require days or weeks of downtime for balancing. With an accurate onboard battery model, balancing can instead be done continuously, eliminating the need for any dedicated balancing time at all.
Passive: Passive balancing circuitry uses resistors and electronic switches to selectively remove energy from series battery cells. The energy cannot be moved between series cells, only removed from individual cells. Coupled with an accurate balancing algorithm, the cells with too much energy can be balanced to remove excess energy and bring them back in balance with the rest of the pack.
Active: Active balancing circuitry uses electronic switches to selectively move energy between series cells. Just like with passive balancing, accurate balancing algorithms are needed to identify the cells to move energy to and energy from in order to bring the entire pack into balance.
Top and bottom balancing describe whether balancing algorithms act on battery cells when a pack is fully charged or fully discharged, respectively. This is a limitation imposed by voltage-based balancing algorithms that restrict when balancing can occur. SoC based balancing algorithms such as Zitara Live allow for continuous balancing, eliminating the restrictions of voltage balancing algorithms.
Cell balance
Cell balance refers to the differences in state of charge of the series cells in a battery pack. The amount of imbalance is the highest cell’s state of charge (SoC) minus the lowest cell’s
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