AUTOMATION & ROBOTICS
for a LiFePo4 battery is 350mV, then every 1mV of cell measurement error reduces the range by 0.28 percent.
IF A BATTERY PACK COST IS $4000, THE COST OF ERROR IS:
$4000 × 0.28 percent = $11.20/mV error, which means that the battery packs would be underused for the range.
Figure 2. Battery pack voltage level vs. DoD.
Figure 3. AMR generic battery and BMS architecture.
TO ILLUSTRATE THIS IN A REAL-LIFE SCENARIO:
Imagine the following AMR is a 24V system and uses a 27.2V LiFePo4 battery pack where each cell has a capacity of 3.4V when fully an SoC for such a battery can be seen in Table 1.
Table 1. Example Data for LiFePo4 Battery Cell and Pack Voltage
SoC Cell Voltage Pack Voltage 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
3.4
3.35 3.32 3.3
3.27 3.26 3.25 3.22 3.2 3
2.5
27.2 26.8 26.6 26.4 26.1 26.1 26
25.8 25.6 24 20
For LiFePo4 batteries, the usable range can vary, but it is a good rule of thumb to consider that the minimum SoC is at 10 percent and the maximum is at 90 percent. Anything below the minimum level can cause an internal short circuit on the battery and charging above 90 percent reduces the lifetime of these batteries.
Taking Table 1 into consideration, note that the voltage range per cell is 350mV, and for a 27.2V pack with 8 cells, it is 3.2V. Having that in mind we can draw the following assumptions; if the usable cell voltage range
Figure 4. Maximum usable range reduction due to natural degradation.
Monitoring all the parameters and precisely controlling the usage of the battery is the best way to extend the life cycle and take advantage of every single unit of charge.
HOW CAN ADI’S BMS SOLUTIONS INCREASE PRODUCTIVITY AND SOLVE PROBLEMS?
So, what technologies can ADI’s BMS offer to enhance and achieve high performance in mobile robotics applications? The precision of battery management batteries by precisely measuring the cells, allowing for more accurate control and estimation of the SoC across various battery chemistries. Measuring each cell individually ensures safe monitoring of battery health. This precise monitoring facilitates balanced charging, preventing cells from overcharging and discharging. Additionally, synchronous current and voltage measurements increase the accuracy of the acquired data. Extremely fast overcurrent detection allows for quick failure detection and emergency stops, ensuring safety and reliability.
While 0.28 percent of the range may appear negligible, when scaled up to multiple AMR systems, this percentage could be multiplied by hundreds or even thousands, making it a more relevant if natural battery degradation is taken into consideration. Natural degradation also plays an important role in battery health as, with time, the maximum SoC of a battery will degrade (Figure 4), hence why a precise measurement of the cells is the best way of keeping performance at an optimal level, even after natural degradation.
The ADBMS6948 provides all the key specs required for mobile robots, but a few critical specs with BMS design considerations for a mobile robot are: • Small total measurement error (TME) over a lifetime, (–40°C to +125°C)
• Simultaneous and continuous measurement of cell voltages
• Built-in isoSPI interface • Hot-plug tolerant without external protection
• Passive cell balancing • Low power cell monitoring (LPCM) for cell and temperature monitoring in key- off state
• Low sleep mode supply current
REDUCING WASTE AND HELPING THE ENVIRONMENT
According to the International Energy Agency’s 2023 report on batteries, “Batteries are an essential building block of the clean energy transition.” It is crucial to recognise the importance of properly managing these resources. The materials that constitute environment, underscoring the need for their the charging and discharging parameters, we can extend the lifespan of batteries, allowing them to be used for longer periods without needing replacements.
The low risk factor with overcurrent protection provided by ADI’s BMS feature allows for very safe operation and cuts down on the risk of damaging both the battery and the system connected as a load. A few examples of degradation factors in Li-Ion batteries can be seen in Figure 5 and it is important to note that they can lead to dangerous situations such as combustion and explosion, which could quickly become catastrophic.
degradation can be measured, treated and acted upon, providing the system with the most optimal conditions to operate over the required lifetime. Increasing the battery’s lifetime is an important factor in the reduction of waste as now the batteries can be used longer due to optimised management, effectively reducing the unnecessary disposal of battery cells.
In summary, we can conclude that BMS can not only increase the overall performance of the system by allowing every parameter to be precisely controlled, but also reduce cost and waste. In an evolving manufacturing environment that is becoming more and more automated and is seeking the extra percentage of performance on its mobile robots, precisely controlling and managing assets becomes essential.
To learn more about ADI offerings for industrial mobile robots, please check our robotics solutions page.
Figure 5. Main degradation factors for Li-Ion batteries.
Analog Devices
www.analog.com
FACTORY&HANDLINGSOLUTIONS | APRIL 2025 39
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