Editor's Choice


How ADI battery management solutions empower safer, smarter robots

31 October 2024 Editor's Choice Power Electronics / Power Management

Choosing an appropriate battery pack and its accompanying battery management system (BMS) is a critical decision in designing an autonomous mobile robot (AMR).

Choosing an appropriate battery pack and its accompanying battery management system (BMS) is a critical decision in designing an autonomous mobile robot (AMR). In tightly integrated settings like factories and warehouses, where every second of operation matters, ensuring the safe and reliable functioning of all components is of utmost importance.

BMS solutions can provide accurate measurements on the charging and discharging of the batteries, which maximises the usable capacity. Additionally, the precise measurements allow for an exact calculation of the state of charge (SoC) and depth of discharge (DoD), which are essential parameters to allow smarter workflows of mobile robots. Equally important are the safety aspects of such systems, and it becomes crucial to consider BMS technologies that provide both overcharge protection and overcurrent detection when selecting systems for these applications.

What are battery management systems?

A BMS is an electronic system that can be used to closely monitor various parameters of a battery pack and/or its individual cells. It is critical for achieving the maximum usable capacity of the batteries, while ensuring safe and reliable operation. An efficient system can not only optimise the usable capacity of the battery in a safe manner, but also provide the engineers with valuable parameters such as the cell voltage, SoC, DoD, state of health (SoH), temperature, and current, all of which can be used to get the best performance out of a system.

What Are SoC, DoD, and SoH, and why are they important for AMRs?

SoC, DoD, and SoH are a few of the common parameters used in BMS to determine if the system is healthy, and provide early fault detection, cell aging, and the remaining time of operation.

SoC stands for state of charge and can be defined by the level of charge of a battery in relation to its total capacity. SoC is usually expressed as a percentage from 0 to 100.

SoH can be defined by the maximum capacity (Cmax) of the battery that can be released relative to its rated capacity (Cmax).

DoD or depth of discharge is the opposite metric of SoC, and is defined by the percentage of the battery that has been discharged (Creleased) relative to its rated capacity.

How are those relevant for an AMR solution?

The SoC of a battery varies according to the battery architecture, nonetheless, it is necessary to have a precise system to measure the state of a battery. Two main types of commonly used batteries are Li-Ion and lead acid batteries. Each has its pros and cons, with various subcategories. In general, Li-Ion batteries are considered a better choice for robots because they offer:

• More energy density, which could be in the order of eight to 10 times the energy density of a lead acid battery.

• Li-Ion batteries are lighter than lead acid batteries of the same capacity.

• Charging a lead acid battery takes longer than charging a Li-Ion battery.

• Li-Ion batteries offer an extended life cycle, allowing for a significantly higher number of charge cycles.

However, these advantages come with a higher cost, and pose certain challenges that need to be addressed to fully realise their performance benefits.

To better explain this in a real-life application, it is possible to analyse the plot in Figure 1, which compares the DoD of a lead acid battery and a Li-Ion battery. It can be observed that the pack voltage varies minimally for a Li-Ion battery while going from 0% DoD to 80% DoD. 80% DoD is usually the lower limit for Li-Ion batteries, and anything below that can be considered a dangerous level.

However, because the pack voltage on a Li-Ion battery shifts only minimally for the usable range, even a minor measurement error could lead to a substantial decrease in performance.

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%, and the maximum is at 90%. Anything below the minimum level can cause an internal short circuit on the battery, and charging above 90% reduces the lifetime of these batteries.

Natural degradation also plays an important role in battery health as, with time, the maximum SoC of a battery will degrade (Figure 2), hence why a precise measurement of the cells is the best way of keeping performance at an optimal level, even after natural degradation.

Monitoring all the parameters and precisely controlling the usage of the battery is the best way to extend the lifecycle and take advantage of every single unit of charge.

How can ADI’s BMS solutions increase productivity and solve problems?

The precision of battery management significantly enhances the efficiency of 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.

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 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 keyoff state.

• Low sleep mode supply current.

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. 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.


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