As in many other areas, the use of big data and data analytics presents new possibilities for the battery industry. This means that these solutions can be harnessed to more rapidly advance technology development and improve battery efficiency to overcome the very challenges facing the energy storage industry, especially in the context of electric vehicles.
What exactly is BMS?
Battery management systems (BMS) are an essential tool for maximising overall battery performance.
For several reasons:
- They provide detailed information
- Allow for adequate monitoring throughout its lifetime.
In addition, they offer the possibility of optimising key aspects such as:
- Energy density
- Charge/discharge rate (c-rate)
- Cycling capacity
- Temperature
- Geometry
Benefits of using BMS in lithium batteries
Detailed analysis of the data collected allows for the identification of patterns and trends in battery performance. This makes it easier to optimise performance, whether by adjusting charge and discharge parameters, modifying geometry or implementing more efficient management strategies.
Data analytics in batteries also plays a crucial role in the traceability of their entire life cycle. It allows relevant information to be tracked and recorded at every stage, from manufacture to use and eventual recycling of the battery.
This affects different phases:
- Battery manufacture
- Distribution and logistics
- Use and performance
- Maintenance and service
- Recycling and life cycle management
The knowledge gained through data analysis and research identifies key areas for battery improvement.
This may include:
- Research into new materials
- Optimisation of battery structure and geometry
- Designing new, more advanced battery management systems
On the other hand, modelling and simulation techniques can be used to design optimised batteries from the outset.
This involves taking into account factors such as:
- Energy density
- Efficiency
- Fast charging capability
- The lifespan
- Security
Instead of extensive testing on physical prototypes, models can be used to evaluate and select the best design options. This helps to reduce costs and time. It is also a way to ensure performance and quality.
In addition, it is possible to tailor their configuration and composition to meet the specific needs of different applications. For example, batteries with optimal characteristics for electric vehicles can be developed.
Finally, by better understanding the condition and performance of batteries through data analysis, we can identify which batteries still have capacity and life remaining to be used in other applications.
By giving batteries a second life, premature disposal is avoided and waste generation is reduced. This has a positive impact on the environment by maximising the value of materials and reducing the need to produce new batteries.
On the other hand, it also has important economic benefits, and it plays in favour of greater flexibility and adaptability.
Challenges for BMS to achieve this model
To achieve the above-mentioned benefits, the first step is to understand and address the fact that the industry presents two major challenges.
The first challenge is to develop battery management systems (BMS) that are able to capture and exploit information effectively. A BMS is an electronic system that collects and monitors key data on battery performance and lifetime.
The BMS is an essential component present in all batteries to ensure their safe and efficient operation. However, it is necessary to incorporate software solutions that go beyond its current functionality.
This means turning the BMS into a "brain" that not only manages information, but also understands it and uses it in an optimal way. To achieve this requires the development of new technologies that enable advanced data management and analysis.
The second challenge relates to the need to develop advanced BMSs capable of adapting to any generation of batteries. As energy storage technology advances, new generations of batteries with different characteristics and requirements are introduced.
As energy storage technology advances, new generations of batteries are introduced with varying configurations, chemistries and approaches. BMS systems must keep pace with this evolution and be able to adapt to these new technologies. This means developing flexible and modular solutions that can be upgraded or reconfigured according to the specific characteristics of each generation of batteries.
In this way, more efficient and accurate management of batteries throughout their life cycle will be achieved.
Conclusion
In short, thanks to the potential of big data and data analytics, batteries can benefit from improvements in performance, lifetime and safety. This integration between the battery industry and digital technology with the battery BMS not only contributes to the energy transition and sustainability, but also has a positive impact on our society and environment.
Moving in this direction opens up new possibilities for the future of batteries and boosts technological development in general.