The rapid emergence and evolution of distributed generation and renewable energy sources such as wind and solar power has increased the need for the transmission and distribution of electricity.
Due to the increasing number of battery energy storage systems, various organizations and government agencies have started to develop safety standards for these systems.
Comprehending Predictive Maintenance For Battery Safety and Protection
This tool uses a combination of data points collected from a battery management system to predict the optimal time to perform battery protection maintenance. It can then provide you with useful details about the condition of the battery pack.
With the help of machine learning and cloud technology, this tool can either be used to prevent a potential failure or perform a manual analysis. According to researchers at Cambridge University, the power of AI and ML to predict the health of batteries is 10x better than the industrial standards.
They noted that this technology could save up to 40% on average compared to preventive maintenance. However, when it comes to choosing the right battery protection system, you can always rely on its advanced capabilities to predict the end of life of your battery pack.
Determining Failure of Batteries
It can be hard to predict when lithium-ion batteries will fail, especially since it’s usually not immediately evident that something is wrong. With the help of predictive maintenance, you can identify potential issues and fix them before they cause harm. You can also predict the exact time that your batteries will end their lives.
Utilizing Predictive Maintenance
This process is commonly referred to as predictive maintenance, and it involves analyzing data and monitoring tools to identify potential issues before they happen. This industry practice has been around since the 1990s, and it’s gaining popularity due to the increasing number of Internet of Things (IoT) applications.
This process is carried out according to the principles of condition monitoring, which involves continuously monitoring an asset to ensure its optimal performance. A battery management system uses data collected by various sensors to perform precise predictions.
Predictive maintenance aims to identify the most cost-effective and convenient time to perform routine maintenance on a battery. This method ensures that the device’s life lasts longer and is always used to its full capacity.
Preventive vs. Predictive
The difference between preventive and predictive maintenance is the time that the work is performed. In preventive maintenance, the focus is on identifying and performing maintenance on equipment regardless of its condition. On the other hand, in predictive maintenance, the focus is on identifying and performing maintenance on an asset only when it’s needed.
The difference between preventive and predictive maintenance is the type of data that is collected to determine the scope of the work that’s required. The data is collected from historical records and various statistical techniques in preventive maintenance. On the other hand, in predictive maintenance, the data is analyzed in real-time using data analytics systems.
Although preventive maintenance is generally cheaper than predictive maintenance, it can still add up to a higher cost in the long run. Preventive maintenance usually involves following the manufacturer’s guide when replacing or changing critical components. Instead, with predictive maintenance, you only replace those needed components.
Advantages of Using Predictive Maintenance
Constantly charging and discharging can cause a battery to overcharge and eventually fail. This can lead to a reduced lifespan and cell failure. With predictive maintenance, you can identify and replace a battery unit’s end-stage components right before it fails. This method offers various advantages, including extending battery life, reducing faulty cell numbers and improving battery prognosis.
With the use of a battery management system, you can now rely on your actual usage to determine when it’s necessary to perform maintenance. This method eliminates the need for you to follow the manufacturer’s advice when it comes to maintaining your energy storage systems.
All in all, implementing predictive maintenance systems will ensure battery safety. The key is to use IoT solutions successfully. However, due to the learning curve involved, personnel training is a must. Despite the advantages of this technology, it can still be challenging to implement it in your organization due to the training requirements that are involved.
Author Name: Jacki
