In an industrial-scale BESS system, management is not limited to a few battery cells, but thousands, even tens of thousands of battery cells operating simultaneously. How can a BMS system monitor and control such a large “army” effectively? The answer lies in an intelligent management architecture and sophisticated computing algorithms.
This article will dive into two core technical aspects: the common hardware architecture of BMS and how it calculates the two “vital” parameters, SoC and SoH.
1. Master-Slave Distributed Architecture
To manage a large battery system, the most popular and efficient BMS architecture is Master-Slave distributed architectureThink of it like a military command structure:
- Slave BMS (BMS / Subordinate): Each battery module (a block of many battery cells) will be equipped with a Slave BMS board. The task of this “soldier” is to directly and continuously monitor the basic parameters of each battery cell inside that module, such as voltage and temperature. It is also responsible for performing local tasks such as battery cell balancing.
- Master BMS (BMS / Superior): This is the “general” in command. The Master BMS will collect data from all the Slave BMSs. Based on that overview, the Master BMS will perform more complex calculations, make decisions at the system-wide level (e.g., calculate SoC, SoH) and communicate with the overall energy management system (EMS).
Why is this architecture efficient?
- Scalability: Easily add new battery modules to the system, each module comes with its own Slave BMS, and simply connect them to the Master BMS.
- Reliability: If a Slave BMS fails, it only affects a single battery module, not bringing down the entire management system.
- Minimize wiring: Significantly reduces the complexity of the signal wiring system compared to connecting each battery cell to a single central controller.
2. Decoding Key Specifications: SoC and SoH
The Master BMS doesn't just collect data, it turns those numbers into useful information. Two of the most important parameters it calculates are SoC and SoH.
a. State of Charge (SoC): The Battery's “Gas Tank”
- Define: SoC is an indicator, expressed as a percentage (%), that shows how much energy is left in the battery compared to its maximum capacity at that moment. It is essentially the “electronic fuel tank” of the BESS system.
- Calculation: Calculating SoC is not as simple as measuring fuel level. BMS usually use a combination of methods, the most common being “Coulomb counting” (integrating charge/discharge current over time) and periodic calibration based on the relationship between voltage and state of charge.
- Importance: The SoC is the core information for the EMS to decide when to charge, when to discharge, and how long the system can operate.
b. State of Health (SoH): Battery “Lifespan”
- Define: SoH is also a percentage (%), but it doesn’t measure the remaining energy on a charge, but rather the overall “ageing” of the battery. It compares the battery’s current maximum energy storage capacity to when it was brand new. A battery with an SoH of 80% means it can only store 80% of its original design capacity.
- Calculation: This is a very complex parameter to estimate. The BMS has to monitor changes in factors such as the internal resistance of the battery, the capacity degradation over each cycle, and other factors over a long period of time.
- Importance: SoH is an important metric for evaluating long-term performance, planning maintenance, and predicting when battery systems need to be replaced. It helps protect the value of a business's investment.
The Master-Slave architecture and the ability to accurately calculate parameters such as SoC and SoH are what make the difference between a basic BMS and an advanced battery management system. A solid architecture ensures scalability and reliability, while intelligent algorithms provide accurate data, allowing the BESS to operate safely, efficiently and optimally throughout its lifecycle.
