Understanding Battery Health Without Taking Systems Offline

How can you understand battery health without taking systems offline?

For operators relying on large banks of series-connected lead acid batteries, maintaining uptime is critical. In industries such as telecommunications, data centres, utilities, and industrial backup power, shutting down systems to test battery health is often impractical and costly.

This case study outlines how we enabled accurate internal resistance measurement of lead acid batteries while the battery chain remained fully operational - either under load, charging, or both.

The Challenge: Measuring battery internal resistance under load

A client required a reliable method to measure the internal resistance of each battery in a series-connected chain without disconnecting or isolating the system.

Traditional vs On-Load Testing

The objective was to develop a non-intrusive battery monitoring solution that could operate continuously and provide meaningful health diagnostics.

The Solution: On-Load internal resistance measurement

Our engineering team designed a system capable of accurately measuring internal resistance while the batteries remained in use.

The process works as follows:

• Inject a controlled load current waveform
  A precisely defined load current waveform is imposed onto the battery chain.
  
  
• Measure individual battery voltage
  High-precision voltage measurements are taken across each battery in the series string.
  
  
• Apply advanced digital signal processing (DSP)
  The voltage waveform generated by the injected load current is isolated and filtered using digital signal processing algorithms.
  
  
• Calculate true internal resistance
  By analysing the relationship between the injected current and measured voltage response, the system calculates:
  -Individual battery internal resistance
  -Interconnection (link) resistance 
  
  
• Remove interconnection effects
  The wiring architecture enables the elimination of link and cabling resistance from the final calculation, ensuring accurate measurement of true battery internal resistance.
  
  

Why internal resistance matters

Internal resistance is a proven indicator of:

• Battery state of health (SoH)
• Performance degradation
• Remaining useful life
• Early failure detection

By monitoring internal resistance in real time, operators can:

• Identify failing batteries before system failure
• Reduce unplanned downtime
• Optimise maintenance schedules
• Extend battery bank lifespan

Scalable battery bank monitoring

The monitoring units can be connected in a ring topology, enabling internal resistance measurement across an entire battery bank. This scalable architecture makes the solution ideal for:

• Large UPS systems
• Telecom backup power
• Substation DC systems
• Industrial battery installations

Key technical features

• High-accuracy ADC (Analog-to-Digital Conversion) for precision voltage measurement
  
  
• Advanced digital signal processing algorithms for waveform filtering and analysis
  
  
• Isolated bus interface compatible with customer serial loop systems
  
  
• High-voltage front-end design suitable for large battery strings
  
  
• On-load and on-charge measurement capability
  
  
• Modular, ring-topology deployment for large installations

Results

This solution enabled continuous battery health monitoring without operational disruption. The client gained:

• Real-time visibility of battery internal resistance
  
  
• Predictive maintenance capability
  
  
• Reduced manual testing
  
  
• Increased system reliability
  
  

Conclusion

Measuring lead acid battery internal resistance without taking systems offline is not only possible - it is practical, accurate, and scalable.

By combining controlled load injection, precision voltage measurement, and advanced digital signal processing, this solution delivers actionable battery health data while maintaining full system operation.

For organisations relying on mission-critical battery systems, this approach provides a powerful foundation for predictive maintenance and long-term reliability optimisation.