BU-917: In Search for Performance Transparency with Batteries

As the world electrifies, battery diagnostics has been lagging behind core developments in batteries. Performance transparency must be equal to or higher than traditional energy systems that burn fossil fuels. Cadex realizes the importance of battery diagnostics and is developing rapid-test technologies that assess battery capacity, the leading health indicator.

Speakers at battery conferences have been promoting the life of a battery as a consumable product that begins with research; then moves to manufacturing, is placed into field deployment, and ends in recycling to retrieve valuable materials. While this business model is solid, one vital part in the life of a battery is missing — it’s diagnostic to enable the full use of each battery with a call for replacement before failure. Imagine life without a doctor to fix our ailments.

Advancements in battery diagnostics are visible and this includes electrochemical impedance spectroscopy (EIS). While the research is mostly done with lab-stressed batteries, commercializing the technology to make performance on field-aged batteries visible to untrained staff is still missing.

Cadex solved this limitation in an instrument that creates a Nyquist plot that is modeled against a matrix to extract battery capacity and other data. Test accuracies rest on the integrity of the matrix that is composed by taking performance data from aged batteries of same-model. The technology is able to assess battery state-of-health (SoH) of lead-acid and lithium-ion systems.

Battery Diagnostic Pyramid

With time, several battery test methods have emerged that are captured in Figure 2. A low numbers in the Battery Diagnostic Pyramid reflect an older and more basic approach while higher numbers include some form of training in use.

EIS stands on its own by comparing test results with a matrix serving as lookup table that is analogous to face recognition using AI. Of importance with all test methods is the ability to assess capacity, the gatekeeper that governs the remaining useful life of a battery.

No universal battery test methods exist that serve all applications. Here is a summary of the best uses.

1. Load Test is a proven method to check power, such as cranking an engine but load test alone cannot assess capacity. Without also knowing the capacity, continuous cranking ability is not assured.

2. Dynamic Response assesses battery SoH by voltage-recovery after applying a load pulse. An analogy is observing the heartbeat after exercising that quickly normalizes in a healthy person. With Li-ion, a quick voltage recovery denotes unrestricted ion flow that manifests good health.

3. Machine Learning calculates battery capacity by tracking charge and discharge currents in coulombs. (One coulomb is 1A per second.) The System Management Bus (SMBus) developed for portable devices also serves the EV and Battery Energy Storage Systems.

4. EIS takes the electrochemical evidence of a battery and compares the results against a matrix. Efforts are made to offer matrices for diverse battery models online for global use.