Advanced battery diagnostics is similar to a medical examination that involves complex pharmaceutical tests. The end goal in battery testing is assessing the remaining useful life in capacity, the leading health indicator.

Battery testing is divided into two basic methods. One is reading captured performance data stored in the Smart Battery System (SMBus) with portable devices; another is taking the electrochemical evidence of larger batteries with a matrix serving as lookup tables. These matrices are reference data similar to face recognition evaluated by AI.

Face recognition with AI

Matrix resembles a bridge from good to bad battery

This article represents matrices that achieve accuracy by including new, partially used, moderate and weak batteries in a matrix serving as a template against which batteries are assessed as if standing before a mirror. An analogy is a bridge with pillars that provide a path from good to weak batteries. The more pillars available, the better the readings will be.

One of the most basic battery test method is measuring internal battery resistance relating to power. While simple, this test method cannot assess capacity. Many batteries tested by power pass but soon fail on low capacity, while others fail prematurely that could be kept in service longer based on sufficient capacity.

Capacity readings are important, a reference made visible with a study provided by Johnston Control in Germany that shows that 48% of starter batteries fail by insufficient capacity while only 12% quit by low CCA.

Scientists envision the future of battery diagnostics in EIS, a technology that has not yet been fully explored. Cadex was first to measure battery capacity by EIS. Test accuracies are based on the Matrix Integrity Level (MIL) that can be improved over time to meet customer demands.

Causes of starter battery failures

Spectro™ sorts the Matrix Integrity Level (MIL) into these categories:
MIL-1: Insufficient for testing. Not applied.
MIL-2 to 3: Provides pass/fail classification for starter batteries. Pass assured grace to next service.
MIL-4 to 5: Evaluates SoH on good, fair and poor category.
MIL-6 to 7: Categorizes SoH into several performance segments
MIL-8 to 10: Displays capacity and other readings in numeric numbers

For simplicity, starter batteries are often tested with a generic matrix based on pass/fail capacity classification. This provides a grace period on pass to maintain battery reliability to next service while prompting a replacement if capacity is low while cranking may still be strong.

Consumer Auto is flooded with devices that test batteries mainly by loading. With EIS Direct Drive we focus on Industrial Auto serving large batteries non-invasively to provide reliable maintenance between services. Industrial Auto has stricter requirements than Consumer Auto and battery capacity plays a leading role as capacity is often also used for hotel load. Our goal is to develop quasi model-specific matrices to improve the test accuracies on selected starter batteries. The cost-effecting Spectro will then spread to Consumer Auto by providing improved battery evaluations for the broad public.

Spectro technology offers other battery test applications that we pursue. One example is the Spectro Monitor to assess the capacity of stationary batteries with notification to replace when the end of Minimum Operational Reserve Energy (MORE) is reached. While stationary batteries are often installed and forgotten, MORE enables the full use of each battery with planned replacement before failure.

Another use is Spectro BMS that takes the electrochemical evidence of a battery and deploys a model-specific matrix to assess capacity and other performance characteristic. Stored in the Matrix Library, custom matrices open subscription services to check batteries with custom matrices under subscription. The Matrix Library is a new business model that will be used to improve battery service.

An additional service is the Spectro Explorer that evaluates the safety of e-bike and other mobility batteries by viewing the Nyquist plot. Our goal is to identify anomalies by the Nyquist plot and provide caution if the battery is compromised. This is important as charging of these batteries is often done in residential dwellings. Venting with flame is not an option.

Conclusion

With the availability of the X-Matrix we approach global companies active in Commercial Auto as listed on the right. This requires sales staff that is familiar with battery test technologies, goes out to introduce advancing technologies, such as EIS, and offers trial units with focus on capacity.

Our training includes education by replicating RCM (Reliability-centered Maintenance) in batteries, a method that gained acceptance in the 1960s to maintain machinery. The first RCM use was the Boeing 747, service that spread to nuclear plants, defense and commuter rail.

As batteries begin assuming critical function, the remaining useful life must be known at all time to prevent unexpected failures. Capacity estimation with EIS is new with promises to exceed expectation once fully developed. More is possible by improving the Matrix Integrity Levels to get a full insight into the battery architecture by evaluating the electrochemical evidence.

Global distribution of industrial Auto

Back To All Posts

June 2024 - Article

Conclusion