Discover why a good CCA reading does not always guarantee a good battery
Ever since Cadillac invented the starter motor in 1912, car mechanics explored ways to measure cold cranking amps. CCA measurements assure that the battery has sufficient power to crank the engine, especially when cold. A starter battery with low resistance promises reasonably good cranking ability, and a CCA reading of 400 to 500A is sufficient for most starter batteries. According to SAE J537, a CCA reading of 500A delivers 500A at -18C (0F) for 30 seconds without dropping below 7.2 volts. [BU-904 How to Measure Capacity].
Courtesy of BMW
A diversity of battery testers have emerged that measure the internal resistance of a starter battery, the gatekeeper that correlates with CCA. These devices are the trusted carbon pile, pulse-load tester, the non-invasive AC conductance method and the modern electrochemical impedance spectroscopy (EIS).
To test the CCA with a carbon pile, a fully charged starter battery is loaded with half the rated CCA for 15 seconds at a moderate temperature of 10º C (50º F) and higher. As example, a 500 CCA battery will discharge at 250A for 15s and the battery passes if the voltage stays above 9.6V. Colder temperatures will cause the voltage to drop further. The carbon pile simulates real-life load condition, detecting defects involving partially shorted cell (low specific gravity) that non-invasive methods might not catch.
Mechanics prefer small sizes and device manufactures have developed handheld testers that induce a momentary high-current pulse. Ohm’s law calculates the internal resistance on hand of the induced voltage drop and provides a CCA-equivalent reading. The test results of this device are similar to those of the carbon pile. The battery should be fully charged and the load methods can estimate capacity.
The AC conductance method reads CCA by injecting a single frequency of 80–90 Hertz to the battery. These non-invasive units are small, stay cool during the test and the battery does not need to be fully charged. As with the other test methods, AC conductance cannot read capacity.
Critical progress has been made in electrochemical impedance spectroscopy (EIS). EIS has been used for many years in laboratories to analyze diverse materials and what has emerged is combining EIS with complex modeling to estimate CCA and capacity. The resulting multi-model electrochemical impedance spectroscopy is called Spectro for short (CadexTM) and here is how it works:
A sinusoidal signal ranging in frequency is injected into the battery at a few millivolts. After digital filtering, the extracted signal produces a Nyquist plot onto which Nyquist plots for various electrochemical models are superimposed. The best matching electrochemical models within allotted margins are selected; non-fitting models are rejected. Data fusion correlates the values of the key parameters to derive at capacity and CCA estimations. Figure 1 illustrates the patented process in a simplified way.
Figure 1 Spectro™ combines EIS with complex modeling to estimate battery capacity and improve CCA measurements
A sinusoidal signal produces a Nyquist plot; data fusion correlates the values of the key parameters to estimate capacity and CCA.
Figure 2 shows the relationship between capacity and available CCA of a fluid-filled container. The liquid represents the capacity, and the tap symbolizes the energy delivery or CCA. While CCA tends to stays stable through most of the battery life, the capacity decreases steadily. The capacity loss is illustrated with the growing “rock content” that invades the energy reserve. [BU-806 Tracking Battery Capacity and Resistance as part of Aging]
Figure 2: Relationship of CCA and capacity of a starter battery
“How accurate are the readings,” car mechanics and battery users ask? This depends on the tester and the test methods used. Spectro™ with a generic matrix provides a correct CCA predictability of about 90 percent and capacity is about 80 percent.
As part of product qualification, a German luxury car manufacturer performed a comparison test using Spectro™ and AC conductance methods side-by-side. With a dedicated matrix, Spectro™ achieved correct CCA predictability of 97% and capacity came in at 87 percent. In this same test, the correct CCA predictability of the AC conductance produced was less than 60 percent.
Such seemingly low accuracy may come as a surprise but the user must appreciate that a battery fault can only be diagnosed if measurable symptoms are present. A new battery that has not yet been fully formatted, has been in storage for a long time, or has a low charge can give false results. For unknown reasons, reversible (soft) sulfation does not display readable symptoms with Spectro™ and the battery receives a clean bill of health in spite of low capacity. Only permanent (hard) sulfation that can no longer be corrected agrees with the result. (See BU-804b: Sulfation and How to Prevent it.) CCA and capacity estimations are most effective with “working” batteries.
Batteries are marked with capacity in Ah (or RC in minutes) and starter batteries also include CCA. These published values are taken earnestly but they may not be correct. In fact, the CCA of some starter batteries are higher or lower than indicated and few consumers verify the readings, especially on a starter battery. Such deviances add to test discrepancies.
State-of-charge (SoC) also affects the accuracy. Figure 3 compares CCA readings taken with AC conductance and Spectro™ at different SoC. Both readings decline with SoC, but since most batteries hover at about 70 percent when the car is brought in for service, the CCA readings between the two methods appear similar.
Figure 3: CCA accuracy on state-of-charge
The Spectro CA-12 provides stable CCA readings between a SoC of 100–40% (red); the values on AC Conductance drop rapidly with SoC (blue).
Figure 4 illustrates CCA readings as a function of SoC and battery performance. The CCA in Battery A with 100 percent capacity stays steady down to a SoC of 10 percent; Battery B with 37 percent capacity starts to show instabilities at a SoC of about 40 percent, and Battery C with only 22 percent capacity provides uncertain results. This test demonstrates that a health battery provides clear and measurable symptoms where the indicators of a weak battery are muddled.
Figure 4: CCA accuracy in relation to battery condition and SoC
The battery condition governs accuracy. Battery A (100%) is accurate to 10% SoC; Battery B (37%) to 40% SoC. Battery C (22%) delivers unstable results. Test condition: Batteries are discharged at 20A. CCA is measured every 10 min with Spectro™
No single instrument can evaluate all battery anomalies and rapid testing only provides rough estimation. A micro-short in a cell, for example, can only be identified by applying a load after a rest period or checking the specific gravity of the electrolyte. Rapid-testing might pass the battery as good because a charge covers up the anomaly.
All test methods provide outliers and no clear accuracy specifications can be given. Certain defects are easier to detect than others. As there is a high probability that it will not rain in the Mohave Desert today, forecasting rain in London is more complex. There are no ideal battery test methods but electrochemical impedance spectroscopy has room to expand.
Last updated 5/20/2015
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