BU-914: Battery Test Summary Table

Battery users want instant readout pertaining to battery state-of-health

A battery resembles a living organism that cannot be measured, only estimated to a varied degree of accuracy based on available symptoms. This simulates a doctor examining a patient by taking multiple tests and applying the law of elimination. Rapid-test methods for batteries have been lagging behind other technologies; complexity and uncertain results when testing outliers are the reasons for the delay.

Cadex realizes the importance of battery diagnostics and has made notable advancements in rapid-test technologies. These developments form the building blocks for Diagnostic Battery Management (DBM), a new direction innovative companies are pursuing in the care and maintenance of batteries. Rather than inventing another new super battery, DBM is vital to assure reliability of current battery systems by monitoring capacity, the leading health indicator, along with other parameters. 

Capacity represents energy storage, internal resistance relates to current delivery, and self-discharge reflects mechanical integrity. All three properties must be met to qualify a battery. In addition to these static characteristics, a battery has different of state-of-charge (SoC), dynamic characteristics that effect battery performance and complicate rapid-testing.

Well-developed battery test technologies must recognize all battery conditions and provide reliable results, even if the charge is low. This is a demanding request as a good battery that is only partially charged behaves in a similar way to a faded pack that is fully charged.

Test methods range from taking a voltage reading, to measuring the internal resistance by a pulse or AC impedance method, to coulomb counting, and to taking a snapshot of the chemical battery with Electrochemical Impedance Spectroscopy (EIS). Capacity estimations by deciphering the chemical battery are more complex than digital monitoring by coulomb counting. Digging into the chemical battery involves proprietary algorithms and matrices that function as lookup tables similar to letter or face recognition.

Voltage and internal resistance do not correlate with capacity and fail to predict the end of battery life effectively, especially with Li-ion and lead acid systems. The truth lies in the chemical battery. A digital measurement alone is subject to failure because the chemical symptoms are not represented.

Here are the most common battery test methods:

Voltage Battery voltage reflects state-of-charge in an open circuit condition when rested. Voltage alone cannot estimate battery state-of-health (SoH).
Ohmic test Measuring internal resistance identifies corrosion and mechanical defects when high. Although these anomalies indicate the end of battery life, they often do not correlate with low capacity. The ohmic test is also known as impedance test.
Full cycle A full cycle consists of charge/discharge/charge to read the capacity of the chemical battery. This provides the most accurate readings and calibrates the smart battery to correct tracking errors, but the service is time consuming and causes stress.
Rapid-test Common test methods include time domain by activating the battery with pulses to observe ion-flow in Li-ion, and frequency domain by scanning a battery with multiple frequencies. Advanced rapid-test technologies require complex software with battery-specific parameters and matrices serving as lookup tables.
BMS Most Battery Management Systems estimate SoC by monitoring voltage, current and temperature. BMS for Li-ion also counts coulombs.
Coulomb counting The Full Charge Capacity (FCC) of a smart battery provides coulomb count that relates to SoH. FCC readout is instant but the data gets inaccurate with use and the battery requires calibration with a full cycle.
Read-and-Charge A charger featuring RAC technology reads battery SoC with a proprietary filtering algorithm and then counts the coulombs to fill the battery. RAC requires a onetime calibration for each battery model; cycling a good pack provides this parameter that is stored in the battery adapters. RAC technology is a Cadex development.
SOLI The State-of-Life-Indicator estimates battery life by counting the total coulombs a battery can deliver in its life. A new battery starts at 100%; delivered coulombs decrease the number until the allotment is spent and a battery replacement is imminent. The full scale is set by calculating the coulomb count of 1 cycle based on the manufacturer’s specifications (V, Ah) and then by multiplying the number with the given cycle count. Developed by Cadex, SOLI can be used in wheelchairs, medical devices, traction and UPS, installed when new or added as retrofit. Wireless connectivity provides fleet management.

Reliable results are only possible when robust symptoms are present. This is not always possible, especially with unformatted lead acid batteries or packs that had been in storage. A good battery pulled form service generally provides solid symptoms with good accuracy; readings from a weak battery can be muddled with inconsistent results. Reliable measurements are impossible if the symptoms are vague or not present, which is the case if the battery has turned into a potato. This fools the system and the battery becomes an outlier. Well-developed rapid-test methods should correctly predict 9 batteries out of 10. EIS has the potential to advance further and surpass other technologies.

Table 1 summarizes test procedures with the most common battery systems. Lead acid and Li-ion share communalities in keeping low resistance under normal condition. Exceptions are heat fail and mechanical faults that raise the internal resistance and a battery replacement ahead of time. Nickel-cadmium and nickel-metal-hydride, and in part also the primary battery, reveal the end-of-life.

Battery test methods for common battery chemistries
Table 1: Battery test methods for common battery chemistries. Lead acid and Li-ion share communalities by keeping low resistance under normal condition; nickel-based and primary batteries reveal end-of-life by elevated internal resistance.

At a charge efficiency of 99 percent, Li-ion is best suited for digital battery estimation. This helps in BMS design by enabling capacity estimation with coulomb counting. While the readings are instant, occasional calibration is needed to correct the tracking error that occurs with random battery usage. In comparison, nickel-based batteries have low charge efficiency and high self-discharge, deficiencies that would skew digital tracking. Under the right conditions and moderate temperature, lead acid batteries are reasonably efficient but not quite good enough to use coulomb counting effectively.

Cold temperature reduces the efficiency of all batteries and affects rapid-testing. Although a battery may function below freezing, charge acceptance is reduced and charge times must be prolonged by lowering the current. Some chargers do this automatically; if not certain, do not charge Li-ion batteries below freezing.


Mark Twain said: “I didn't have time to write a short letter, so I wrote a long one instead.” Efforts to make something “short” also apply in the development of Diagnostic Battery Management. Adding features is easy, but also keeping the price affordable is a challenge. Switching to new microcontrollers with added intelligence and simplifying assembly enables new product features that were unthinkable a few years ago. But as Mark Twain hinted, making something economical takes time.

The objective is to advance the battery into a reliable, safe, cost efficient and environmentally sustainable power source. This requires systems that operate in the background with minimal overhead and little extra cost. The goal is to fully utilize each battery and make state-of-health transparent to the user and fleet supervisor. This can make unexpected battery failures a thing of the past.

Last updated 2017-04-26

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