A new battery starts at 100% delivered coulombs decrease the number until the allotment is spent and a battery replacement is imminent. The State-of-Life-Indicator estimates battery life by counting the total coulombs a battery can deliver in its life. RAC requires a onetime calibration for each battery model cycling a good pack provides this parameter that is stored in the battery adapters. FCC readout is instant but the data gets inaccurate with use and the battery requires calibration with a full cycle.Ī charger featuring RAC technology reads battery SoC with a proprietary filtering algorithm and then counts the coulombs to fill the battery. The Full Charge Capacity (FCC) of a smart battery provides coulomb count that relates to SoH. Most Battery Management Systems estimate SoC by monitoring voltage, current and temperature. Advanced rapid-test technologies require complex software with battery-specific parameters and matrices serving as lookup tables. This provides the most accurate readings and calibrates the smart battery to correct tracking errors, but the service is time consuming and causes stress.Ĭommon 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. The ohmic test is also known as impedance test.Ī full cycle consists of charge/discharge/charge to read the capacity of the chemical battery. Although these anomalies indicate the end of battery life, they often do not correlate with low capacity. Measuring internal resistance identifies corrosion and mechanical defects when high. Voltage alone cannot estimate battery state-of-health (SoH). Here are the most common battery test methods:īattery voltage reflects state-of-charge in an open circuit condition when rested. A digital measurement alone is subject to failure because the chemical symptoms are not represented. 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. Digging into the chemical battery involves proprietary algorithms and matrices that function as lookup tables similar to letter or face recognition. Capacity estimations by deciphering the chemical battery are more complex than digital monitoring by coulomb counting. 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). 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. Well-developed battery test technologies must recognize all battery conditions and provide reliable results, even if the charge is low. 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. All three properties must be met to qualify a battery. 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.Ĭapacity represents energy storage, internal resistance relates to current delivery, and self-discharge reflects mechanical integrity. 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. Rapid-test methods for batteries have been lagging behind other technologies complexity and uncertain results when testing outliers are the reasons for the delay.Ĭadex realizes the importance of battery diagnostics and has made notable advancements in rapid-test technologies. This simulates a doctor examining a patient by taking multiple tests and applying the law of elimination. This growing dependency on batteries requires advancements in diagnostics to observe capacity loss to maintain reliability as the capacity declines, identify anomalies to prevent catastrophic failures, and predict the end of battery life when the battery fades to a set capacity threshold.Ī battery resembles a living organism that cannot be measured, only estimated to a varied degree of accuracy based on available symptoms. From basic Voltage to Electrochemical Impedance Spectroscopyįrom 2013 to 2020, experts predict a 3.7 fold increase in the demand of lithium-ion batteries.
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