However, the fact that the OCV–SOC isĭependent on ambient temperature and can result in errors in battery SOC estimation. A widely used method to estimate SOC is open-circuit voltage (OCV). Optimal charge/discharge control of batteries. The data for the tests performed is available below for download.Īmbient temperature is a significant factor that influences the accuracy of battery SOC estimation, critical for remaining driving range prediction of electric vehicles (EVs) and Therefore, the incremental OCV test is recommended for predetermining the OCV-SOCs forīattery SOC online estimation in BMSs. The comparison results show that estimator 2(based on the incremental OCV test) has higher tracking accuracy and is more robust against varied loading conditionsĪnd different initial values of SOC than estimator 1 (based on the lowcurrent OCV test) with regard to ambient temperature. Other three for estimator performance evaluation. In addition, four dynamic tests are presented, one for estimator parameter identification and the We conducted an experiment where these two OCV tests are run at three different temperatures and based on which, two SOC estimators are compared andĮvaluated in terms of tracking accuracy, convergence time, and robustness. Which is an important element of the SOC estimation technique Low-current OCVĪnd Incremental-current OCV tests are two common methods to observe the OCV-SOC relationship, Testing and battery is carefully described, the complex relationships between cell design, chemistry, and usage conditionsīattery state of charge (SOC) estimation is a crucial function of battery management systems (BMSs), since accurate estimated SOC is critical to ensure the safety and reliability of electric vehicles.Ī widely used technique for SOC estimation is based on online inference of battery open circuit voltage (OCV). If all of this data can be put into one place and the type of This kind of testing would need to involve large quantities of dataįor many different types of batteries and usage conditions. Overcome with a brute strength approach to testing. Kind of component or system (e.g., sample size, statistical significances, influence of design parameters) may only be The complexities of battery life-cycle testing, compounded by the typical challenges of life-cycle testing for any Include rest times may be reporting premature failures. Therefore, life-cycle testing that does not Capacity fading after a given discharge cycle may not be permanent.Īllowing a battery to rest will result in a regeneration of lost capacity. Regeneration phenomenon also needs consideration. Therefore, it becomes difficult to find meaningful load vs. Increasing operational stresses (e.g., temperature or current rate) on batteries accelerates failure but not withoutĬhanging the failure mechanisms. This is a blessing for consumers,īut a curse for reliability researcher because it may take several months or years before failure testing is complete.Īdding to the difficulty of life-cycle testing is the lack of accelerated test methods available for batteries. Technology has reached a point where batteries are achieving thousands of cycles. Provides a useful baseline for comparison against more complex discharge profiles. The data generated from this type of testing The logical starting point for most battery life-cycle testing is to apply a constant current/voltageĬharging protocol and then discharge under a constant rate.
Testers and the complexity and resources needed for building robust charge/discharge systems with independent channels,
However, due to the cost of commercial battery Many Institutions are conducting their own battery life-cycle testing. We believe that advancement in the field of lithium-ion battery research can be accelerated through collaboration. Use of this data for publication purposes should include references to the CALCE article(s) that describes the experiments conducted for generating the data. If you are interested inĬontributing to the battery data collective, please contact Prof. A description of each cell and each test is presented below. The CALCE battery group would like to kick off this collaborative effort by providing baseline cycle-life dataįor cells from two different lots.
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