Lifetime Prediction of Massively Parallelized Lithium-Ion Batteries
Authors: Hust Friedrich Emanuel , Kabzinski Jan , Niessen Markus , Witzenhausen Heiko , Sauer Dirk Uwe 
Published: February 2020

Batteries need to pass several stress tests before deployment. These tests can range in complexity from seconds (short-time electrochemical impedance spectroscopy) to several years during life time estimation tests. Several publications have shown that at the end of life, the behavior of specimens can drastically differ, even though initial measurements indicate identical behavior [1,2]. The effect of highly volatile ageing in specimens can be attributed to mainly two factors, discrepancies during production batches [3] and thermal inhomogeneities [4]. Cooling and pack design can be optimized to minimize the thermal effects on ageing. However, it is still unclear to what extent the risk of a single faulty battery cell, which might impact the whole pack performance, can be minimized.
Therefore, it is useful to design tests that have a statistical significance to estimate and reduce the risk of faulty battery packs. One way to design a test setup is to create a serial connection of batteries and measure voltage over every specimen and the current in the string. This method has decisive drawbacks. Depending on the number of test subjects, the total voltage of the string might exceed extra-low voltage regulation and therefore only specialized personnel are allowed to handle the test equipment. Another drawback is that the weakest battery limits the total amount of energy that can be used. The discharge voltage limit of the weakest battery will be reached faster and therefore the measurement has to be stopped. Thus, it leads to inhomogeneities in the depth of discharge.
To overcome these disadvantages the specimens can be connected in parallel, forcing an equal voltage and a homogeneous depth of discharge. This setup is especially challenging as the current of every parallel path has to be measured separately. To research the influence on the specimen and the accuracy of the measurement, the project openBat has been established. The project openBat examines the effect of a mass parallelization on the failure rate of lithium-ion-battery-packs and creates a statistical lifetime model.
Overall, more than 600 specimens of the type NCR 18650B of Panasonic with a rated capacity of 3.20 Ah will be measured over the lifetime of the cells. The operating temperature and the cycle depth will be varied. The specimens are connected in smaller packages (30 specimens), each with its own synchronous current and voltage measurement. Each channel can be sampled at a maximum sampling rate of 1 kHz with 24 bit resolution. This enables the calculation of the impedance during the different stages of the life cycle without changing the test setup. Likewise, it is possible to measure the capacity of every single cell and the total pack. The impedance and capacity allow modeling the terminal voltage behavior and the heat generated by the batteries. To minimize temperature differences, all cells are closely fitted into an aluminum block and therefore allow temperature to be distributed evenly. The aluminum block is placed inside a temperature chamber and is actively cooled by a special cooling system.
The submission will cover the hardware setup and preliminary measurement results.
References
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[1]
Thorsten Baumhöfer, Manuel Brühl, Susanne Rothgang, and Dirk Uwe Sauer, "Production caused variation in capacity aging trend and correlation to initial cell performance," Journal of Power Sources, vol. Volume 247, pp. 332-338, February 2014.

[2]
Matthieu Dubarry, Cyril Truchot et all., "Evaluation of commercial lithium-ion cells based on composite positive electrode for plug-in hybrid electric vehicle applications," Journal of Power Sources, vol. 196, no. 23, pp. 10336 – 10343, 2011.

[3]
Shriram Santhanagopalan and Ralph E. White, "Quantifying cell-to-cell variations in lithium ion batteries," International Journal of Electrochemistry, 2012.

[4]
Sebastian Paul, Christian Diegelmann, Herbert Kabz, and Werner Tillmetz, "Analysis of ageing inhomogeneities in lithium-ion battery systems," Journal of Power Sources, 2013.

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Figure 1