Elsevier

Journal of Power Sources

Volume 262, 15 September 2014, Pages 129-135
Journal of Power Sources

Temperature dependent ageing mechanisms in Lithium-ion batteries – A Post-Mortem study

https://doi.org/10.1016/j.jpowsour.2014.03.112Get rights and content

Highlights

  • The ageing behaviour of cycled cells is tested in the range of −20 °C to +70 °C.

  • Temperature dependent ageing mechanisms are found by an Arrhenius plot.

  • The different ageing mechanisms are proven by Post-Mortem analysis.

  • The reason for the different mechanisms is found by tests with reference electrodes.

Abstract

The effects of temperatures in the range of −20 °C to 70 °C on the ageing behaviour of cycled Lithium-ion batteries are investigated quantitatively by electrochemical methods and Post-Mortem analysis. Commercial 18650-type high-power cells with a LixNi1/3Mn1/3Co1/3O2/LiyMn2O4 blend cathode and graphite/carbon anode were used as test system. The cells were cycled at a rate of 1 C until the discharge capacity falls below 80% of the initial capacity. Interestingly, an Arrhenius plot indicates two different ageing mechanisms for the ranges of −20 °C to 25 °C and 25 °C to 70 °C. Below 25 °C, the ageing rates increase with decreasing temperature, while above 25 °C ageing is accelerated with increasing temperature. The aged 18650 cells are inspected via scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), inductively coupled plasma (ICP), measurements of electrode thickness and X-ray diffraction (XRD) after disassembly to learn more about the chemical reasons of the degradation. The effect of different temperatures on the electrode polarizations are evaluated by assembling electrodes in pouch cells with reference electrode as a model system. We find that the dominating ageing mechanism for T < 25 °C is Lithium plating, while for T > 25 °C the cathodes show degeneration and the anodes will be increasingly covered by SEI layers.

Introduction

Besides the use of Lithium-ion batteries in portable devices, they are regarded as the key technology for the next generation of vehicles [1], [2], [3] and nearly all car manufacturers have already introduced one or more vehicles that utilize electric drive systems. Apart from major advantages of this technology, such as local zero emission vehicles and independence from the oil market, there are still problems regarding the life-time of car batteries. In order to improve the long-term usability of Lithium-ion batteries, it is essential to gather more knowledge about the chemical processes that contribute to battery ageing. The state-of-health (SOH) which determines the ‘age’ of a battery is commonly defined as the discharge capacity of an aged cell compared to the discharge capacity of the same cell when it was new. An SOH <80% is commonly regarded as end-of-life (EOL) criterion for a battery. The course of SOH as function of time during the ageing process is influenced by the conditions of operation of the battery and contains information on the ageing rate of the cell if the experimental conditions are well-defined. Such defined model conditions can for example be achieved by cycling at defined temperatures [4]. In order to learn more about ageing processes on the microscopic scale, there have been several studies regarding the ageing of electrodes [5], [6], electrolyte [7], [8], [9] and separator materials [10] as well as the electrode | electrolyte interface [11], [12], [13], [14], [15]. Known ageing effects comprise Mn dissolution from the cathode [16], [17], [18], [19] and subsequent deposition on the anode [5], Mn re-deposition on the cathode [20], particle cracks [21], loss of cyclable Li [22], [23], [24], Lithium plating [25], [25], [26], [27], [28] or solid–electrolyte interface (SEI) growth [13], [14], [15], [24], [27]. It was also shown that variations of the material composition can lead to improved batteries, e.g. by using additives [29], [30] or blending of cathode materials [31], [32], [33]. Since it may take several years to reach the EOL criterion of a battery under moderate operation conditions, accelerated ageing tests are used. In such tests the batteries are put under stress for example by elevated temperatures [4], [34], [35], [36], [37], however, there is a lack of data on the ageing induced by low temperatures. The speed of ageing can quantitatively be described by ageing rates, which are contained in the capacity fade curves. After measuring ageing rates as a function of temperature, it is common practice to linearize the data by plotting ln(r) vs. 1/T, which is known as Arrhenius plot [38], [39] according to the equationr=Aexp(EakBT)with the ageing rate r, the pre-exponential factor A, the activation barrier Ea and the Boltzmann constant kB. Arrhenius theory has been used in the field of Lithium-ion batteries to determine activation barriers for ageing [36], [40] and other processes [41], [42], [43], [44]. However, it is often disregarded that the linear Arrhenius-like behaviour is only valid in certain temperature intervals. A change of the slope in an Arrhenius plot is an indication for a mechanism change [38]. Arrhenius behaviour has been observed for Lithium-ion batteries [14], [36], [45], but not over the whole temperature range which a battery electric car might be exposed to (−20 to 70 °C). In literature, ageing measurements are carried out mostly below 60 °C, since changes in the reaction mechanism are expected [4]. Only few authors performed tests at 65 °C [4], 70 °C [46] or 85 °C [47]. It depends on the battery chemistry and design at which temperature a change of the ageing mechanism occurs. Results on 18650 cells with LixNi1/3Mn1/3Co1/3O2/LiyMn2O4 blend cathodes have been published before, however, different ageing conditions and electrochemical instead of Post-Mortem analysis was applied [24], [27], [48].

In this paper, we use temperatures in the range of −20 °C to 70 °C to accelerate the ageing of 18650 cells with blend cathodes under cycling conditions. By utilizing an Arrhenius plot, we find two different ageing mechanisms depending on the ageing temperature. The chemical reasons for the degradation mechanisms are identified by Post-Mortem analysis of the 18650 cells and by polarization measurements with pouch cells with reference electrode.

Section snippets

Experimental

The investigated commercial batteries used in this work have an initial capacity of 1.5 Ah and contain LixNi1/3Mn1/3Co1/3O2/LiyMn2O4 blend cathodes and graphite/carbon anodes. All tested cells in the present study were very similar in mass, open circuit voltage, internal resistance and capacity at SOH = 100%, qualifying them for systematic ageing tests [48]. To compensate the small variations in the capacities and internal resistances of the new batteries, both values are relating to those of

Un-aged commercial 18650 cells

First, the un-aged 18650 batteries were characterized, in order to compare the results with those from the aged cells. ICP measurements showed a 1:1 ratio for the LixNi1/3Mn1/3Co1/3O2:LiyMn2O4 blend. The chemical composition of single particles LixNi1/3Mn1/3Co1/3O2 was determined by EDX point spectra to be 1:1:1 under consideration of the excitation radius and within the error bars. The anode consists of spherical graphite and carbon particles (Fig. 1a). For the anode material, the blend ratio

Conclusions

We tested commercial 18650 cells with LixNi1/3Mn1/3Co1/3O2/LiyMn2O4 blend cathodes and graphite/carbon anodes. The cells were cycled in a temperature range between −20 °C and 70 °C until an SOH limit of ∼80% was reached. An Arrhenius plot reveals two different ageing mechanisms below and above 25 °C. Below 25 °C, we find that the predominant ageing mechanism is plating of metallic Lithium on the anodes and subsequent reaction with the electrolyte, leading to loss of cyclable Lithium. The

Acknowledgement

The authors would like to thank D. Rosato and N. Dorsch from Robert Bosch GmbH for providing the cells within the common research project (ReLiOn, contract no. 03X4619C), funded by the German Federal Ministry of Education and Research (BMBF) and managed by the Project Management Agency Forschungszentrum Jülich (PTJ). We thank Gerda Dörfner for SEM/EDX and Barbara Zwikirsch/Gisela Arnold for ICP measurements. The responsibility for this publication rests with the authors.

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