Methods and Competencies - Ageing Tests

A precise prediction of the lifetime in certain applications and an identification of the major ageing processes is a necessary prerequisite for the optimisation of battery systems and battery technologies. Reliability, safe and economic system operation requires clear indications on the estimate lifetime and also on the changes in the battery performance within the lifetime.

Cycle lifetime and calendar lifetime can be distinguished. The cycle lifetime is influenced by all factors and mechanisms, which are related to the stress during operation, mainly charge and discharge cycles with a certain depth of discharge. The calendar lifetime summarises the ageing effects and processes, which occur without any operation of the battery system. Typical processes which occur even in rest periods are corrosion, re-crystallisation or self-discharge processes. The real battery lifetime is a combination between cycle lifetime and calendar lifetime, which depends mainly on the application profile of the battery. The employed application or rather the load profile determines which ageing mechanism is the dominating one.

In order to investigate and analyse both lifetimes independently from each other sophisticated systematic accelerated ageing tests are necessary. Cycle lifetime is evaluated by employing well-defined charge/ discharge pulse patterns at different battery temperatures and different states of charge. During calendar lifetime tests the battery is aged only by the presence of a elevated temperature in open-circuit operation. The elevated temperature accelerates the ageing processes with an exponential dependency.

Nevertheless, accelerated ageing tests as described before hand hardly can give a precise statement concerning the lifetime in a certain application. For lead-acid batteries, as an example, very small currents and rest periods between charging and discharging periods, cause significant ageing. In accelerated tests these conditions can be hardly represented. But accelerated ageing test can show differences between different products and in combination with sophisticated simulation tools - which include e.g. thermal modelling - an extrapolation to the lifetimes applications under different operating conditions can be achieved. This is a very important active research topic.

Beside periodical electrical tests (capacity, power capability, cranking capability, efficiency, internal resistance, open-circuit voltage characteristic) and the analysis of the test data, impedance spectroscopy is used in order to determine the battery’s state during ageing tests and to identify ageing phenomena. Based on these information it is possible to draw conclusions on the battery’s state of health (SOH). Here a close link is given to online monitoring systems which have to determine the varying performance and state of health e.g. in vehicles. Anyhow, the lifetime of a battery pack typically is shorter than an the lifetime of an individual cell. Additional ageing processes occur in battery stacks with a high number of series connected cells. Interaction between cells can cause accelerated ageing of the battery stack. Different battery temperatures or small variations in performance parameters cause already during the production process can shorten the lifetime due to self-accelerating ageing processes. Intelligent energy management systems, single cell equalisation systems or proper thermal design of the battery pack are measures to increase the system lifetime.