The reuse, usually for stationary applications, of batteries used on vehicles – known as 2nd-life batteries – is a concept that is spreading thanks to the exponential increase in electric vehicles. 2nd-life has both economic and environmental benefits. However, to enable 2nd-life it is necessary to resolve some problems regarding the diagnostics and management of used batteries. 2nd-life batteries are, in fact, partially aged and often their cells are not homogeneous. In order to create a 2nd-life Storage System (SS), costly tests on the cells would therefore be necessary to re-evaluate their performance and integrate active Battery Management Systems (BMSs) capable of managing inhomogeneities. The research activity led to the creation of alternative solutions that reduce the cost of enabling 2nd-life batteries.
In order to monitor the battery without carrying out characterization tests, an algorithm called Voltage Dynamic-Based SoC Estimation (VDB-SE) was developed based on Machine Learning techniques, which allows for the estimate of the main battery status indicators, such as state of charge and state of health. The results of the validation tests carried out on a real 30 kW SS showed an average error of less than 5% on the state of charge estimate and less than 2% on the capacity estimate, which is useful to assess the state of health. Various sensitivity analyses carried out in a simulation environment demonstrated good robustness of the algorithm as the configuration changes (storage technology, type of application, algorithm settings).
As far as the management of a 2nd-life battery is concerned, the validation tests of a 2nd-life SS prototype managed by an active BMS, started during the previous year, continued and came to an end. The tests proved how the use of an active BMS can improve the performance of a battery composed of 2nd-life modules, and of the entire SS, by appropriately managing non-homogeneous modules. The results show that the BMS allows for a 39% increase in the energy that can be discharged from the battery compared to an SS without an active BMS. Furthermore, the use of the BMS also reduces the degradation rate.3131