Verification of Screening Conditions Related to Reuse of Used Lithium-Ion Batteries
Authors: Ohmoto Tomohisa , Abe Takeshi , Fukui Masahiro 
Published: August 2024

Abstract（Introduction, Background/Research objectives）

Lithium-ion batteries (hereinafter LIB) are becoming explosively popular around the world, and demand for electric vehicles (hereinafter EV) is particularly remarkable. However, lithium and rare metals are finite and their prices are soaring worldwide, which is hindering LIB market growth. On the other hand, technology for recycling and reusing used LIBs (EVs) is attracting attention. If safety, performance, and economic efficiency are ensured, a new market will be created and it will also contribute to the realization of a recycling-oriented society.

However, there are many challenges to actually reusing LIBs, so we will consider screening methods that enable LIB reuse in an optimal, safe, and low-cost manner.

This time, we will perform deterioration diagnosis and capacity estimation of reused LIBs whose usage history is unknown, and construct assembled batteries. The battery is actually installed in an EV, driven, and the battery status monitored. We will devise combinations of assembled batteries and verify the accuracy required for screening in order to achieve both performance and economy.

Keywords

reused LIB, BMS, LIB screening, EV

Proposed approach

Up until now, we have been able to obtain satisfactory results with battery packs that have taken time to ensure that battery deterioration and capacity are as consistent as possible. However, this time, we purposely created an assembled battery by adding batteries with different deterioration conditions and different capacities, and monitored what kind of behavior and performance changes occur when installed and operated in an EV. We will verify these results and provide feedback to the screening method.

Materials and methods

First, we screened 100 LIB modules taken from an EV that had traveled 100,000 km. The screening method involves estimating capacity using a charger/discharger manufactured in-house and diagnosing deterioration by measuring internal resistance. These LIBs will form a 12-module assembled battery in three patterns and will be installed in a converted EV manufactured in-house. The status of the onboard LIB will be remotely monitored and logged using our own BMS with IoT functionality, and statistical verification will be performed.

The following three patterns are used for the 12-module assembled battery configuration.

condition A: Match all capacitance and internal resistance.

condition B: 1 module capacity is low.

condition C: High internal resistance of 1 module.

The capacity of the entire battery pack was taken as the average capacity of the installed batteries. 100% SOC was defined as an average voltage of 4.2V, and 0% was defined as an average voltage of 3.2V. Further, the lower limit voltage of each cell is set to 3.2V, and if the OCV of even one cell falls below the lower limit voltage, it is assumed that the battery is used up and the running test is terminated.

Results

The pack voltage, SOC, and standard deviation when running from SOC 100 to 90% to 5 to 0% are shown in Fig. 1 to 3. The standard deviation was used as an index for observing voltage variations among the 24 cells. Only in the case of condition A, the battery capacity could be used up until the SOC reached 0%, but in the cases of B and C, the battery capacity could not be used up because some cells had a voltage lower than the lower limit voltage when the SOC was 4%. Under all conditions, the variation in each cell voltage tends to increase during acceleration/deceleration (charging/discharging) and at low SOC (20% or less), but we observed a large difference in the magnitude of the variation and the focusing value.

Discussion and conclusion

In the case of condition A, the fluctuation and dispersion of the pack voltage are small, and the focusing time and focusing value when the pack voltage varies are also short and small. In the case of condition B, although the pack voltage fluctuation was large, the variation was slightly increased compared to condition A, and the convergence time and convergence value were also slightly increased. Condition C had large fluctuations and dispersions in the pack voltage, and the convergence time when the dispersion occurred was also long and large. From these results, it can be said that the important condition to consider during screening is to match the capacity of the batteries. This result not only improves the accuracy of screening, but also has the potential to increase the reuse rate of used batteries.

Figure 1