The broad adoption of battery systems is increasing the complexity and size of lithium-ion battery packs. This increased complexity is raising the concerns related to the safety of lithium-ion batteries. In this context, this poster presents the development and validation of an integrated fault diagnosis identification method for lithium-ion battery packs. The algorithm is based on the aggregation of complementary state-of-the-art methods, allowing the identification of different types of faults with a single algorithm. The poster shows how the proposed integrated solution has been validated using a synthetic dataset. In this way, the results show that the aggregation of methods allows an increased identification rate of the faults.