The global market for End of Life Lithium-Ion Batteries is growing exponentially to satisfy the needs of electric mobility and clean energy technologies. Reusing or repurposing these batteries could ensure sustainability and keep the excessive demands of raw materials in check. However, a strong commitment and trust from the various stakeholders is necessary to build such circular industrial systems. In this paper, a thorough analysis of practices and regulations allowed us to highlight the actors and processes involved in the life cycle of repurposed Lithium-Ion Batteries (LIBs). This led us to propose a conceptual framework describing a generic organization for LIB repurposing. LIB State of Health and diagnosis estimations, which can be carried out with data from LIB passports, are also underlined as essential for the functioning of the organization. This was discussed and implemented on a real case of LIBs used as a power source for electric heaters after their first life in a mobility application.

To date, fault diagnosis is more and more studied due to its essential role in equipment availability and human safety. This paper proposes a model-based method for event-discrete systems, using the characteristic times in its normal behavior. Indeed, a failure can be detected is these times are not respected. Then the failure is isolate using fault signature analysis. A failure can be distinguished from each other by a set of variables, called diagnostic variables. The choice of these particular variables is essential to diagnose efficiently a system. The diagnosis performance can also be quantified through two parameters : the detection and isolation times.

The paper deals with the definition of procedure that enables one to determine, for a given plant, if all faults can be detected and located after a finite sequence of observable events. More formally, the diagnosability is the property that every fault can be correctly detected from the observable events of the system after its occurrence no later than a bounded number of events. In this paper, the diagnosability problem of Discrete Event Systems (DESs) is studied. As modeling tool, finite-state automaton in an event-based framework is used. A necessary and sufficient condition of diagnosability of such systems is proposed. The results proposed in this paper allow checking the diagnosability of discrete event systems in an efficient way, i.e. in polynomial time.