Hierarchical Diagnostics and Risk Assessment for Energy Supply in Military Vehicles

Péter Földesi, László T. Kóczy, Ferenc Szauter, Dániel Csikor and Szabolcs Kocsis Szürke
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Péter Földesi: Department of Logistics and Forwarding, Széchenyi István University, 9026 Győr, Hungary
László T. Kóczy: Department of Logistics and Forwarding, Széchenyi István University, 9026 Győr, Hungary
Ferenc Szauter: Department of Logistics and Forwarding, Széchenyi István University, 9026 Győr, Hungary
Dániel Csikor: Department of Logistics and Forwarding, Széchenyi István University, 9026 Győr, Hungary
Szabolcs Kocsis Szürke: Department of Logistics and Forwarding, Széchenyi István University, 9026 Győr, Hungary

Energies, 2022, vol. 15, issue 13, 1-16

Abstract: Hybrid vehicles are gaining increasing global prominence, especially in the military, where unexpected breakdowns or even power deficits are not only associated with greater expense but can also cost the lives of military personnel. In some cases, it is extremely important that all battery cells and modules deliver the specified amount of capacity. Therefore, it is recommended to introduce a new measurement line of rapid diagnostics before deployment, in addition to the usual procedures. Using the results of rapid testing, we recommend the introduction of a hierarchical three-step diagnostics and assessment procedure. In this procedure, the key factor is the building up of a hierarchical tree-structured fuzzy signature that expresses the partial interdependence or redundancy of the uncertain descriptors obtained from the rapid tests. The fuzzy signature structure has two main important components: the tree structure itself, and the aggregations assigned to the internal nodes. The fuzzy signatures that are thus determined synthesize the results from the regular maintenance data, as well as the effects of the previous operating conditions and the actual state of the battery under examination; a signature that is established this way can be evaluated by “executing the instructions” coded into the aggregations. Based on the single fuzzy membership degree calculated for the root of the signature, an overall decision can be made concerning the general condition of the batteries.

Keywords: risk assessment; military vehicles; battery; energy supply (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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