PREDICTION OF ELECTRIC VEHICLES CHARGING: A (MAX, +) ALGEBRABASED APPROACH

Nowadays, one of the most major issues for electric vehicles (EVs)concerns their charging. In our previous research works in thisfield, we have proposed a predictive charging policy aiming toreduce waiting times of EVs within charging stations. In this paperwe continue this effort by developing a formal model to describeand study the charging process behavior. Based on this model, theobjective consists of serving a large number of charging demandswith a minimum of time tacking into account many parameters of thesystem such as the location of EVs, their consumption and theirreal needs in terms of energy. Our developed model is described asstates/transitions occurring sequence in a chronological order. Itbased on Petri net model in which each event execution requires thetime amount. Managing charging demands is ensured by acollaborative platform based on communication technologies andgeopositioning techniques. The behavior of this platform isrepresented and access control of registered EVs is also addressed.Some qualitative properties of charging system such asreachability, deadlock-free and synchronization are checked andvalidated using Petri net theory. Afterwards, we combine Petri netswith (Max, +) equations in order to express the analytic behaviorof the process and, to analyze and validate some of itsquantitative properties.

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