Abstract
Hybrid propulsion system consists of at least two different energy sources combined with energy conversion devices. The aim of an energy management strategy is to specify the optimal distribution of energy between all the sources. However, energy and emission performances have a high degree of dependency on the hybrid strategy and the drive cycle used. That is why the results of a strategy optimised on standard test cycles can change dramatically on any particular driving pattern. To improve energy management strategy, intelligent supervision based on the recognition and prediction of the driving patterns is considered to adapt the balance of power flow.
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