PROJECT TITLE :

Drive Cycle Identification and Energy Demand Estimation for Refuse-Collecting Vehicles

ABSTRACT:

Drive cycle identification and future energy demand prediction are advantageous when developing hybrid propulsion systems. They're applicable to vehicles that are driven along the identical route every day, like busses, refuse-collecting vehicles (RCVs), or delivery vehicles. Drive cycle identification can be used to spot what power transients can be expected to arrange the facility train to operate beneath these conditions. If the energy management algorithm of a hybrid vehicle will account for future energy demand, then it can be arranged in such a manner that the non-fossil-fuel energy sources are totally depleted at the tip of the drive cycle. Given that RCVs continuously drive in similar drive cycles, a drive cycle has been modeled and its main characteristics parameterized. The model is separated into different drive cycles that are related to completely different power consumption modes. During this paper, a new methodology to spot drive cycles and therefore the energy left to end a route is proposed. The drive cycle identification is based on artificial intelligence algorithms, which have been trained and tested with real information with a median potency in drive cycle identification of over ninetypercent. The energy necessary to complete the route is predicated on vehicle energy models and statistical analysis. This technique will be employed in the daily management of fleet vehicles to switch fossil fuel by electrical energy, as is demonstrated within the proposed examples.


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