A Data-Driven Method for Reliability Estimation of Auxiliary Power Consumption Prediction in Commercial Electric Vehicles

Description

One of the main issues concerning Battery Electric Vehicles (BEVs) is represented by range anxiety. This problem becomes crucial considering commercial vehicles equipped with electric Power Take Off (ePTO), which acts as power supplier for auxiliary loads. The paper presents a technique to estimate the reliability of power consumption prediction performed on ePTO consumption trends. Results show that the proposed algorithm balances the effects of power consumption prediction error in a more effective way with respect to a baseline solution.

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