Due to the complexity of real driving and operating conditions of Battery Electric Vehicles, it
is challenging to accurately estimate the remaining driving range of the vehicle. Relying only …

Energy consumption modeling for electric vehicles is conducive to achieving eco-driving
optimization and alleviating driver 'range anxiety'. However, it remains challenging due to …

The transport sector is one of the most polluting sectors globally, battery electric vehicles
(BEVs) are deemed as one alternative to improve the environmental efficiency for the …

For multi-energy storage vehicles, the performance of online predictive energy management
strategies largely relies on the length and effective utilization of predictive information. In this …

Connected and automated vehicles (CAVs) are expected to provide enhanced safety,
mobility, and energy efficiency. While abundant evidence has been accumulated showing …

Accurate estimation of the power consumption of electric vehicles in the future driving route
will help to reduce the user's range anxiety, which results from short all electric range of …

Battery and energy management methodologies have been proposed to address the design
challenges of driving range and battery lifetime in electric vehicles (EVs). However, the …

Remaining driving range (RDR) research has continued to consistently evolve with the
development of electric vehicles (EVs). Accurate RDR prediction is a promising approach to …

Battery-powered electric vehicles (EVs) have a limited on-board energy storage and present
the problem of driving mileage anxiety. Moreover, battery energy storage density cannot be …

This paper presents a novel probabilistic data-driven approach to trip-level energy
consumption estimation of battery electric vehicles (BEVs). As there are very few electric …