Title
Remaining Driving Range Estimation Framework for Electric Vehicles in Platooning Applications
Abstract
Range anxiety has been one of the largest issues for battery electric vehicle (BEV) adoption. Accurate estimation of EV remaining driving range (RDR) can alleviate this issue by informing drivers of appropriate timings and energy needed to propel their EVs to meet their needs, particularly during a long trip. Vehicle platooning with a short inter-vehicle distance has demonstrated significant energy saving benefits on high-way operation by reducing aerodynamic drag force. On the other hands, vehicle platooning also introduces uncertainties to aerodynamic drag coefficient estimation and model-based RDR estimation algorithms. Therefore, it is a challenging task to precisely estimate the RDR for EVs in vehicle platoon. This work proposes a novel EV RDR estimation method that integrates the real-time estimation of aerodynamic drag coefficient and the operation mode from advanced driver-assistance systems (ADAS) or platooning into a physics-based EV model to improve RDR estimation accuracy in highway operation. Simulation results demonstrate that the proposed estimation method can potentially reduce EV RDR estimation errors when compared to the baseline EV RDR estimation method which is based on historical data.
Year
DOI
Venue
2021
10.23919/ACC50511.2021.9482698
2021 American Control Conference (ACC)
Keywords
DocType
ISSN
platooning applications,high-way operation,aerodynamic drag force,aerodynamic drag coefficient estimation,physics-based EV model,remaining driving range estimation framework,battery electric vehicle,BEV,short intervehicle distance,energy saving benefits,model-based RDR estimation algorithms,advanced driver-assistance systems,ADAS
Conference
0743-1619
ISBN
Citations 
PageRank 
978-1-7281-9704-3
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Maxavier Lamantia100.68
Zifei Su200.34
Pingen Chen300.68