Paper Info
Title
Fast stochastic non-linear model predictive control for electric vehicle advanced driver assistance systems
Abstract
Semi-autonomous driving assistance systems have a high potential to improve the safety and efficiency of the battery electric vehicles that are enduring limited cruising range. This paper presents an ecologically advanced driver assistance system to extend the functionality of the adaptive cruise control system. A real-time stochastic non-linear model predictive controller with probabilistic constraints is presented to compute on-line the safe and energy-efficient cruising velocity profile. The individual chance-constraint is reformulated into a convex second-order cone constraint which is robust for a general class of probability distributions. Finally, the performance of proposed approach in terms of states regulation, constraints fulfilment, and energy efficiency is evaluated on a battery electric vehicle.
Year
DOI
Venue
2017
10.1109/ICVES.2017.7991907
2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES)
Keywords
Field
DocType
fast stochastic nonlinear model predictive control,advanced driver assistance systems,constraints fulfilment,states regulation,probability distributions,convex second-order cone constraint,chance-constraint,energy-efficient cruising velocity profile,probabilistic constraints,real-time stochastic nonlinear model predictive controller,adaptive cruise control system,limited cruising range,battery electric vehicle efficiency,safety improvement,semiautonomous driving assistance systems
Control theory,Electric vehicle,Cruise control,Control theory,Advanced driver assistance systems,Model predictive control,Control engineering,Vehicle dynamics,Probabilistic logic,Engineering,Battery electric vehicle
Conference
ISBN
Citations 
PageRank 
978-1-5090-5678-1
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Seyed Amin Sajadi-Alamdari100.68
Holger Voos211834.98
Mohamed Darouach326142.82