Energy-efficient train control: From local convexity to global optimization and uniqueness

The optimal driving strategy for a train is essentially a power–speedhold–coast–brake strategy unless the track contains steep grades in which case the speedhold mode must be interrupted by phases of power for steep uphill sections and coast for steep downhill sections. The Energymiser®  device is u...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Automatica (Oxford) Ročník 49; číslo 10; s. 3072 - 3078
Hlavní autori: Albrecht, Amie R., Howlett, Phil G., Pudney, Peter J., Vu, Xuan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Kidlington Elsevier Ltd 01.10.2013
Elsevier
Predmet:
Algorithms
Applied sciences
Automation
Calculus of variations
Computer science; control theory; systems
Control theory. Systems
Devices
Energy minimization
Exact sciences and technology
Ground, air and sea transportation, marine construction
Numerical analysis
Optimal control
Optimal train control
Optimization
Railway transportation and traffic
Strategy
Switching
Trains
Calculus of variations
Optimal train control
Energy minimization
Optimal algorithm
Vehicle driving
Rail vehicle
Minimization
Global optimum
Torque measurement
Freight transportation
Global local method
Perturbation method
Optimal strategy
Optimal control
Variational calculus
Optimality condition
Optimality criterion
Rail transportation
Convexity
ISSN:0005-1098, 1873-2836
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:The optimal driving strategy for a train is essentially a power–speedhold–coast–brake strategy unless the track contains steep grades in which case the speedhold mode must be interrupted by phases of power for steep uphill sections and coast for steep downhill sections. The Energymiser®  device is used on freight and passenger trains in Australia and the United Kingdom to provide on-board advice for drivers about energy-efficient driving strategies. Energymiser®  uses a specialized numerical algorithm to find optimal switching points for each steep section of track. Although the algorithm finds a feasible strategy that satisfies the necessary optimality conditions there has been no direct proof that the corresponding switching points are uniquely defined. We use a comprehensive perturbation analysis to show that a key local energy functional is convex with a unique minimum and in so doing prove that the optimal switching points are uniquely defined for each steep section of track. Hence we also deduce that the global optimal strategy is unique. We present two examples using realistic parameter values.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2013.07.008