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Fuel-Efficient Truck Platooning using Speed Profile Optimization

Sina Torabi (Institutionen för tillämpad mekanik, Fordonsteknik och autonoma system)
Gothenburg : Chalmers University of Technology, 2017.
[Licentiatavhandling]

This thesis is concerned with fuel-efficient driving strategies for heavy-duty
vehicles driving on highways with varying topography. A method for reducing
the fuel consumption of single trucks and platoons consisting of several trucks
is described and evaluated both in simulation and in real trucks. The method,
referred to as speed profile optimization (SPO), uses a genetic algorithm
to find fuel-efficient speed profiles. Using SPO, the fuel consumption of a
single truck was reduced by 11.5% (on average) relative to standard cruise
control. The method’s extension to platooning (P-SPO), reduced the fuel
consumption by 15.8% to 17.4% for homogeneous and heterogeneous
platoons (with different mass configurations), respectively, relative to the
combination of cruise control and adaptive cruise control, when applied to
road profiles of 10 km length. Furthermore, it was demonstrated that the
results obtained in the simulations are sufficiently accurate to be transferred
to real trucks.

The SPO and P-SPO methods also outperform the commonly used MPC-
based methods by a few percentage points: For single trucks, SPO outper-
formed an MPC-based approach by 3 percentage points, in a case with iden-
tical roads and similar experimental settings. Similarly, for a platoon of two
trucks, P-SPO outperformed an MPC-based approach by around 3 percent-
age points.



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Denna post skapades 2017-10-02. Senast ändrad 2017-10-02.
CPL Pubid: 252192

 

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Institutioner (Chalmers)

Institutionen för tillämpad mekanik, Fordonsteknik och autonoma system (2010-2017)

Ämnesområden

Transport
Farkostteknik
Energiteknik

Chalmers infrastruktur

Relaterade publikationer

Inkluderade delarbeten:


Truck Platooning Based on Lead Vehicle Speed Profile Optimization and Artificial Physics


Fuel consumption optimization of heavy-duty vehicles using genetic algorithms


Examination

Datum: 2017-10-23
Tid: 13:15
Lokal: Lecture room FB, Fysikgården 4, Chalmers University of Technology
Opponent: Dr. Slawomir Nowaczyk, Halmstad University, Sweden

Ingår i serie

Thesis for the degree of Licentiate - Department of Mechanics and Maritime Sciences 2017:07