On optimal mission planning for vehicles over long distance trips

This thesis proposes a mission planner for vehicles over long-distance trips, for finding the optimal trade-off between trip time, energy efficiency, and driver comfort, subject to road information, traffic situations, and weather conditions. The mission planner consists of three components, i.e. logistics planner, eco-driving supervisor, and thermal and charging supervisor. The logistics planner aims at optimising the mission start and/or finish time by minimising energy consumption and trip time. The eco-driving supervisor computes the velocity profile of the driving vehicle, by optimising the energy consumption and penalising driver discomfort. To do so, an online-capable algorithm has been formulated in a model predictive control framework, subject to road and traffic information, and the pre-optimised mission start and/or finish time. This algorithm is computationally efficient and enables the driving vehicle to adapt and optimally respond to predicted disturbances within a short amount of time. Eco-driving has also been achieved for a vehicle confronted with wind, by applying stochastic dynamic programming method. The thermal and charging supervisor regulates battery temperature and state of charge by coordinating the energy use of different thermal components. Within the thermal and charging supervisor design, a heat pump has been included for waste heat recovery purposes. Also, the charging stops have been optimally planned, in favour of energy efficiency and trip time. The performance of the proposed algorithms over a road with a hilly terrain is assessed using simulations.

• Record URL:
  • https://research.chalmers.se/publication/533947/file/533947_Fulltext.pdf
• 
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9789179057886
• Authors:
  • Hamednia, Ahad
• Publication Date: 2023

Language

• English

Media Info

• Pagination: 251
• Serial:
  • Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie
  • Issue Number: 5254
  • Publisher: Chalmers University of Technology, Sweden
  • ISSN: 0346-718X

Subject/Index Terms

• TRT Terms: Ecodriving; Electric vehicle charging; Electric vehicles; Energy; Mathematical models; Nonlinear systems; Stochastic processes; Theses
• ITRD Terms: 6473: Algorithm; 984: Charging (electric vehicle); 1872: Ecodriving; 1282: Electric vehicle; 213: Energy consumption; 203: Energy efficiency; 6473: Equation; 6473: Formula (math); 6482: Non linear; 6574: Stochastic process; 8597: Thesis
• Subject Areas: Energy; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01910029
• Record Type: Publication
• Source Agency: Swedish National Road and Transport Research Institute (VTI)
• ISBN: 9789179057886
• Files: ITRD, VTI
• Created Date: Feb 27 2024 2:25PM