Platooning has the potential to significantly reduce fuel consumption, but with heavy duty vehicles scattered on roads driving alone, there is a need for coordination. One solution is for a vehicle to increase its speed to catch up and platoon with a preceding vehicle. This could reduce the fuel consumption of a mission, but it could also increase it if too much fuel is spent catching up. By finding the fuel consumption of catching up and platooning and comparing it to driving alone the decision of whether or not to catch up can be made. This thesis proposes a fuel-optimal algorithm based on a look-ahead controller taking future road topography into account to find the optimal trajectory and merge point when catching up to a preceding vehicle. By weighting time against fuel in the objective function, the addition of a state to keep track of time can be avoided and thus the algorithm can remain low in complexity, making it suitable for dynamic programming (DP). The DP algorithm is iterated in a forward fashion keeping track of the time-to-come for each state until it catches up to the preceding vehicle, then the platooning is simulated with a constant time gap, making it easy and fast to simulate. The algorithm is tested on real-world road topography data where it showed that taking road topography into account when choosing the merge point can have a significant fuel reduction.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-166748 |
Date | January 2020 |
Creators | Dennis, Edblom |
Publisher | Linköpings universitet, Fordonssystem |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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