| 1. |
- Eriksson, Lars, et al.
(författare)
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Look-ahead controls of heavy duty trucks on open roads - six benchmark solutions
- 2019
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Ingår i: Control Engineering Practice. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0967-0661 .- 1873-6939. ; 83, s. 45-66
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Tidskriftsartikel (refereegranskat)abstract
- A benchmark problem for fuel efficient control of a truck on a given road profile has been formulated and solved. Six different solution strategies utilizing varying degrees of off-line and on-line computations are described and compared. A vehicle model is used to benchmark the solutions on different driving missions. The vehicle model was presented at the IFAC AAC2016 symposium and is compiled from model components validated in previous research projects. The driving scenario is provided as a road slope profile and a desired trip time. The problem to solve is a combination of engine-, driveline- and vehicle-control while fulfilling demands on emissions, driving time, legislative speed, and engine protections. The strength of this publication is the collection of all six different solutions in one paper. This paper is intended to provide a starting point for practicing engineers or researchers who work with optimal and/or model based vehicle control.
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| 2. |
- Henriksson, Manne, 1987-, et al.
(författare)
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Implementation of an Optimal Look-Ahead Controller in a Heavy-Duty Distribution Vehicle
- 2019
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Ingår i: Proceedings 2019 IEEE Intelligent Vehicles Symposium (IV). ; , s. 2202-2207
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Konferensbidrag (refereegranskat)abstract
- Controlling the longitudinal movement of heavy-duty vehicles based on optimal control can be a cost-efficient way of reducing their fuel consumption. Such controllers today mainly exist for vehicles in haulage applications, in which the velocity is allowed to deviate from a constant set-speed. For distribution vehicles, which is the focus of this paper, the desired and required velocity has large variations, which makes the situation more complex. This paper describes the implementation of an optimal controller in a real heavy-duty distribution vehicle. The optimal control problem is solved offline as a Mixed Integer Quadratic Program, which yields reference trajectories that are tracked online in the vehicle. Some important steps in the procedure of the implementation are, except for designing the controller: developing a positioning system for the test track where the experiments are performed, estimating the parameters of the resistive forces, and setting the velocity constraints. Simulations show a potential of 10% reduction in fuel consumption without increasing the trip time. Experiments are then performed in a Scania truck, with the optimal solution as reference for the existing cruise control functions in the vehicle. It is concluded that in order to verify the fuel savings experimentally, the low-level controllers in the vehicle must be modified such that the tracking error is decreased.
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| 3. |
- Henriksson, Manne, 1987-, et al.
(författare)
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Optimal Freewheeling Control of a Heavy-Duty Vehicle Using Mixed Integer Quadratic Programming
- 2020
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Ingår i: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 13809-13815
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Konferensbidrag (refereegranskat)abstract
- Improving the powertrain control of heavy-duty vehicles can be an efficient way to reduce the fuel consumption and thereby reduce both the operating cost and the environmental impact. One way of doing so is by using information about the upcoming driving conditions, known as look-ahead information, in order to coast in gear or to use freewheeling. Controllers using such techniques today mainly exist for vehicles in highway driving. This paper therefore targets how such control can be applied to vehicles with more variations in their velocity. The driving mission of such a vehicle is here formulated as an optimal control problem. The control variables are the tractive force, the braking force, and a Boolean variable representing closed or open powertrain. The problem is solved by a model predictive controller, which at each iteration solves a mixed integer quadratic program. The fuel consumption is compared for four different control policies: a benchmark following the reference of the driving cycle, look-ahead control without freewheeling, freewheeling with the engine idling, and freewheeling with the engine turned off. Simulations on a driving cycle with a varying velocity profile show the potential of saving 11 %, 19 %, and 23% respectively for the control policies compared with the benchmark, in all cases without increasing the trip time. Copyright
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| 4. |
- Henriksson, Manne, 1987-, et al.
(författare)
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Optimal Powertrain Control of a Heavy-Duty Vehicle Under Varying Speed Requirements
- 2017
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Konferensbidrag (refereegranskat)abstract
- Reducing the fuel consumption is a major issue in the vehicle industry. In this paper, it is done by formulatinga driving mission of a heavy-duty truck as an optimal control problem and solving it using dynamic programming.The vehicle model includes an engine and a gearbox with parameters based on measurements in test cells. The dynamic programming algorithm is solved by considering four specifictypes of transitions: transitions between the same gear, coastingin neutral gear, coasting with a gear engaged with no fuel injection and transitions involving gear changes. Simulations are performed on a driving cycle commonly used for testing distribution type of driving. In order to make sure that the truck does not deviate too much from a normal way of driving, restrictions on maximum and minimum allowed velocities are imposed based on statistics from real traffic data. The simulations show that 12.7% fuel can be saved without increasing the trip time by allowing the truck to engage neutral gear and make small deviations from the reference trajectory.
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| 5. |
- Henriksson, Manne, 1987-, et al.
(författare)
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Optimal Speed Trajectories Under Variations in the Driving Corridor
- 2017
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Ingår i: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; , s. 12551-12556
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Konferensbidrag (refereegranskat)abstract
- The optimal speed trajectory for a heavy-duty truck is calculated using the Pontryagin's maximum principle. The truck motion depends on controllable tractive and braking forces and external forces such as air and rolling resistance and road slope. The velocity of the vehicle is restricted to be within a driving corridor which consists of an upper and a lower boundary. Simulations are performed on data from a test cycle commonly used for testing distribution driving. The data include road slope and a speed reference, from which the driving corridor is created automatically. The simulations include a sensitivity analysis on how changes in the parameters for the driving corridor influence the energy consumption and trip time. For the widest driving corridor tested, 15.8% energy was saved compared to the most narrow corridor without increasing the trip time. Most energy was saved by reducing the losses due to braking and small amounts of energy were saved by reducing the losses due to air resistance. Finally, optimal trajectories with the same trip time derived from different settings on the driving corridor are compared in order to analyse energy efficient driving patterns.
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| 6. |
- Henriksson, Manne, 1987-, et al.
(författare)
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Optimal Speed Trajectory for a Heavy Duty Truck Under Varying Requirements
- 2016
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. - : IEEE. - 9781509018895 ; , s. 820-825
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Konferensbidrag (refereegranskat)abstract
- The optimal speed trajectory for a heavy duty truck is calculated by using the Pontryagin’s maximum principle. The truck motion depends on controllable tractive and braking forces and external forces such as air and rolling resistance and road slope. The solution is subject to restrictions such as maximum power and position dependent speed restrictions. The intended application is driving in environments with varying requirements on the velocity due to e.g. legal limits and traffic. In order to limit the vehicle to a speed trajectory that follows the normal traffic flow, data from real truck operation have been analysed and used for setting upper and lower boundaries for the decelerations. To evaluate the solution, simulations have been performed on a segment of a road normally used as a distribution test cycle. Three different policies were compared where the solution adopts to free optimization, optimization following traffic flow and finally cruise control using look-ahead control. Results from the simulations show that fuel consumption and trip time can be reduced simultaneously while following the traffic flow.
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