| 1. |
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| 2. |
- Askerdal, Mikael, 1975, et al.
(författare)
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Development of simplified air drag models including crosswinds for commercial heavy vehicle combinations
- 2024
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Ingår i: Vehicle System Dynamics. - 1744-5159 .- 0042-3114. ; 62:5, s. 1085-1102
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Tidskriftsartikel (refereegranskat)abstract
- Accurate range prediction requires good knowledge of the prevailing wind conditions and how they affect the energy consumption of the ego vehicle. A few different simplified vehicle air drag models that explicitly include the effect from crosswinds are presented and compared through some objective criteria. The models are developed from the normal air drag equation where the effect from wind is implicit and therefore often forgotten or neglected. The purpose is to find a low-complexity model complementing CFD models and wind tunnel tests, that can be used for range estimation and predictive energy management algorithms. To simplify online estimation, a requirement is that the air drag models only contain a few tuning parameters. The models are validated against CFD calculations for a few vehicle combinations and the best models show good accuracy for air attack angles up to at least 60 degrees. It is shown that the parameters of the simplified models can loosely be connected to some basic geometrical attributes of a vehicle combination so it should be possible to give at least a rough estimate of the parameters of a simplified model based on these geometrical attributes. This is useful for making a first estimate of the aerodynamic properties of a vehicle combination after major changes in the exterior, e.g. when adding a trailer. It also highlights that the size and the shape of the vehicle side may be mainly responsible for the high longitudinal air drag sensitivity to crosswinds for large vehicle combinations.
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| 3. |
- Askerdal, Mikael, 1975, et al.
(författare)
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Motion resistance modelling and validation in winter conditions with varying air drag
- 2024
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Ingår i: Vehicle System Dynamics. - 1744-5159 .- 0042-3114. ; In Press
-
Tidskriftsartikel (refereegranskat)abstract
- Range prediction is vital for battery electric vehicles, and the main source of errors in range prediction is often the uncertainty in motion resistance. Rig and wind tunnel measurements can be used to find the motion resistance of a specific vehicle combination under specified weather conditions. However, real-life variation of the operating conditions of heavy-duty vehicles makes testing impractical. This paper proposes and validates a model of motion resistance with parameters adapted to actual road weather conditions. The model is validated in winter conditions with varying wind, using a vehicle equipped with a wind sensor. The results show that the proposed model captures the motion resistance with high accuracy. Results also indicate that it is crucial to take weather effects into account when modelling motion resistance, particularly in winter conditions.
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| 4. |
- Erdinc, Umur, 1992, et al.
(författare)
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Experimental Validation of Yaw Stability Control Strategies for Articulated Vehicle Combinations
- 2024
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Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. - 1931-0587 .- 2642-7214. ; , s. 1476-1483
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Konferensbidrag (refereegranskat)abstract
- Articulated Heavy Vehicles (AHVs) play a crucial role in today's transportation, offering significant commercial and environmental advantages. However, challenges like jackknifing and trailer swing in AHVs highlight the need for focused research. This paper introduces innovative yaw stability algorithms designed to tackle these concerns, employing advanced control allocation techniques, including distributed control allocation. A power loss minimization algorithm with four different methods to maintain yaw stability is tested with real test vehicles. In this framework, the algorithms ensure that control actions stay within predetermined safe limits, contributing significantly to the overall safety and efficiency of AHVs.
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| 5. |
- Erdinc, Umur, 1992, et al.
(författare)
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Modelling of Articulated Heavy Vehicles for Computation of Accurate Safe Operating Envelope for Yaw Stability
- 2023
-
Ingår i: Proceedings of the 17th International Symposium on Heavy Vehicle Transport & Technology (HVTT17).
-
Konferensbidrag (refereegranskat)abstract
- As articulated heavy vehicles switch to electric power, new ways of allocating wheel forces have emerged. To improve energy efficiency, it is increasingly common to use propulsion or regenerative braking on only one unit of the vehicle combination. This leads to yaw stability problems, mainly jackknifing if the towing unit has excessive wheel forces, or trailer swing if the trailing unit has excessive wheel forces. Hence, it becomes important to allocate the total force request into different units and actuators in a safe way. This paper formulates a nonlinear two-track model with a nonlinear tire model, combined slip, and roll degree of freedom. Thus, the presented model can accurately simulate brake-in-turn and propel-in-turn maneuvers at high lateral accelerations. And it can be used to study when the yaw instability occurs and understand if the maneuver is safe or not. One way to ensure safe control allocation is by implementing a safe operating envelope that restricts the allocation within predefined limits. This helps maintain control of the system and prevent any potential safety hazards. In this paper, a nonlinear two-track model is utilized to simulate a range of lateral accelerations and various combinations of braking forces between the tractor and semitrailer. Through this process, an envelope is obtained which is then compared to an envelope generated from a single-track model and validated against high-fidelity model-based envelopes. This rigorous process helps to ensure the accuracy and reliability of the two-track model.
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| 6. |
- Erdinc, Umur, 1992, et al.
(författare)
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Safe operating envelope based on a single-track model for yaw instability avoidance of articulated heavy vehicles
- 2024
-
Ingår i: Vehicle System Dynamics. - 1744-5159 .- 0042-3114. ; 62:8, s. 2138-2161
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Tidskriftsartikel (refereegranskat)abstract
- The electrification of commercial vehicles has led to new wheel torque allocation options for propulsion and braking of articulated heavy vehicles. Each unit or axle can be individually braked or propelled whilst the other units or axles are excluded from such action. This may achieve the best energy efficiency. However, this can also lead to potential yaw stability problems such as jackknifing and trailer swing, especially under bad loading and weather conditions. This paper describes the above instabilities and introduces a nonlinear single-track model to study the vehicle dynamics of the tractor-semitrailer combination. The effects of different vehicle and environment parameters are analysed with this vehicle model. A safe operating envelope for limiting the wheel forces is obtained using this vehicle model. Since the vehicle model introduced in this paper is computationally effective, it can be run online in real vehicles, with an instantaneous safe operating envelope obtained for the momentary conditions. Thus, yaw instabilities such as jackknifing and trailer swing may be avoided.
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| 7. |
- Erdinc, Umur, 1992, et al.
(författare)
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Validation of high-fidelity simulation-based safe operating envelopes for articulated heavy vehicles using real test data
- 2024
-
Ingår i: Vehicle System Dynamics. - 1744-5159 .- 0042-3114. ; In Press
-
Tidskriftsartikel (refereegranskat)abstract
- The electrification of towing and trailing units creates new torque allocation alternatives among different units of articulated heavy vehicles. To increase the power and energy efficiency, control algorithms can request propulsion or regenerative braking from a single unit while keeping the other units unbraked or unpropelled. However, this may lead to safety problems, such as jackknifing or trailer swing. This paper uses a high-fidelity simulation tool to formulate safe operating envelopes for a tractor and semitrailer combination for braking-in-turn cases. The effects of different vehicle and environment parameters on the safe operating envelope are studied. The safe operating envelope obtained is then validated using real vehicle tests and can be used with any control algorithm to avoid requesting unsafe unit force combinations.
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| 8. |
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| 9. |
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| 10. |
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| 11. |
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| 12. |
- Laine, Leo, 1972, et al.
(författare)
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Traction and braking of hybrid electric vehicles using control allocation
- 2008
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Ingår i: International Journal of Vehicle Design. - 0143-3369. ; 48:3/4, s. 271-298
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers how a reusable motion control system can be designed to handle Hybrid Electric Vehicle (HEV) systems. The design considers simultaneously energy management and vehicle stability control, by distributing the task among available actuators. The suggested controlsystem includes a control law for longitudinal, lateral, and yaw motion and a control distributor which distributes the desired control signals on the available actuators. The distribution among available actuators is designed by using constrained control allocation with mixed optimisation formulation, which gives a smooth blending among the available actuators. Simulations confirm that the proposed motion control system not only works as a traction, braking, and steering controller, it also works well as a vehicle stability controller.
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| 13. |
- Sadeghi Kati, Maliheh, 1979, et al.
(författare)
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A feedback-feed-forward steering control strategy for improving lateral dynamics stability of an A-double vehicle at high speeds
- 2022
-
Ingår i: Vehicle System Dynamics. - : Informa UK Limited. - 1744-5159 .- 0042-3114. ; 60:11, s. 3955 -3976
-
Tidskriftsartikel (refereegranskat)abstract
- A control strategy based on H∞-type static output feedback combined with dynamic feed-forward is proposed to improve the high-speed lateral performance of an A-double combination vehicle (tractor–semitrailer–dolly–semitrailer) using active steering of the front axle of the dolly. Both feedback and feed-forward syntheses are performed via Linear Matrix Inequality (LMI) optimisation. From a practical point of view, the proposed controller is simple and easy to implement, despite its theoretical complexity. In fact, the measurement of the driver steering angle and only one articulation angle are required for the feed-forward and the feedback controllers, respectively. The results are verified using a high-fidelity vehicle model and confirm a significant reduction in yaw rate and lateral acceleration rearward amplification and also high-speed transient off-tracking, and subsequently improving the lateral stability and performance of the A-double combination vehicle during sudden lane change manoeuvres.
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| 14. |
- Sadeghi Kati, Maliheh, 1979, et al.
(författare)
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Design of a Robust Load-dependent Steering Controller for Improved High Capacity Vehicle Safety
- 2021
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. ; 2021-September
-
Konferensbidrag (refereegranskat)abstract
- This paper proposes a robust load-dependent controller synthesis to improve the lateral stability and performance of an A-double vehicle (tractor-semitrailer-dolly-semitrailer) at high speeds and consequently road safety by active steering of the dolly unit. The mass of the semitrailers resides in an interval between empty and fully-loaded scenarios and can be measured online. The yaw moments of inertia of the semitrailers can significantly change depending on loading conditions. In order to design a gain-scheduled controller with the mass of the semitrailers as scheduling parameters and to guarantee the system performance against the yaw moment of inertia variations in the semitrailers, a linear matrix inequality (LMI)-based design framework has been utilized. In this formulation, a descriptor-form representation of the vehicle model is used in order to avoid dealing with rational parameter dependency. The controller synthesis is formulated as an H∞-type static output feedback (SOFB), which uses information from one articulation angle which is easily measurable in practice. The simulations results indicate significant improvements in the high-speed lateral performance of the A-double in various loading conditions by suppressing undesired oscillations in the yaw rate of the last semitrailer during sudden lane change manoeuvres.
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| 15. |
- Sadeghi Kati, Maliheh, 1979, et al.
(författare)
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Evaluation of Dynamical Behaviour of Long Heavy Vehicles Using Performance Based Characterstics
- 2014
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Ingår i: FISITA 2014 World Automotive Congress - Proceedings.
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Konferensbidrag (refereegranskat)abstract
- Long Heavy Vehicle Combinations (LHVCs) are an attractive alternative to Conventional Heavy Vehicle Combinations (CHVCs) in goods transportation because of reduction in fuel consumption, reduced costs and emissions. One major issue concerning LHVCs is their potential impacts on traffic safety that is the most controversial issue of LHVCs. Road safety performance of LHVCs depends on their technical features such as power train and braking systems capability, lateral dynamical stability, manoeuvrability and etc. By introducing LHVCs as a part of future transportation, there is a need to ensure that they are performing within specific boundary conditions. Defining proper technical characteristics, denoted as Performance Based Characteristics (PBCs) for LHVCs would assist to create operational requirements by which LHVCs will be allowed to operate in the road network with less negative road safety impacts. A comprehensive list of safety related PBCs is defined in (1). In this paper the test conditions and methods for each characteristic are specified and a set of heavy vehicle combinations (including European vehicle combinations, modular vehicle combinations and perspective modular vehicle combinations) are assessed and compared by using computer simulations. In addition, it is shown that by design parameter changes it is possible to improve the performance of a truck with double centre-axle trailers to perform almost similar as existing European conventional vehicle combinations like a truck and centre-axle trailer combination.
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| 16. |
- Sadeghi Kati, Maliheh, 1979, et al.
(författare)
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Gain-scheduled H Controller Synthesis for Actively-steered Longer and Heavier Commercial Vehicles
- 2020
-
Ingår i: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. - : SAGE Publications. - 2041-2991 .- 0954-4070. ; 234:7, s. 2045-2065
-
Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a gain-scheduled controller synthesis for improving the lateral performance and stability of articulated heavy vehicles by active steering of the selected towed vehicle units. The longitudinal velocity is on-line measurable, and it is thus treated as a scheduling parameter in the gain-scheduled controller synthesis. The lateral performance of four articulated heavy vehicles, including existing Nordic heavy vehicles and prospective longer articulated heavy vehicles, are investigated with and without active steering and compared with a commonly used conventional tractor–semitrailer. The control problem is formulated as an ℋ∞H∞ static output feedback, which uses only information from articulation angles between the steered vehicle unit and the vehicle unit in front of it. The solution of the problem is obtained within the linear matrix inequality framework, while guaranteeing ℋ∞H∞ performance objectives. Effectiveness of the designed controller is verified through numerical simulations performed on high-fidelity vehicle models. The results confirm a significant reduction in yaw rate rearward amplification, lateral acceleration rearward amplification, and high-speed transient off-tracking, thereby improving the lateral stability and performance of all studied heavy vehicles at high speeds.
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| 17. |
- Sadeghi Kati, Maliheh, 1979, et al.
(författare)
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LATERAL CONTROL OF AN A-DOUBLE COMBINATION VEHICLE CONSIDERING DIFFERENT MEASUREMENT SIGNALS AND DOLLY STEERING CONFIGURATIONS
- 2018
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Ingår i: International Symposium on Heavy Vehicle Transport Technology, HVTT15.
-
Konferensbidrag (refereegranskat)abstract
- The objective of this paper is to compare and study the performance of different steering configuration of an active dolly which is employed in an A-double combination vehicle (tractor-semitrailer-dolly-semitrailer) to enhance high speed stability and performance of the vehicle. Three dolly steering configurations are considered to be investigated; the front axle steering (FAS), rear axle steering (RAS) and double axle steering (DAS). A static output feedback control synthesis is used based on linear matrix inequality (LMI) and H1 control. The simulation results show significant effects of the active dolly steering on improving lateral stability and performance at high speeds. The effectiveness of approaches are demonstrated using a high-fidelity vehicle model. The simulation results indicate that the FAS and DAS configurations are preferable compared to the RAS configuration at high speeds.
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| 18. |
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| 19. |
- Uhlén, Karin, 1990, et al.
(författare)
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Coordination of Actuators for an A-double Heavy Vehicle Combination
- 2014
-
Ingår i: 17th International IEEE Conference on Intelligent Transportation Systems.. - 9781479960781
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Konferensbidrag (refereegranskat)abstract
- This paper shows how actuator coordination,based on control allocation, can be used in the motion control system for long articulated heavy vehicles. Usage of a control allocation structure is one way to handle an over-actuated system, which is a system where there are more motion actuators than controlled motions. The A-double combination is in focus for the control allocation design, which is based on vehicle modelling using the Lagrange formulation. The control structure is tested in a simulation environment and evaluated by two test scenarios. For the selected configuration with 31actuators, the control allocation method coordinates the desired motion for both large and small steer and articulation angles. The proposed control structure is shown to be convenient when the vehicle configuration, for example the number of actuators in the combination, is changed.
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| 20. |
- Akhmetov, Yerlan, et al.
(författare)
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Predictive Driver Interpreter by using Inverse Model for Heavy Vehicles
- 2010
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Ingår i: 13th International IEEE, Annual Conference on Intelligent Transportation Systems, Madeira Island, Portugal, September 19-22, 2010. ; , s. 174-179
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Konferensbidrag (refereegranskat)abstract
- This paper evaluates predictive control and necessary time horizon for heavy vehicle's active safety functionality by using an inverse model as predictor. The predictive driver interpreter provides the anticipating signals for limiting the forward velocity which can guarantee a manoeuvre's safe realization without loss of control. It has been integrated in a control allocation structure. The controller has been tested for an open-loop avoidance manoeuvre which is given by a sine with dwell steering input. Simulations showed for the studied manoeuvre and truck configuration that the passive vehicle is stable up to amplitude of 105 deg of steering wheel angle. When no predictive horizon was applied in the control allocation, the amplitude could be increased to 150 deg. When a predictive horizon of 1.5 s was used the amplitude could be doubled and still be stable.
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| 21. |
- Börve, Erik, 1998, et al.
(författare)
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Interaction-Aware Trajectory Prediction and Planning in Dense Highway Traffic using Distributed Model Predictive Control
- 2023
-
Ingår i: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. ; , s. 6124-6129
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Konferensbidrag (refereegranskat)abstract
- In this paper we treat optimal trajectory planning for an autonomous vehicle (AV) operating in dense traffic, where vehicles closely interact with each other. To tackle this problem, we present a novel framework that couples trajectory prediction and planning in multi-agent environments, using distributed model predictive control. A demonstration of our framework is presented in simulation, employing a trajectory planner using non-linear model predictive control. We analyze performance and convergence of our framework, subject to different prediction errors. The results indicate that the obtained locally optimal solutions are improved, compared with decoupled prediction and planning.
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| 22. |
- Duijkeren, Niels van, et al.
(författare)
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Real-Time NMPC for Semi-Automated Highway Driving of Long Heavy Vehicle Combinations
- 2015
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Ingår i: 5th IFAC Conference on Nonlinear Model Predictive Control, NMPC'15, Seville, September 17-21, 2015.
-
Konferensbidrag (refereegranskat)abstract
- This work presents a Nonlinear Model Predictive Control (NMPC) approach to realtime trajectory generation for highway driving with long truck combinations. In order to consider all relevant information for the road and the surrounding traffic, we formulate a finite-horizonoptimal control problem (OCP) that incorporates a prediction model in spatial coordinates for the vehicle and the surrounding traffic. This allows road properties (such as curvature) to appear as known variables in the prediction horizon. The objective function of the resultingconstrained nonlinear least-squares problem provides a trade-off between tracking performance, driver comfort, and keeping a comfortable distance from fellow road users. The OCP is solved with a direct multiple shooting solution method implemented in a real-time iteration schemeusing ACADO code generation and compared with a feedback scheme that solves the entire nonlinear program in each time step with the interior point solver IPOPT. To illustrate the efficacy and the real-time implementability of the methodology, simulation results are presentedfor a high way merging scenario of a long heavy vehicle combination.
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| 23. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Computationally Efficient Nonlinear One-and Two-Track Models for Multitrailer Road Vehicles
- 2020
-
Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8, s. 203854-203875
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents nonlinear mathematical models of one-and two-track multitrailer vehicles. We derive nonlinear equations of motion in the form of a system of implicit ordinary differential equations (ODEs) by using Lagrangian mechanics. The system of ODEs has the minimum number of states and equations that enables efficient computations yet maintains the most important nonlinear vehicle dynamic behavior and allows actuator coordination and energy consumption evaluation. As examples, we build different models of a 4-unit long combination vehicle, i.e., two-track 11-axle and single-track 6-axle nonlinear models as well as a linear single-track 6-axle model. We compare the performance of these models to experimental data of different driving maneuvers. The nonlinear single-track model demonstrates close dynamic behavior to the experiment, which makes it an efficient alternative to the two-track model. The vehicle equations can be generated automatically by using the code provided in this paper and subsequently used for conducting frequency analysis, evaluating energy consumption, deriving performance measures from simulations, and facilitating optimal control applications that involve combined steering, braking and propulsion control.
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| 24. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Impact of automated driving systems on road freight transport and electrified propulsion of heavy vehicles
- 2020
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 115
-
Tidskriftsartikel (refereegranskat)abstract
- The technological barriers to automated driving systems (ADS) are being quickly overcome to deploy on–road vehicles that do not require a human driver on–board. ADS have opened up possibilities to improve mobility, productivity, logistics planning, and energy consumption. However, further enhancements in productivity and energy consumption are required to reach CO2–reduction goals, owing to increased demands on transportation. In particular, in the freight sector, incorporation of automation with electrification can meet necessities of sustainable transport. However, the profitability of battery electric heavy vehicles (BEHVs) remains a concern. This study found that ADS led to profitability of BEHVs, which remained profitable for increased travel ranges by a factor of four compared to that of BEHVs driven by humans. Up to 20% reduction in the total cost of ownership of BEHVs equipped with ADS could be achieved by optimizing the electric propulsion system along with the infrastructure for a given transportation task. In that case, the optimized propulsion system might not be similar to that of a BEHV with a human driver. To obtain the results, the total cost of ownership was minimized numerically for 3072 different transportation scenarios that showed the effects of travel distance, road hilliness, average reference speed, and vehicle size on the incorporated electrification and automation, and compared to that of conventional combustion–powered heavy vehicles.
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| 25. |
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| 26. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Optimization Based Design of Heterogeneous Truck Fleet and Electric Propulsion
- 2016
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Ingår i: Proceedings, ITSC. IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), November 1-4, 2016, Rio de Janeiro, Brazil. - 9781509018895 ; , s. Art no 7795575, Pages 328-335
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Konferensbidrag (refereegranskat)abstract
- Many researches have been focused on vehicle routing problem during past decades where subject vehicles are previously fully designed and ready to start operation. Further, extensive studies have been done on powertrain design irrespective of the routes where the vehicle is going to be employed. In the present paper, we try to define a new branch of problems where the vehicle design, in particular its propulsion system and loading capacity, is treated simultaneously with the routing problem. The focus is on optimization based design of heterogeneous electric truck fleet to perform a prescribed task with a lowest cost on an available set of routes. The approach is illustrated in a simple case study problem. It is shown that long heavy combination vehicles are energy-efficient but not cost-optimal on short routes.
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| 27. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Optimization data on total cost of ownership for conventional and battery electric heavy vehicles driven by humans and by Automated Driving Systems
- 2020
-
Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409. ; 30
-
Tidskriftsartikel (refereegranskat)abstract
- In road freight transport, the emerging technologies such as automated driving systems improve the mobility, productivity and fuel efficiency. However, the improved efficiency is not enough to meet environmental goals due to growing demands of transportation. Combining automated driving systems and electrified propulsion can substantially improve the road freight transport efficiency. However, the high cost of the battery electric heavy vehicles is a barrier hindering their adoption by the transportation companies. Automated driving systems, requiring no human driver on–board, make the battery electric heavy vehicles competitive to their conventional counterparts in a wider range of transportation tasks and use cases compared to the vehicles with human drivers. The presented data identify transportation tasks where the battery electric heavy vehicles driven by humans or by automated driving systems have lower cost of ownership than their conventional counterparts. The data were produced by optimizing the vehicle propulsion system together with the loading/unloading schemes and charging powers, with the objective of minimizing the total cost of ownership on 3072 different transportation scenarios, according to research article “Impact of automated driving systems on road freight transport and electrified propulsion of heavy vehicles” (Ghandriz et al., 2020). The data help understanding the effects of traveled distance, road hilliness and vehicle size on the total cost of ownership of the vehicles with different propulsion and driving systems. Data also include sensitivity tests on the uncertain parameters.
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| 28. |
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| 29. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Real-time Predictive Energy Management of Hybrid Electric Heavy Vehicles by Sequential Programming
- 2021
-
Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 70:5, s. 4113-4128
-
Tidskriftsartikel (refereegranskat)abstract
- With the objective of reducing fuel consumption, this paper presents real-time predictive energy management of hybrid electric heavy vehicles. We propose an optimal control strategy that determines the power split between different vehicle power sources and brakes. Based on the model predictive control (MPC) and sequential programming, the optimal trajectories of the vehicle velocity and battery state of charge are found for upcoming horizons with a length of 5-20 km. Then, acceleration and brake pedal positions together with the battery usage are regulated to follow the requested speed and state of charge that is verified using a vehicle plant model. The main contribution of this paper is the development of a sequential linear program for predictive energy management that is faster and simpler than sequential quadratic programming in tested solvers and gives trajectories that are very close to the best trajectories found by nonlinear programming. The performance of the method is also compared to two different sequential quadratic programs.
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| 30. |
- Ghandriz, Toheed, 1982, et al.
(författare)
-
Sensitivity Analysis of Optimal Energy Management in Plug-in Hybrid Heavy Vehicles
- 2017
-
Ingår i: 2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE). - 9781509062737 ; , s. 320-327
-
Konferensbidrag (refereegranskat)abstract
- Optimal energy management strategies of hybrid vehicles are computationally expensive when considering the entire trip ahead rather than a short upcoming horizon. Considering the entire representative trip is already needed in concept design stages of the vehicle. In order to come up with an appropriate design while minimizing the total ownership cost the energy management strategies must already be used together with early concept evaluations. To investigate the possibility of replacing the optimal energy management with simpler approaches, here, the sensitivity of optimal solution to some of vehicle parameters and traffic flow is studied. It is seen that a simpler approach, i.e. an instantaneous optimization, can be used, in case of smooth traffic flow, since the gain of optimal strategy in reduction of operational cost is less than 4% for different vehicle hardware setup and for selected representative driving cycle. Dynamic programming is used as a solution method for finding the optimal strategy.
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| 31. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Trajectory-Following and Off-Tracking Minimization of Long Combination Vehicles: A Comparison Between Nonlinear and Linear Model Predictive Control
- 2024
-
Ingår i: Vehicle System Dynamics. - : Informa UK Limited. - 1744-5159 .- 0042-3114. ; 62:2, s. 277-310
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we compared the linear and nonlinear motion prediction models of a long combination vehicle (LCV). We designed a nonlinear model predictive control (NMPC) for trajectory-following and off-tracking minimisation of the LCV. The used prediction model allowed coupled longitudinal and lateral dynamics together with the possibility of a combined steering, propulsion and braking control of those vehicles in long prediction horizons and in all ranges of forward velocity. For LCVs where the vehicle model is highly nonlinear, we showed that the control actions calculated by a linear time-varying model predictive control (LTV-MPC) are relatively close to those obtained by the NMPC if the guess linearisation trajectory is sufficiently close to the nonlinear solution, in contrast to linearising for specific operating conditions that limit the generality of the designed function. We discussed how those guess trajectories can be obtained allowing off-line fixed time-varying model linearisation that is beneficial for real-time implementation of MPC in LCVs with long prediction horizons. The long prediction horizons are necessary for motion planning and trajectory-following of LCVs to maintain stability and tracking quality, e.g. by optimally reducing the speed prior to reaching a curve, and by generating control actions within the actuators limits.
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| 32. |
- Ghandriz, Toheed, 1982, et al.
(författare)
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Transportation-mission-based Optimization of Heterogeneous Heavy-vehicle Fleet Including Electrified Propulsion
- 2021
-
Ingår i: Energies. - : MDPI AG. - 1996-1073 .- 1996-1073. ; 14:11
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Tidskriftsartikel (refereegranskat)abstract
- Commercial-vehicle manufacturers design vehicles to operate over a wide range of transportation tasks and driving cycles. However, certain possibilities of reducing emissions, manufacturing and operational costs from end vehicles are neglected if the target range of transportation tasks is narrow and known in advance, especially in case of electrified propulsion. Apart from real-time energy optimization, vehicle hardware can be meticulously tailored to best fit a known transportation task. As proposed in this study, a heterogeneous fleet of heavy-vehicles can be designed in a more cost- and energy-efficient manner, if the coupling between vehicle hardware, transportation mission, and infrastructure is considered during initial conceptual-design stages. To this end, a rather large optimization problem was defined and solved to minimize the total cost of fleet ownership in an integrated manner for a real-world case study. In the said case-study, design variables of optimization problem included mission, recharging infrastructure, loading--unloading scheme, number of vehicles of each type, number of trips, vehicle-loading capacity, selection between conventional, fully electric, and hybrid powertrains, size of internal-combustion engines and electric motors, number of axles being powered, and type and size of battery packs. This study demonstrated that by means of integrated fleet customization, battery-electric heavy-vehicles could strongly compete against their conventional combustion-powered counterparts. Primary focus has been put on optimizing vehicle propulsion, transport mission, infrastructure and fleet size rather than routing.
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| 33. |
- Hansson, Axel, et al.
(författare)
-
Safe operating envelope for limiting actuation of electric trailer in tractor-semitrailer combination
- 2022
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. ; 2022-October, s. 3886-3893
-
Konferensbidrag (refereegranskat)abstract
- This paper shows how a safe operating envelope based on simulated data can be implemented in an allocation-type control system for a two-unit heavy vehicle. The vehicle in focus is a tractor semi-trailer combination for which firstly safe driving conditions are defined and then control laws and systems are designed with respect to set safe driving conditions. The proposed system is evaluated in a simulation environment and is verified to, during some typical use cases, avoid violating the definitions of safe driving while also minimizing energy losses with regard to some actuation prioritization laws. The system is constructed in a modular way which allows for changes in vehicle configurations and changes in specifications of installed actuators.
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| 34. |
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| 35. |
- Hoel, Carl-Johan, 1986, et al.
(författare)
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Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving
- 2020
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Ingår i: IEEE Transactions on Intelligent Vehicles. - 2379-8858. ; 5:2, s. 294-305
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Tidskriftsartikel (refereegranskat)abstract
- Tactical decision making for autonomous driving is challenging due to the diversity of environments, the uncertainty in the sensor information, and the complex interaction with other road users. This article introduces a general framework for tactical decision making, which combines the concepts of planning and learning, in the form of Monte Carlo tree search and deep reinforcement learning. The method is based on the AlphaGo Zero algorithm, which is extended to a domain with a continuous state space where self-play cannot be used. The framework is applied to two different highway driving cases in a simulated environment and it is shown to perform better than a commonly used baseline method. The strength of combining planning and learning is also illustrated by a comparison to using the Monte Carlo tree search or the neural network policy separately.
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| 36. |
- Hoel, Carl-Johan E, 1986, et al.
(författare)
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Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning
- 2018
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. ; 2018-November, s. 2148-2155
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a method, based on deep reinforcement learning, for automatically generating a general purpose decision making function. A Deep Q-Network agent was trained in a simulated environment to handle speed and lane change decisions for a truck-trailer combination. In a highway driving case, it is shown that the method produced an agent that matched or surpassed the performance of a commonly used reference model. To demonstrate the generality of the method, the exact same algorithm was also tested by training it for an overtaking case on a road with oncoming traffic. Furthermore, a novel way of applying a convolutional neural network to high level input that represents interchangeable objects is also introduced. https://arxiv.org/abs/1803.10056
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| 37. |
- Hoel, Carl-Johan E, 1986, et al.
(författare)
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Ensemble Quantile Networks: Uncertainty-Aware Reinforcement Learning With Applications in Autonomous Driving
- 2023
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:6, s. 6030-6041
-
Tidskriftsartikel (refereegranskat)abstract
- Reinforcement learning (RL) can be used to create a decision-making agent for autonomous driving. However, previous approaches provide black-box solutions, which do not offer information on how confident the agent is about its decisions. An estimate of both the aleatoric and epistemic uncertainty of the agent’s decisions is fundamental for real-world applications of autonomous driving. Therefore, this paper introduces the Ensemble Quantile Networks (EQN) method, which combines distributional RL with an ensemble approach, to obtain a complete uncertainty estimate. The distribution over returns is estimated by learning its quantile function implicitly, which gives the aleatoric uncertainty, whereas an ensemble of agents is trained on bootstrapped data to provide a Bayesian estimation of the epistemic uncertainty. A criterion for classifying which decisions that have an unacceptable uncertainty is also introduced. The results show that the EQN method can balance risk and time efficiency in different occluded intersection scenarios, by considering the estimated aleatoric uncertainty. Furthermore, it is shown that the trained agent can use the epistemic uncertainty information to identify situations that the agent has not been trained for and thereby avoid making unfounded, potentially dangerous, decisions outside of the training distribution.
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| 38. |
- Hoel, Carl-Johan E, 1986, et al.
(författare)
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Tactical Decision-Making in Autonomous Driving by Reinforcement Learning with Uncertainty Estimation
- 2020
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Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. ; , s. 1563-1569
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Konferensbidrag (refereegranskat)abstract
- Reinforcement learning (RL) can be used to create a tactical decision-making agent for autonomous driving. However, previous approaches only output decisions and do not provide information about the agent's confidence in the recommended actions. This paper investigates how a Bayesian RL technique, based on an ensemble of neural networks with additional randomized prior functions (RPF), can be used to estimate the uncertainty of decisions in autonomous driving. A method for classifying whether or not an action should be considered safe is also introduced. The performance of the ensemble RPF method is evaluated by training an agent on a highway driving scenario. It is shown that the trained agent can estimate the uncertainty of its decisions and indicate an unacceptable level when the agent faces a situation that is far from the training distribution. Furthermore, within the training distribution, the ensemble RPF agent outperforms a standard Deep Q-Network agent. In this study, the estimated uncertainty is used to choose safe actions in unknown situations. However, the uncertainty information could also be used to identify situations that should be added to the training process.
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| 39. |
- Hofmann, Michael, 1989, et al.
(författare)
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Development and Evaluation of an Experimental Platform for Steered Axles of Long Combination Vehicles
- 2016
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Ingår i: 14th International Symposium on Heavy Vehicle Transport Technology (HVTT14).
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Konferensbidrag (refereegranskat)abstract
- Long Combination Vehicles (LCVs) require different strategies in controlling lateral dynamics of the combinations to ensure optimal paths followed by the trailers. Steering more than one axle of the combination has been developed in previous works and now needs to be verified in real vehicle tests. This work thus developed an experimentation platform incorporating a rapid-prototyping system to provide the possibility of evaluating these algorithms on vehicle level. In this paper the solution is detailed as a Hardware-in-the- Loop (HiL)-platform linking a vehicle dynamics frame-work with two steered axles. In accordance with the automotive development process after the V-model, this allows to safely verify the functioning of both software and hardware before performing track-tests of the fully integrated system with all units of a LCV. This paper outlines the development and capabilities of the resulting experimental platform and gives a short example of its performance in a standard-maneuver, which is also used to proof the validity between simulation and HiL-environment enabling full system testing on vehicle level.
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| 40. |
- Islam, Manjurul, 1984, et al.
(författare)
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Improve Safety by Optimal Steering Control of a Converter Dolly using Particle Swarm Optimization for Low-Speed Maneuvers
- 2015
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Ingår i: 18th IEEE International Conference on Intelligent Transportation Systems,ITSC 2015, September 15-18, 2015. - 2153-0009. - 9781467365963 ; 2015-October, s. 2370-2377
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Konferensbidrag (refereegranskat)abstract
- This paper offers a solution to the problem of poor path-following performance of high capacity transport (HCT) vehicles, such as A-double combinations, causing safety issue for the vulnerable road users during low-speed turning maneuvers. An advanced control strategy is developed which only demands the axles of the converter dolly of such vehicle to be actively steerable so that existing tractor and semitrailers can be used without any further modification. The control strategy described in this paper allows the change of forward speed and even to stop the vehicle completely during the turning maneuver without any performance degradation. The controller utilizes the delays of tractor front axle steering angle and the articulation angles measured not in traditional time but in path-distance domain. The optimal controller is achieved using particle swarm optimization (PSO) technique. Finally the optimal vehicle performance is compared with a baseline non-steerable converter dolly case and also with a proportional control case. Significant improvement in path-following performance is observed.
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| 41. |
- Islam, Manjurul, 1984, et al.
(författare)
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Inverse Model Control Including Actuator Dynamics for Active Dolly Steering in High Capacity Transport Vehicle
- 2015
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Ingår i: Intelligent Vehicles Symposium (IV), 2015 IEEE. - 9781467372664 ; 2015-August, s. 1024 - 1031
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Konferensbidrag (refereegranskat)abstract
- This paper describes an advance controller designed using the nonlinear inversion technique of a Modelica based simulation tool, such as Dymola, for active dolly steering of a high capacity transport vehicle. Actuator dynamics is included in the inverse model controller. Therefore, it can automatically generate required steering angle request for the dolly axles of the vehicle combination. The resultant controller is transfered as a functional mock-up unit (FMU) to Simulink environment where the actual simulations are conducted. The controller is simulated against a high-fidelity vehicle model of an A-double combination from Virtual Truck Models (VTM) library -- developed by Volvo Group Trucks Technology. Effects of variations of the actual actuator dynamics, with respect to the modeled dynamics in the inverse model controller, on overall vehicle performance are investigated.
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| 42. |
- Janardhanan, Sachin, 1983, et al.
(författare)
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Concept design of electric cruise and startability axles for long haul heavy vehicles to maximise driving range
- 2021
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Ingår i: 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS.
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Konferensbidrag (refereegranskat)abstract
- Electrification of commercial heavy vehicles hasled to the offer of different electric drive-based powertrainarchitectures, most of them with the adaptation of the dieselengine based architecture. Due to the limited driving rangepossible, optimal configuration of the powertrain becomes avital task with the battery as the energy source, which alsotakes a significant portion of payload capacity. A modularand distributed powertrain architecture using separate cruiseand startability axles is introduced in this paper with theaim to maximise driving range. The concept is developed andevaluated using a joint hardware and control design frameworkfor a target vehicle combination of 36 tonnes over a typicalregional long haul drive cycle using simulations. Sensitivitystudy of gear ratios and motor sizes with vehicle targetrequirements is performed to identify the optimal configurationfor the powertrain concept. The simulation results show thatby configuring around50%of the total electric machine powerto the cruise axle and choosing a gear ratio between 12-13, therange capability is maximised, while satisfying startability andcruise mode operations.
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| 43. |
- Janardhanan, Sachin, 1983, et al.
(författare)
-
Introduction of Traffic Situation Management for a rigid truck, tests conducted on object avoidance by steering within ego lane
- 2015
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Ingår i: 2015 IEEE 18th International Conference on Intelligent Transportation Systems.
-
Konferensbidrag (refereegranskat)abstract
- Awareness in traffic situations and manoeuveringefficiently through complex scenarios is a critical task to be managed for active safety and autonomous vehicle applications. This task could be assigned as a separate functionality layer due to its complexity. A reference development framework for autonomous heavy vehicle applications called Traffic Situation Management functionality layer is presented in this study. Thefunctionality layer is then verified by developing a real time rear end collision avoidance function by steering. The motion of the truck is restricted within the existing lanes representing situations where there is a partial lateral interference by other vehicles, with safe distance to manoeuvre in the longitudinal and lateral directions. Lane markings are used as a reference to guide the vehicle within the ego lane during the avoidance manoeuvre. Based on the traffic scenario and ego vehicle states an escape path is generated. A simple feed-forward and PD based feedback controller is used to track the generatedpath. Physical tests are conducted on a 6X2 rigid heavy truck to verify the proposed function. Results indicate satisfactory performance of the avoidance function and safe margins during the test runs.
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| 44. |
- Janardhanan, Sachin, 1983, et al.
(författare)
-
Motion control and power coordination of electric propulsion and braking distributed on multiple axles on heavy vehicles
- 2022
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Ingår i: 2022 IEEE Vehicle Power and Propulsion Conference, VPPC 2022 - Proceedings.
-
Konferensbidrag (refereegranskat)abstract
- Instantaneous allocation of power in a distributed electric powertrain reduces losses by selective usage of actuators. Such an allocation also poses a challenge of coordinating power among actuators optimally. This study explores three different approaches of motion control and power coordination of electric machines and service brakes, using an instantaneous power allocation. These approaches based on control allocation framework, are further evaluated and compared for a given use case using simulations. The distinctive strength of the power loss minimisation approach, by using regressed data of power losses from electric machine models instantaneously, is highlighted. Additionally, it is also shown that the power loss minimisation approach resulted in the lowest energy loss in actuator power losses compared to the other approaches.
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| 45. |
- Janardhanan, Sachin, 1983, et al.
(författare)
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Reviewing control allocation using quadratic programming for motion control and power coordination of battery electric vehicles
- 2022
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Ingår i: 2022 IEEE Vehicle Power and Propulsion Conference, VPPC 2022 - Proceedings.
-
Konferensbidrag (refereegranskat)abstract
- This paper evaluates the performance of control allocation (CA) problem formulations for battery electric vehicles. optimisation-based CA formulations such as mixed optimisation, power loss minimisation and their various configurations are solved as a constrained quadratic programming (QP) problem. Metrics such as the numerical error of the solution, the condition number of the hessian matrix and energy efficiency associated with the solution obtained for the QP formulation are used to analyse the problem formulations with three decision variables. For the mixed optimisation formulation, these metrics aid in tuning the weighting term and actuator priority matrix parameters. The sensitivity of the solution due to the weighting term in the the mixed optimisation formulation is avoided by explicitly setting an equality constraint for the motion control. Additionally, implementing motion control requests as equality constraints, avoids the need of tuning the parameters and leads to the formulation as a pure power loss minimisation problem. Finally, it is also shown that the actuator coordination is not sensitive to the normalisation of the virtual control request and actuator capabilities.
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| 46. |
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| 47. |
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| 48. |
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| 49. |
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| 50. |
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