| 1. |
- Jones, Stephen, et al.
(författare)
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Energy-efficient cooperative adaptive cruise control strategy using V2I
- 2019
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Ingår i: 2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019. ; , s. 1420-1425
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Konferensbidrag (refereegranskat)abstract
- In an increasingly connected world, this paper presents an advanced and cooperative semi-autonomous driving system which targets not only convenient and safe mobility, but also achieves noticeably enhanced energy efficiency. By utilizing V2V and V2I communication, a vehicle's energy consumption can be significantly reduced, while maintaining safety and driving comfort. A holistic control strategy is considered, which integrates features from earlier Cooperative Adaptive Cruise Control (CACC) and Traffic Light Assistant (TLA) research. This strategy incorporate s traffic light signal phase timing (SPAT), speed limits, road gradients and curves, surrounding traffic and detailed powertrain characteristics of the ego vehicle into a single Model Predictive Controller (MPC) formulation. The system's performance was evaluated using a realistic cosimulation toolchain and tested on a real conventional vehicle on a powertrain testbed with real V2I hardware. Results for a D-class diesel passenger car driven over an urban route, show energy savings up to 25%, with an unchanged journey time compared to a typical human driver. The approach is valid for both urban cities driving and highways, whilst being adaptable to commercial vehicles and other powertrains (hybrid, fully electric).
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| 2. |
- Kural, Emre, et al.
(författare)
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Traffic light assistant system for optimized energy consumption in an electric vehicle
- 2014
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Ingår i: 2014 International Conference on Connected Vehicles and Expo (ICCVE). - 9781479967292 ; , s. 604-611
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Konferensbidrag (refereegranskat)abstract
- Increasingly intelligent vehicle driving systems are rapidly being developed, and will in the future become a necessity for sustainable, convenient and safe mobility in our ever more urbanized world. This paper presents an innovative approach for the control of a fully electric vehicle approaching a road segment with Multiple Traffic Lights (TL). By utilizing Vehicle to Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, the energy consumption for the maneuver completion can be reduced. The problem is approached from a Model Predictive Control (MPC) framework. The performance of the system is evaluated using a complex simulation toolchain representing the vehicle, powertrain, driver, and road including the traffic conditions. The results have shown an overall energy consumption reduction of 29 % for an idealized case and 17 % for a real road simulated scenario as compared to ‘normal’ human driver behavior.
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