Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Distributed Road Grade Estimation for Heavy Duty Vehicles
An increasing need for goods and passenger transportation drives continued worldwide growth in traffic. As traffic increases environmental concerns, traffic safety, and cost efficiency become ever more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. Applications such as predictive cruise control, automated gearbox control, predictive front lighting control, and hybrid vehicle state-of-charge control decrease the energy consumption of vehicles and increase the safety. These control systems can benefit significantly from preview road grade information. This information is currently obtained using specialized survey vehicles, and is not widely available. This thesis proposes new methods to obtain road grade information using on-board sensors. The task of creating road grade maps is addressed by the proposal of a framework where vehicles using a road network collect the necessary data for estimating the road grade. The estimation can then be carried out locally in the vehicle, or in the presence of a communication link to the infrastructure, centrally. In either case the accuracy of the map increases over time, and costly road surveys can be avoided. This thesis presents a new distributed method for creating accurate road grade maps for vehicle control applications. Standard heavy duty vehicles in normal operation are used to collect measurements. Estimates from multiple passes along a road segment are merged to form a road grade map, which improves each time a vehicle retraces a route. The design and implementation of the road grade estimator are described, and the performance is experimentally evaluated using real vehicles. Three different grade estimation methods, based on different assumption on the road grade signal, are proposed and compared. They all use data from sensors that are standard equipment in heavy duty vehicles. Measurements of the vehicle speed and the engine torque are combined with observations of the road ...
Distributed Road Grade Estimation for Heavy Duty Vehicles
An increasing need for goods and passenger transportation drives continued worldwide growth in traffic. As traffic increases environmental concerns, traffic safety, and cost efficiency become ever more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. Applications such as predictive cruise control, automated gearbox control, predictive front lighting control, and hybrid vehicle state-of-charge control decrease the energy consumption of vehicles and increase the safety. These control systems can benefit significantly from preview road grade information. This information is currently obtained using specialized survey vehicles, and is not widely available. This thesis proposes new methods to obtain road grade information using on-board sensors. The task of creating road grade maps is addressed by the proposal of a framework where vehicles using a road network collect the necessary data for estimating the road grade. The estimation can then be carried out locally in the vehicle, or in the presence of a communication link to the infrastructure, centrally. In either case the accuracy of the map increases over time, and costly road surveys can be avoided. This thesis presents a new distributed method for creating accurate road grade maps for vehicle control applications. Standard heavy duty vehicles in normal operation are used to collect measurements. Estimates from multiple passes along a road segment are merged to form a road grade map, which improves each time a vehicle retraces a route. The design and implementation of the road grade estimator are described, and the performance is experimentally evaluated using real vehicles. Three different grade estimation methods, based on different assumption on the road grade signal, are proposed and compared. They all use data from sensors that are standard equipment in heavy duty vehicles. Measurements of the vehicle speed and the engine torque are combined with observations of the road ...
Distributed Road Grade Estimation for Heavy Duty Vehicles
Sahlholm, Per (Autor:in)
01.01.2011
2011:008
Hochschulschrift
Elektronische Ressource
Englisch
Road damage caused by heavy duty vehicles
| Tema Archiv | 1995
| Engineering Index Backfile | 1963