Refueling and Battery Charging Driver Assistance System for Online Operation Optimization of Connected Vehicles

摘要

In recent years, all major commercial vehicle OEMs have introduced predictive functionalities based on an electronic horizon for their on-highway fleets. Many studies show that more hybrid and electric vehicle variants in the medium and heavy commercial vehicle segments are in the development pipeline. Telemetry, navigation and electronic horizon systems are the key elements for reducing fuel and electric energy consumption as well as pollutant emissions in real world driving conditions. In this paper, a novel driver assistance system will be introduced that advises the driver to select refueling and battery charging stations as well as the quantities to be refueled or recharged. In this way the travel costs for a preselected route can economically be minimized, while still being compliant with an arrival time criteria. When selecting the stations, the most cost-effective recharging tariffs are considered. The presented algorithm calculates the global optimal solution with discrete dynamic programming. The novel modular approach is able to interact with existing powertrain optimization systems. The approach is applied to study the German highway Aachen-Munich-Aachen route. With the novel method, a reduction of more than 14.3 % of costs and 13.7 % of fuel consumption can be achieved. Further constraints allow to combine charging durations with legally required driver breaks.