Dynamic Cruising Range Prediction for Electric Vehicles

Abstract

Battery electric vehicles (BEVs) require new driver information systems. We anticipate a new integrated and networked information system class, combining data input from central car systems, drivers’ behaviour and environmental parameters. By introducing the system mapZero we propose an OEM-independent cruising range prediction system, which combines measurement and GIS-system based calculations on the ride (see Fig. 1). For the first time, we can consider range-affecting variables like outside temperatures, driving style preferences, charge metering, navigation, consumption planning, and route distance prediction to manage the immanent range restrictions.

The car side system consists of an optional on-board unit with metering and communication properties, and a mobile unit, preferably a smartphone (e.g., iOS, Android), offering navigation, power management, information and convenience features. System core is a self-learning algorithm as aggregation feature inside of a collaborating community, the car’s actual performance behaviour and the users preferred destinations and driving styles. It will propose charging or battery swapping stations on the planned route, which will then be passed on to a reservation management system, making sure the driver can enjoy a maximum of comfort and peace-of-mind on his or her journey.