The software package “upgrade-E” enables the predictive calculation of the expected speed, elevation and tractive power requirements of an “unknown” driving route. The development platform exclusively accesses freely available data formats such as Open Street Map (OSM) and SRTM altitude profiles in order to be independent of a supplier.
The predicted driving route provides a plethora of optimization possibilities for classical vehicle and powertrain functions. The prototype software is implemented on a conventional 7-inch Tablet PC with data-gateway to the main powertrain controller which is integrated in the AVL electric vehicle “Coup-e 800”.
A rapid prototyping platform for connected powertrain functions and services
Buzzwords like “Vehicle-to-x” and “connected powertrain services” are currently on the mind of most decision takers in automotive as well as in heavy duty industry. The basic question, how navigation data, internet- and infrastructure-information can be utilized in order to optimize fuel efficiency, electric driving range etc. and how these information can be bundled to provide additional services to the customer / driver are keeping the strategic departments of the OEMs busy.
The biggest issue of all “connectivity topics” however consists in its interdisciplinary multi-domain nature (navigation, internet, powertrain development). Due to the involvement of trans-sectoral departments and suppliers it is quite difficult and cost-intensive to test and evaluate new “connected-functionalities” in the area of powertrain development. For this reason AVL has developed the rapid prototyping platform upgrade-E for “connectivity functions and services”.
Basic idea of upgrade-E
The idea of using driving route prediction in order to optimize fuel consumption by adjusting the calibration of a powertrain and designing new predictive-functions is well known. Especially for electrified powertrains with more than one traction source those predictive approaches appear quite attractive as they offer a substantial increase in fuel efficiency by adjusting the operating strategy of the combustion engine and the E-Motor to the respective driving task.
But also conventional powertrain concepts (petrol / diesel) can be improved. Using predictive information for controlling the emission aftertreatment systems of a conventional truck, especially the Diesel Particulate Filter (DPF) for example offers a significant potential in fuel economy reduction. From time to time the DPF requires an active regeneration, which removes the particulates from the filter, at the cost of fuel. By telling the DPF-function at which point of time a full-load situation is most likely to occur within the next 100 km the system performance can be optimized over the expected duty cycles.
Finally the calculation of the traction power over the expected driving profile can be utilized for spanning the electric range display of an electric vehicle / plug-in electric vehicle. All surveys concerning electro mobility show that an inadequate range is given as the biggest disadvantage of electric vehicles. Apart from an increase in range, the precise representation of the remaining range is one of the possibilities to reduce range-anxiety and hence increase acceptance by the customer.
The resulting velocity profile needs to be modified and enhanced with up-to-date information concerning the traffic situation and traffic flow. Commercial traffic situation service providers evaluate the GPS signals of active navigation devices and use the data to determine the speed of traffic flow on the roads. Since the initial speed profile was generated via distance, the VPG can include the additional information from the traffic flow service, which is available as v(s), into the speed profile.
For calculating the elevation profile freely available data from the „Shuttle Radar Topography Mission“(SRTM altitude information) are processed into an altitude over distance characteristic.
Finally the power requirements of auxiliary components have to be considered. The predictive energy management system predicts the power requirements of the auxiliary components over time by using current data – read via CAN – concerning the auxiliary components (windscreen wipers, lights, aircon compressor, etc.), the external temperature and the desired internal temperature.
For calculating the tractive power requirements for the calculated profiles (velocity over time / altitude over distance / electric power over time), the powertrain and on-board electrical system architecture of the respective vehicle is modeled in the 1d simulation tool “Cruise” which is compiled for the tablet PC’s ARM processor (Snapdragon).
The powertrain simulation tool “Cruise” contains calculation components for the main road load components, the on-board load, all inertias and loss mechanisms (friction, component losses, warm-up behavior, etc.). Simultaneously, Cruise permits a comfortable and modular adaptation of any arbitrary powertrain architecture and possible component variants.
In form of ADASIS V2 protocol the calculated driving profiles are send to the data-gateway respectively to the powertrain controller unit. On the basis of these profiles the powertrain controller optimizes the existing functions (e.g. operating strategy, diagnosis, electric horizont, etc.)
Summary / Outlook
Within the scope of currently intensive but unstructured discussions surrounding the Vehicle-to-X / Connected Powertrain topic, the precise prediction of elevation, speed and tractive power requirements provide an interesting possibility to implement potential energy savings in electrified powertrain concepts. The rapid prototyping platform “upgrade-E” enables the comfortable development of “connectivity functions” which allow the optimization of conventional as well as future innovative powertrain functions for both passenger cars and commercial vehicles. Due to the significantly increased customer benefit, the described methods will leverage the acceptance of electrified vehicle concepts in the market.
Software concept of upgrade-E
The Calculation principals for tractive power are clearly defined by physics. The energy consumption of (electrified) vehicles is mainly affected by the vehicle speed profile (calculation of the main road load factors) and the elevation profile (calculation of the road gradient effect on road load). How can these two profiles now be acquired by navigation data?
The map data in navigation systems is stored in the form of nodes and ways. Nodes are defined by latitude and longitude and represent route points where a change of direction occurs or could occur. The nodes themselves are connected by ways that contain information pertaining to the distance between the nodes and the road class (country road, highway, etc.). In order to be able to derive the most realistic speed profile possible from the map data, the available average speed data for each way is connected in a speed-distance diagram. Taking driver characteristics such as sporty, comfortable etc. into account, the acceleration and stationary times can subsequently be considered and the speed-over-distance profile can be transferred to a speed-over-time profile.
Dr.-Ing. Armin Engstle
Department Manager Vehicle Controls
AVL Software and Functions