This networked vehicle will improve efficiency, increase cruising range, and contribute to the overall driving enjoyment of an EV or plug-in hybrid-electric vehicle (PHEV). Through tailored applications created by content and service providers, the driver will identify the most efficient travel routes, learn efficient driving behaviors, avoid energy-wasting situations, locate charging stations, and have confidence in reaching a destination and returning home. Using map-based predictive technology, vehicle power controls will become more efficient through knowledge of road terrain, traffic controls, and regeneration opportunities.

Research demonstrates that connected hybrid-electric vehicles (HEVs) using digital map information can demonstrate energy savings of about 25%, according to Navteq researchers who presented a paper on this topic at the SAE Convergence 2010 conference in Detroit Oct. 19-20.

A connected EV/PHEV will operate in an “ecosystem” of intelligent applications that enable evolving EV support functions. This connected EV will combine embedded road knowledge used by the driver and vehicle systems with off-board dynamic information regarding the current or anticipated driving environment. Five significant domains—predictive road intelligence from digital maps, awareness of current and future traffic conditions, mobile data communications, advanced driver assistance systems (ADAS), and smart applications—will join the driver, vehicle, and world together seamlessly.

Connected services are a key enabler for enhancement of EV/ PHEV efficiency and the ownership experience. Whether incrementally updating an onboard map wirelessly to ensure the latest changes to the road network are represented, or delivering traffic-enabled routes to the nearest available charging station, a variety of innovative services are made possible by the combination of wireless connectivity, map data for ADAS, and back-end services and delivery capabilities. As these capabilities converge, and “cloud computing” services mature, the EV driver interface, mobile handset, and home computer all become relevant to this enhanced ownership experience.

There are five distinct ways that digital map data and wireless connectivity enhance EV/PHEV and driver efficiency: everyday navigation, eco-routing, eco-driving, predictive cruise control, and predictive powertrain control. These applications all demonstrate some kind of efficiency gain. The digital map can also identify EV/PHEV charging station locations and regenerative charging opportunities along a route.

For example, eco-routes are those that minimize vehicle energy consumption due to excessive stop-and-go driving and topographic challenges. Eco-routing applications are planned for current production vehicles with conventional powertrains and hybrids.

Eco-routing is undergoing an evolution where advanced map content is being identified and integrated into these applications to optimize route calculation. The applications will need to go through a similar evolution as they are optimized for EV/PHEVs. For example, physical map attributes (such as ADAS height and ADAS curvature), legal attributes (such as traffic signals, stop signs, and speed limits), and real-time traffic information using a connected data support system have been identified to be of value in calculating the most energy-efficient route and are being implemented in conventional vehicles today. These same attributes will also be of value for eco-routing applications for EV/PHEVs, but there may be differences in the algorithms that calculate the eco-route and the relative weighting of the individual attributes used in these algorithms.

For example, both conventional and EV/PHEVs will maximize trip efficiency by taking routes that strike the proper balance between minimizing stops caused by traffic controls and traffic conditions while not significantly extending the total distance traveled as a result. However, EV/PHEVs place a greater importance on smoother braking to maximize regenerative effects, and so routes may be calculated to emphasize avoidance of specific situations that cause frequent quick or hard braking behavior—for example severe road declines and traffic signals.

Until EV charging stations are as commonplace as conventional fueling stations, routes for EVs that accommodate the need for vehicle recharging will be of immense value. One can imagine the additional peace of mind this information will provide to EV owners when planning long drives. Pertinent information regarding charging stations—such as the vehicle connector types supported and electrical ratings, along with dynamic information accessible to a connected EV, including electricity prices and current availability of charging bays—also will be valuable.

One of the other applications, predictive powertrain control, involves the use of digital map data, especially height, slope, and curvature, to add predictive intelligence to automatic transmission shift timing and predictive power mode apportionment for HEVs. For transmissions, knowledge of road slope and curvature can help engineers optimize gear selection algorithms and avoid poorly timed gear shifts due to terrain-induced torque demands. For HEVs, anticipation of impending road slope changes will allow more sophisticated gasoline/electric mode control algorithms.

Slope data can also be used to identify future regeneration opportunities and safely allow extended depletion of the battery, thereby extending cruising range.

Key success factors for the migration to EVs/PHEVs will be consumer acceptance of and even excitement over these new propulsion technologies. Connectivity in many forms, including home Internet, vehicle-to-vehicle, and vehicle-to-infrastructure, will foster an ecosystem where these unique vehicles will be supported by an equally compelling suite of services that enhance the ownership experience.