Since 2012, trucks equipped with the static eHorizon technology from Continental have saved more than one billion litres of diesel. The figure equals three million tons of CO2. The investment in the technology has helped truck manufacturers and the environment and is proof that the right product conserves resources in a cost-driven transport industry.
Roughly 4.1 lakh commercial vehicles that have been equipped with the static eHorizon as of today. Continental is working with ten truck OEMs in Europe, Asia and USA on this technology. The company expects further growth for this in the near future with growth in the US market picking up strongly.
The eHorizon technology offers information about the condition of the route ahead to the ECU in the trucks. This is based on highly accurate topographical route data from location cloud developer HERE Technologies and GPS signal information. The ECU then automatically adapts the driving style and speed.
Adaptive cruise control or predictive transmission control that avoids unnecessary gear changes are not just applications which CV makers can use with sensor systems. The customer uses this information from eHorizon to optimise other system functions like exhaust gas aftertreatment and increase the potential savings further. The list of possibilities also includes optimisation of heat recovery and exhaust gas aftertreatment, since the ideal time for particle filter regeneration can be calculated on data derived from eHorizon, energy-intensive process are prevented from being interrupted and repeated.
The next generation of electronic horizon, or dynamic eHorizon will offer additional savings of upto two percent in contrast with the earlier product. In the expansion stage, the digital map material is updated in close to real time through networking with the cloud, providing accurate and fresh data on the current traffic situation. The driving behaviour can be adapted to the current traffic situation at an early stage. This increases safety, but eHorizon also becomes an important bases for automated driving.