Predictive Truck Reduces Emissions

Many aspects influence the amount of CO₂ emitted by a truck during its journey from shipper to consignee. Factors include the truck type and its aerodynamic drag as well as the cargo’s weight and the tare weight. Then there are external factors that can change at any time, including traffic conditions or the weather. A change in the wind direction also alters the amount of CO₂ emitted on the various routes from start to destination.

In the EU project “optiTruck” (optimal fuel consumption with predictive powertrain control and calibration for intelligent trucks), a cloud solution should help to find the route with the lowest CO₂ emissions on the basis of all these various influencing factors. The main idea is as follows. Before starting the journey, the logistics dispatcher sends important key data to the data cloud such as starting point and destination, load and delivery deadline. The data cloud uses this information to calculate a choice of alternative routes with the lowest possible CO₂ emissions. Due consideration is also given to changing t raf f ic and weather conditions: the software on the cloud checks constantly whether the truck is still on the ideal route. If necessary, it sends the driver an update by mobile communication. The truck and cloud are therefore in constant contact.

But the road directly ahead of the truck also offers scope for optimization. For example, if the truck is approaching a longer downhill section, the actuation of accessory units such as the compressed air supply can be delayed because potential energy will then become available while driving downhill. A similar approach can be taken to reducing energy consumption in the exhaust gas aftertreatment system. Regeneration of the diesel particulate filter can be delayed just before reaching an uphill climb because the exhaust temperature will increase anyway during the ascent. Predictive management can also save energy in the cooling system by taking account of the operating points expected in each case. This depends on having precise and real-time knowledge of the route ahead and the traffic conditions.

In the OptiTruck project , IAV was responsible for the basic structure of the control unit software, a rapid prototyping unit and the soft ware development environment for the partners. The platform for overall system simulation and three other innovation elements were also part of IAV’s remit: the model-based coordinator for the exhaust gas aftertreatment system as well as predictive management for the cooling system and for the auxiliary units.

The aim of the optiTruck project was to reduce the fuel consumption of a 40 – ton truck by 20% while at the same time complying with the Euro VI emission limits. In July 2019, the big moment had finally arrived. Two trucks set off in Turkey to deliver their freight to Italy and then to return to Turkey. One truck was fitted with conventional technology and the other with the optiTruck innovations. After evaluating the trip of roughly 5,000 kilometers, it transpired that the opti Truck vehicle consumed up to 13% less diesel fuel on certain sections of the journey. “The 20% goal can only be achieved under ideal conditions with all individual measures interacting perfectly”, says Oliver Dingel, IAV Project Manager for optiTruck. “It was not possible to achieve more under the prevailing circumstances. The results were sure to have been better on another route.” What’s more, the technology has gone through further development since the project began in 2015. The comparison truck in 2019 already exhausted some of the optimization potential in 2019.

That is why the IAV experts are satisfied with the results. “We worked with different partners from across Europe to set up a complex system and get it to work”, says Dr. Dennis Jünemann, development engineer for performance engineering at IAV. “That on its own was already a great success”. Furthermore, solutions were found for major technical problems, such as transferring data from the cloud to the vehicle and on to the individual control units. The limited capacity of the truck’s data buses made it necessary to reduce the volume of data and to divide the data into packages. The project also saw the emergence of a simulation environment for developing new algorithms that could then be transferred to a vehicle control unit almost without adjustments.

“optiTruck was a great success. We learned a lot during the project, and it has provided a good basis for subsequent projects”, summarizes Dingel. “We have identified
which points can be tackled and where it is possible to tap into further potential”. The cloud data, for example, were not ideal: further reductions in a truck’s CO₂ emissions could be achieved with more accurate maps and better route planning algorithms. IAV will work with customers to develop the identified potential on the basis of experience gained in the project.

Other stakeholders in the EU project OptiTruck alongside IAV include the truck manufacturer Ford Otosan, ERTICO ITS Europe (coordinator), the universities of Aalborg, Leeds and Okan, the Hellenic Institute of Transport, the ICOOR and ISMB research institutes and the user companies Eliadis Transport and Codognotto Italia. optiTruck was funded from the EU research framework program “Horizon 2020”. It was launched in September 2016 and ran until August 2019. The EU contributed € 4.5 million to the total project costs of € 5.3 million.
www.optitruck.eu

The article was published in automotion 01/2020, the automotive engineering magazine of IAV. Here you can order the automotion free of charge.