Optimal Design of Future Hybrid Trucks

by Emilia Silvas

In an emerging society, where both the amount of people and cars are seriously  increasing,  concerns are raised on how can we improve the quality of life.  And we, as a society, want to achieve this while leaving an insignificant foot-print  on the environment that surrounds us.  We want to be smart. To develop our urban areas into smart cities we need to integrate smart mobility, with smart economies, smart environments, smart people, smart governance and smart living.

What is mobility and how can we make it smart? Mobility refers to the ability to move or to be moved freely and easily. This involves not only passenger cars but also trucks, vans, busses, trains, boats and so forth. If we look back, a car in the 1970s produced as many pollutant emissions as 100 cars today. Solely in the Netherlands the average CO2 emissions of new bought cars has decreased with 25% in the last 5 years. The noise has been largely reduced, both for passenger cars,  by 90% since 1970, as-well as trucks or busses. 25 of today’s trucks and buses are quieter than one built in 1980. And then today,  Europe’s cars, vans, trucks and buses are the cleanest, safest and quietest in the world. This has been achieved by cleaner production, decreased quantities of water and energy used to manufacture a vehicle and much less waste and CO2  produced in the process.

A significant step in this evolutionary process is the entry of hybrid and electrical vehicles; new innovative technologies that can implement fuel-efficient measures and advanced technologies. In Eindhoven one such project is the Hybrid Innovation for Trucks, an interdependent automotive ecosystem headed by DAF, SKF, DTI, Heliox and TU/e as knowledge institute. Within this project a multi-disciplinary approach and a fundamental/strategic technological research are performed for developing a hybrid truck.  By using new technologies and a newly developed energy management system that intelligently combines data on speed, load weight, incline, and curve radius,  this truck should prove fuel savings between 7% and 16% . Trucks represent a link between producers and consumers, travelling  a tremendous amount of kilometres each year and  transporting 76.4% of goods  around Europe. Therefore, by reducing with only few percentages the fuel consumption the levels of emitted CO2 and driver’s costs can be significantly  decreased.

The hybridization or electrification of vehicles brings an increase in the design complexity of the powertrain. As one of the 4 PhD students involved in this project, I am working on the integrated optimal design of the vehicle. Such multi-disciplinary dynamical systems present unique challenges to researchers and their design is becoming an increasingly important technical issue as the number and complexity of smart and autonomous systems rises, and as their role in society becomes more crucial (e.g., energy and transportation systems).  

Developing  these new concepts translates in solving a complex optimization problem, where trade-offs between performance, costs, fuel consumption and computation time exist and these will strongly depend on the vehicle’s application (e.g. long-haul trucks, garbage trucks). Prior to the choice of a suitable optimization algorithm for solving this design problem, there is a need of developed and in-depth understanding of powertrain models and possible topologies (series, parallel, series-parallel). Beside the main components of the vehicle, as engine, electric machine and battery, we are also researching the best design for auxiliary units (power steering pump, air compressor and so on). Moreover,  the optimal choice of component sizes, technology and topology, should be done in an integrated way with the energy management of the vehicle. The later ensures  the optimum power requirement and distribution between the diesel engine and the electric powertrain, as well as the optimum vehicle speed and transmission ratio of the power train. Such a design tool should prove to be beneficial on a long term for OEMs as DAF, where given small changes in the vehicle’s usage conditions or components characteristics, an automatic analysis can be done to show a new optimal design.

This project represents both a collaboration between companies and the university in the Brainport Area,  and a collaboration between three departments of  TU/e., namely the Mechanical Engineering, Electrical Engineering and Mathematics and Computer Science. It is financially supported by the Dutch automotive innovative programme HTAS (High-Tech Automotive Systems) of the Ministry of Economic Affairs, Agriculture and Innovation, the Netherlands.