The European Union (EU) has set the goal to have a carbon-neutral economy by 2050. To achieve this, a key sector to focus on is the transportation sector. It will be especially challenging though to decarbonise the larger vehicles from the transportation sector, the trucks, ships and airplanes.

The typical way to respond to this or any other design challenge is by making use of the top-down/sequential design process, where first the larger parts of the design are established, and later the finer details are developed. However such an approach cannot guarantee that the design at the end is optimal or anywhere close to it. This makes the sequential design approach ill-suited to tackle the challenge of decarbonising the EU transportation sector. Co-Design on the other hand, a simultaneous design approach, can guarantee optimality, and would be a much more appropriate approach if it wasn’t for it being limited to only consider around 10-20 components.

The work in this report first investigated where this limitation of 10-20 components comes from. It is described how the source of the problem does not originate from topology optimisation, where most research has gone into, but rather it originates from the vast number of isomorphic topologies that are created during the topology generation process. Adding more data to describe the components only increases the number of isomorphic topologies even further. Since the results of the topology generation process are fed to the topology optimisation process, the entire Co-Design process is impacted by these isomorphic topologies.

The work that follows therefore focused on topology generation for Co-Design by testing a candidate method that allows topologies to be generated without any of the isomorphic topologies while describing components in more detail than what has been done in literature. The approach taken here relied, unlike what has been done so far, on the use of adjacency matrices and the interconnected system model. With this, new insight into topology generation for Co-Design was developed. The use of adjacency matrices were also key to automate the formation of constraints, which allowed to generate topologies for any set of components, also a first in the literature. The program TopoGen was developed to make this possible. The results that were obtained showed how using requirement chains and ordering instances, at least in simple cases, the 10-20 components limitation is fully overcome. This confirmed that the presence of isomorphic topologies the cause was for 10-20 components limitation in Co-Design. Still, for more complex cases, mistakes were present. However it was also shown how these too may be prevented in the future. This means that with further research and development, the candidate method presented here can be adjusted so that Co-Design can be applied even to complex cases, and therefore be used to develop solutions needed to decarbonise the EU transportation sector.

Fuel consumption reduction in Hybrid Electric Vehicles (HEV) powertrains has been an important area of research over the past few decades. HEV powertrains have two energy sources : fuel and battery. The important task of splitting the energy/power demand between both these sources is performed by the Energy Management Systems (EMS). There are many EMS methods and the focus of
this thesis is on a method called Modular ECMS (MEMS) implemented by TNO. MEMS finds the optimal power split among the subsystems by minimizing the energy loss in each subsystem. This strategy assumes that the operating speed of the subsystems of the powertrains is known and uses this knowledge to find the optimal power split and torque among these subsystems. The objective of this thesis is to find the optimal operating speed of the subsystems as well. This is done by a least squares fitting of the objective function and constraints as functions of subsystems speed and torque. A revised Optimal Control Problem (OCP) is formulated as a quadratic programming problem of speed and torque and is termed as Speed-Torque Coupled MEMS (ST-MEMS). The ST-MEMS algorithm is tested on a series-hybrid wheel loader powertrain model and its performance is compared to MEMS, with the model and data provided by TNO. It is concluded that the ST-MEMS, while adding the speed and torque bounds as degrees of freedom, does not achieve a good distribution of power between the 2 sources. The reason for this behaviour is analyzed and an alternate approachis suggested for future work.