Battery electric vehicle (BEV) are a clear alternative to conventional vehicles that rely solely on a combustion engine to propel them. This technology among other advantages allows to reduce fuel consumption and green house emissions. However, their higher cost and reduced range (especially in the case of plug-in and full electric vehicles) are two major drawbacks that are yet to be overcomed.

Now that the technology has proven to be feasible and almost every automaker has a hybrid or full electric solution in its portfolio, the next logical step is to try to solve or at least reduce the drawback mentioned before.

In this context, efforts have been place on fighting against range anxiety through fast and/or dynamic charging, increased in the size of the energy storage on board the vehicle and adding range extenders to the powertrain.

However, the work made on cost optimization of the electric powertrain has been characterize for the use of inexact cost models that might yield to misleading results. For this reason, this work focuses on  identifying and understanding the factors that drive the cost of the different components in the electric powertrain. This understanding is then used to develop models that describe the cost of these components based on a reduced number of parameters. A powertrain optimization is then to be performed taking advantages of the developed models. 

Additionally, the cost effectiveness of integrating charging and auxiliary components into the powertrain is to be studied and possibilities  for cost reductions at a system level are to be identified.

The main outcome of this project is to reduce the system cost of electric and electrified vehicles, making this technology more appealing to potential customers. This in return, will benefit society by reducing the pollution generated by road transport and the dependency on fossil fuels.

Main supervisor: Mats Alaküla

Co-supervisor: Avo Reinap

Mats Alaküla