Discussion of study boundaries and extension opportunities

This section explores areas for building on this work and highlights areas where care must be taken in interpreting results. First and foremost among them is the method used to evaluate the lifecycle impacts of the various alternatives. Due to the lack of a single comprehensive, consistent database for all environmental indicators, an attempt was made to combine the US-centric GREET database with the European ecoinvent database. While sufficient for an initial study, this approach is

sub-172 optimal. Significant developments in lifecycle inventories for advanced mobility in the European context have been made in the context of the THELMA (TecHnology-centered Electric Mobility Assessment) project which can and should be used to update the models input assumptions.

The dominance of biofuels is only valid if broader social issues such as land use change and food price increases are ignored. As such, these vehicle designs may present an effective mid-term mitigation option until land use constraints are reached. In any case, a more detailed analysis is warranted to examine this conclusion.

The broad stakeholder robustness analysis methodology does not provide results which can be used to examine market acceptance. It is only useful for evaluating which performance levels must be achieved for different technology options to be equally attractive to a broad range of rational stakeholders. To examine minimum performance levels for advanced technology in a way that is more directly transferable to policy recommendation, it is necessary to expand these methods to provide a more thorough representation of societal stakeholders. For an analysis of the dynamics of consumer behaviour concerning alternative powertrain technologies, please refer to (Alexander Wokaun & Erik Wilhelm 2011). Also, the survey methods employed in this thesis are not suitable for inferences about broader populations due to the limited demographic of the respondants.

One stakeholder criteria which was modeled, but not discussed in this thesis is fuelling time.

Conventional vehicles using liquid fuels „charge‟ at a rate of roughly 10MW over 3 minutes, which translates to a drivable distance of 200 km/filling minute. Electric vehicles, on the other hand, are currently limited to a maximum of roughly 60 kW, which translates to a drivable distance of about 5 km/filling minute. Neglecting the quantity of batteries which would need to be carried on-board and only considering charging time, to transfer enough energy into an average electric vehicle to travel 625 km (standard for most liquid fuel vehicles) in 10 minutes, one would have to charge at a rate of over 700 kW. Assuming a battery voltage of 500V, this means that the required current would be over 1500A, and likely to be possible only with very complicated high power bus technology or by performing battery swapping. For the charging time criterion, vehicles with gaseous fuels are slightly disadvantaged relative to liquid fuel vehicles. The difference may be approximately a doubling of charging time, but certainly not 40 times slower, as is the case for

all-173 electric vehicles. These are initial thoughts that can be incorporated into future investigations of this technology.

The analysis of plug-in series hybrids should be extended to include charge-depleting modes in order to understand how driver behaviour influences the performance of these vehicles. The assumption that plug-in hybrids would be operated in a charge-neutral way simplified the analysis of these vehicles by removing the need to assume usage profiles, but missed characterizing series hybrids as truly „plug-in‟ vehicles. As well, the lower part-load losses for diesel vehicles due to the lack of manifold throttling should be more explicitly modelled.

There are several interesting questions with regards to the trade-off between battery life and fuel consumption which are of concern to both industry and consumer stakeholders that could be answered with the dynamic programming approach developed in this thesis, but for which there unfortunately was not time. Considering the battery „state-of-health‟ as an additional state variable would add depth to the simulation methodology and bring the heuristic design set closer to how real vehicle designs are evaluated.

The influence of driving cycle on the results generated in this thesis was discussed very briefly at the end of Chapter 3, and this aspect of the work certainly deserves more attention. Although it is only possible to compare technologies on a fair basis if one cycle is used consistently throughout the analysis, it may be that the NEDC favours some designs over others, and that there is a better cycle which could be selected.

Vehicle safety was treated in a very cursory way in this thesis, and deserves much more discussion due to its importance to stakeholders. The perceived safety of advanced powertrains using gaseous fuels could be compared with actual safety performance to compose safety indicators. The effect of increased powertrain weight due to hybridization on safety may also result in interesting research questions.

The THELMA project which builds on the structures developed in this thesis should address these points to provide an un-biased and comprehensive analysis of the potential of various advanced transportation technologies. The project‟s web space can be found at http://thelma-emobility.net

174 and Work Package 2: Vehicle Simulation and Powertrain Assessment will continue expanding the results of this thesis. The interface with the Work Package 1, which deals with comprehensive lifecycle assessment of advanced vehicles, is particularly promising for further developing the models presented in this thesis.