Energy Consumption Analysis of Different Bev Powertrain Topologies by Design Optimization

Flexible layout of electric motors in battery electric vehicles (BEVs) has enabled different powertrain topologies to be used. However, these different powertrain topologies also affect the overall efficiency of energy conversion from the electrochemical form stored in the battery to the mechanical form on the driving wheels for vehicle propulsion. In this study, a methodology combining an energy-based BEV simulation model with the genetic algorithm optimization approach is applied to evaluate the energy efficiency of three different BEV powertrain topologies. The analysis is carried out assuming two different urban driving conditions, as exemplified by the New European Drive Cycle (NEDC) and the Japanese JC08 drive cycle. Each of the three BEV powertrain topologies is then optimized – in terms of its electric motor size and, where applicable, gear reduction ratio – for minimum energy consumption. The results show that among the three powertrain topologies, the wheel-hub drive without gear reducers consumes the least energy. The energy consumption of BEVs under the more aggressive JC08 drive cycle is consistently 8 % above that under NEDC for all three powertrain topologies considered.     

Passenger experience with quality-enhanced bus service: the tyne and wear ‘superoute’ services

This paper investigates the role that enhanced service quality introduced into a deregulated market has in improving the experience of bus travel by a sample of passengers in the Tyne and Wear area of England. A generalised ordered choice (GOC) model that accounts for preference heterogeneity through random parameters, as well as heteroscedasticity in unobserved variance, and random parameterisation of thresholds, is implemented to identify sources of influence on the overall experience of bus travel in the presence and absence of the quality-enhanced treatment of service. The GOC model is contrasted with a standard ordered logit model, and the marginal effects associated with the preferred GOC model are derived for each influencing attribute, taking into account the various ways in which each influence contributes to the utility associated with each level of bus experience. The paper supports a view that the introduction of quality improvements, via a Quality Bus Partnership, does contribute non-marginally to an increase in a positive bus experience, and signals a way forward through cooperative intervention, to grow patronage. Knowing which attributes successfully deliver a more positive experience (and those that do not) means that resources are effectively targeted at the aspect of service provision which will increase patronage and therefore revenues, satisfying the objectives of both the bus operator and the local authority partner.     

A note on implicit consumer discounting of automobile fuel economy: Reviewing the available evidence

A key element in the long run response of the automotive market to higher fuel prices is consumers' willingness to pay for fuel economy improvements. Eight recent studies are examined and estimates of asset price/operating cost discount rates are derived for each. A critical comparison of results suggests that most are implausible. Plausible estimates range from 4 to 40% as a function of household income.     

Approximate procedures for planning public transit systems: A review and some examples

The approximate analytical models of public transit systems are reviewed. First, the derivation and formation of the standard model form is presented. Once the model is explained in general terms some practical planning applications are considered and evaluated. The model type presents an invaluable tool to the transit planner but a few operational problems need to be considered. Further benefits to the planning professionals would be realized if researchers were to devote more effort to sensitivity analysis as a means of determining which system parameters have the greatest impact upon the operation of the transit system.     

Noisy demand and mode choice

Mode choice under stochastically varying demand is studied via a dynamic mathematical model which describes the behavioural interactions between population groups. The model is developed by assuming competing attractivity functions for automobile and public transit which motivate their use subject to an overall demand for transportation. When this demand is allowed to vary stochastically, a set of stochastic differential equations describing the model are obtained. These are solved for their steady-state values. It is found that noisy demand can structure the system qualitatively differently than when the demand is fixed. The noise is found to generally reduce the level of public transit ridership, but it also changes the values of the threshold at which new regimes occur and, most interestingly, it induces new steady-state solutions for ridership at critical values of the variance of demand. In the latter case, noise becomes a source of new possibilities in the system by triggering a steady-state solution not present in the noise-free environment.     

Bridge sampling for evaluating structural impact of trucks

In this paper, a method for designing a statistically valid sample of bridges is proposed. The need for such a sampling procedure arises from the impracticality of a detailed analysis of the structural effects of new candidate truck configurations on the whole bridge inventory. In this study, a set of bridges from the national inventory was determined for the purpose of selecting a bridge sample. This set of bridges is referred to as the population. The selection of bridges for inclusion in the population was based on the status of the bridge, type of service, structural material, structural system type and functional class. The stratified sampling method was used in the determination of the required sample sizes. According to this method, the population was first divided into sub-populations, or strata. These sub-populations were non-overlapping. In turn, each strata was divided into sub-strata. The characteristics of each sub-stratum were estimated and combined to determine the characterics of the strata. Then the characteristics of the strata were combined to determine the characteristics of the bridge population. A comparison of the results based on the sample and bridge population was conducted in order to verify the validity of the proposed sampling procedure.