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These files must be understood in relation to the main text. EV2ndlife_workbook.m - Matlab code containing all input data and methodology used to generate and plot results. EV2ndlife_alldata.xlsx - data generated by the above Matlab code, whose plots are included as figures in the main text and Supplementary Information. BEV_PHEV_salesdata.xlsx - sales data of BEVs and PHEVs broken down by make/model for years 2013-2016, copied from the website EV Volumes, and their use in calculating the average EV battery capacity in years 2013-2016.

This is the second paper in a series of two that introduce our research on dynamic programming on new energy vehicles. In the first paper, we introduce the four main problems (the interpolation leakage problem, the dimension disaster problem, the standardization problem and the Markov problem) of dynamic programming on new energy vehicles, and put forward a unified dynamic programming model and its solution method for electric vehicles and hybrid electric vehicles. In this paper, we present a unified dynamic programming model and its solution method to solve these problems for fuel cell electric vehicles. The results demonstrate that the proposed method is much better than Basic Dynamic Programming and Level-Set Dynamic Programming in both calculation time and computation accuracy.

The future of road transportation systems faces fundamental changes concerning technological progress and business models. Automated and electric vehicles are coming into the market and evolving towards a service-based mobility system with promises to tackle energy and environmental issues in the mobility sector. Although recent studies have begun to explore the potential impact of shared and privately owned automated and electric vehicles (AEVs) mostly from an operational perspective, little is known about the life cycle impact of such future transport systems. To fill this gap, this paper aims to compare the life cycle environmental impacts of shared vs privately owned AEVs in a regional context. A life cycle assessment (LCA) approach is developed to appraise impact categories with a direct effect on human health, ecosystems, and resources availability. Given that automated vehicles are not yet being used massively, the LCA is applied to synthetic travel demand data to assess the characteristics of privately-owned AEVs and the results of an optimization model that determines the vehicle fleet and driving patterns of shared AEVs serving a regional case-study in the central region of Portugal. Two different vehicle seating capacities - one passenger (non-ridesharing) and four passengers (ridesharing) – are considered to evaluate shared mobility systems. Results show that shared mobility systems yield a potential reduction of up to 42% (with 4 passengers per vehicle) of the system's environmental impacts compared to privately owned automated vehicles. Human toxicity, mineral resource scarcity, and marine and freshwater ecotoxicity are the impact categories with a higher potential of reduction. ; Transport and Planning

In this article, we introduces a model based on big data analysis to characterize the travel times of buses in public transportation systems. Travel time is a critical factor in evaluating the accessibility of opportunities and the overall quality of service of public transportation systems. The methodology applies data analysis to compute estimations of the travel time of public transportation buses by leveraging both open-source and private information sources. The approach is evaluated for the public transportation system in Montevideo, Uruguay using information about bus stop locations, bus routes, vehicle locations, ticket sales, and timetables. The estimated travel times from the proposed methodology are compared with the scheduled timetables, and relevant indicators are computed based on the findings. The most relevant quantitative results indicate a reasonably good level of punctuality in the public transportation system. Delays were between 10.5% and 13.9% during rush hours and between 8.5% and 13.7% during non-peak hours. Delays were similarly distributed for working days and weekends. In terms of speed, the results show that the average operational speed is close to 18 km/h, with short local lines exhibiting greater variability in their speed.

Weather is identified as one of many factors that influence the demand for cycling. Weather patterns will change due to expected climate change. The aim of this article is to study the extent to which climate change influences the cycling frequency. The analysis in this article is conducted using an econometric model based on data spanning over four years on weather indicators and the cycling frequency in the Norwegian city of Bodø, which is located north of the Arctic Circle. According to the projections for climate change, both temperature and quantity of precipitation are expected to increase in this area during the next century. An important consequence of changes in the climate in the studied region is the reduced duration of what can be characterised as the winter season. However, this consequence is highly uncertain. When using Norway’s middle projections for climate change by 2050, the analysis shows a moderate increase in cycling frequency of 6.2%. For the reduced winter period, the cycle rate might be two and three times higher in 2050 compared to the current level. Both estimates assume that every other potential impact on cycling rates remain equal.

The trolleybus traction grids, an effective electrification solution for urban transport, can become more sustainable and efficient through the direct integration of solar photovoltaic systems. Previous research shows different results for this application. The aim of this study is to identify a set of Key Performance Indicators (KPIs) and to study their effects on the feasibility of integrating PV in two trolleygrids, Arnhem (Nl) and Gdynia (Pl). This is done through the simulation of the yearly operation of the trolleygrids with PV systems integrated at substation level. It is demonstrated that the integration of PV in trolleybus traction grids can vary depending on the characteristics of the grid and the location. In particular, the increase in power demand, in number of sections served, in the traffic conditions and in the radiation and sunshine duration levels induces an improvement in the performance of PV. The average length of the sections supplied and the removal of the HVAC demand on the other hand, are not beneficial to the integration of PV. It is concluded that the potential of integrating PV in the Gdynia trolleygrid is higher than the one in Arnhem. It is also shown, that the introduction of storage always improves the PV potential. ; Electrical Engineering | Sustainable Energy Technology

The urban heat island effect is often associated with large metropolises. However, in the Netherlands even small cities will be affected by the phenomenon in the future (Hove et al., 2011), due to the dispersed or mosaic urbanisation patterns in particularly the southern part of the country: the province of North Brabant. This study analyses the average night time land surface temperature (LST) of 21 North-Brabant urban areas through 22 satellite images retrieved by Modis 11A1 during the 2006 heat wave and uses Landsat 5 Thematic Mapper to map albedo and normalized difference temperature index (NDVI) values. Albedo, NDVI and imperviousness are found to play the most relevant role in the increase of night-time LST. The surface cover cluster analysis of these three parameters reveals that the 12 “urban living environment” categories used in the region of North Brabant can actually be reduced to 7 categories, which simplifies the design guidelines to improve the surface thermal behaviour of the different neighbourhoods thus reducing the Urban Heat Island (UHI) effect in existing medium size cities and future developments adjacent to those cities. Tema. Journal of Land Use, Mobility and Environment, Vol 9, N° 1 (2016): Planning for livable and safe cities: Extreme weather events caused by climate change

Electric vehicles (EVs) have the potential to play a crucial role in clean and intelligent power systems. The key to this potential lies in the flexibility that EVs provide by the ability to shift their electricity demand in time. This flexibility can be used to facilitate the integration of renewable energy sources by adjusting EV demand to the variable production of wind or solar energy. On the other hand, the same flexibility can be employed to reduce peaks in network load that could result from a massive adoption of EVs. This PhD thesis aims to improve the understanding of the value of flexible EV demand in the context of multi-actor power systems with a high share of renewable energy sources. We first explore flexible EV demand from a distribution network point of view, and then in the light of renewable energy integration. Moreover, we also bring these perspectives together and investigate mechanisms to align the different objectives related to the distribution networks and renewable energy integration. This thesis thus demonstrates the value of demand response in the sustainable power systems of the future.