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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

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.

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.

Will automotive be the future of mobility or will the motorcar era come to an end in the 21st century? Today, auto-mobility is still growing, but in the future, this will depend on its ability to adapt to the needs of modern society. Disruptive technologies like electrification, automation, and connectivity can make automotive more sustainable by striving for the Six Zero goals: Zero Emission, Zero Energy, Zero Congestion, Zero Accident, Zero Empty, and Zero Cost. These tempting goals can lead not only to a more sustainable ecology, but also to a new economy with more efficient use of the time and money needed for mobility. In this future mobility framework, this article describes the practice-oriented research of the Rotterdam University of Applied Sciences with its regional partners to achieve these goals.

In this paper, a framework is presented for the evaluation of smart grid environment which is called the three-layer model. This three-layer model comprises three specific categories, or ‘layers’, namely, the stakeholder, market and technologies layers. Each layer is defined and explored herein, using an extensive literature study regarding their key elements, their descriptions and an overview of the findings from the literature. The assumption behind this study is that a solid understanding of each of the three layers and their interrelations will help in more effective assessment of residential smart grid pilots in order to better design products and services and deploy smart grid technologies in networks. Based on our review, we conclude that, in many studies, social factors associated with smart grid pilots, such as markets, social acceptance, and end-user and stakeholder demands, are most commonly defined as uncertainties and are therefore considered separately from the technical aspects of smart grids. As such, it is recommended that, in future assessments, the stakeholder and market layers should be combined with the technologies layer so as to enhance interaction between these three layers, and to be able to better evaluate residential smart energy systems in a multidisciplinary context.

The need for zero emission drive is a global necessity that can contribute to mitigate greenhouse gas emissions. In this context, fuel cell hybrid electric vehicles are increasingly attracting interest by governments, companies and academia. While parked they can operate as power generation units, given the proper connection to the electricity grid via vehicle-to-grid integration (V2G), or even power appliances directly (Vehicle-to-Load, V2L). In this study, we analysed the use of a hydrogen fuel cell electric scooter in combined driving, V2G and V2L mode. V2G resulted in the most efficient mode of the three, while V2L led to higher degradation rates. The measured average cell voltage degradation rate was 209 μV/h for driving mode, 356 μV/h for V2G and 648 μV/h for V2L. The insights provided in this study are useful to develop new, optimized and specifically targeted energy management systems for power generation of hydrogen hybrid electric drive vehicles.