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This paper presents an integrated vehicle model to simulate simultaneously the driver, powertrains, chassis, body, road condition, vehicle dynamics and the Active Suspension (AS) system with/without an energy harvesting module. The developed model is used to investigate the ride comfort and influences of energy harvesting AS system on the total energy consumption of battery Electric Vehicles (EVs) relative to EVs with a passive suspension system. Preliminary simulation results show that compared to EVs with a passive suspension system, the ones with AS system improve ride comfort, up to 31% reduction of the vehicle body acceleration RMS value, with an expense of higher energy consumption. This expense can be reduced to about 2.8% when using an energy harvesting AS system. Simulation results also demonstrate that the available energy for recuperation during the AS system operation is significant in relation to the regenerative braking energy of the propulsion system, up to approx. 70% on bumpy road surfaces.

The private motor vehicles are significantly important means of transportation in modern lifestyle, however, these also contribute to a large proportion of the total air pollution and primary energy consumption. In order to develop green transportation system, it becomes imperative to use integrated technologies to achieve reduced emissions and utilize renewable energy. Electric vehicles (EVs) have been considered as one of these technologies to transform the traditional vehicle mix. However, the uptake of EV has been debated on factors like cost, performance (autonomous mileage), charging point infrastructure construction, energy saving, policy and end users’ adaptation. Present study investigates the technology feasibility (which usually refer to EVs’ cost, EV charging, supplier’s customer services quality, EV travel performance) and users’ adaptation of EV in Beijing, which is a key driver for the EV uptake into the Beijing transportation system. The relevant data have been collected and analyzed in the form of questionnaire survey around all of these factors. While considering the user perception and satisfaction, safety of charging and energy bills have also been investigated. According to the data analysis, it has been found the policy of ‘No traffic restrictions for EVs’ (the traffic restrictions means for certain date, from Monday to Friday the motor vehicles with the last register number of 1 and 6, 2 and 7, 3 and 8, 4 and 9, 5 and 0, are restricted to travel, respectively), the availability of the charging infrastructure and technical support are the most significant factors affecting the users’ opinions on using EVs.

Abstract This paper presents a study of the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles. In particular, the aim is to find the number of battery (and supercapacitor) cells to propel a light vehicle to run two different standard driving cycles. Three equivalent circuit models are considered to simulate the battery electrical performance: linear static, non-linear static and non-linear with first-order dynamics. When dimensioning a battery-based vehicle, less complex models may lead to a solution with more battery cells and higher costs. Despite the same tendency, when a hybrid vehicle is taken into account, the influence of the battery models is dependent on the sizing strategy. In this work, two sizing strategies are evaluated: dynamic programming and filter-based. For the latter, the complexity of the battery model has a clear influence on the result of the sizing problem. On the other hand, a modest influence is observed when a dynamic programming strategy is followed.

Abstract This paper describes a new approach to estimate accurately the battery residual capacity (BRC) of the nickel–metal hydride (Ni–MH) battery for modern electric vehicles (EVs). The key to this approach is to model the Ni–MH battery in EVs by using the adaptive neuro-fuzzy inference system (ANFIS) with newly defined inputs and output. The inputs are the temperature and the discharged capacity distribution describing the discharge current profile, while the output is the state of available capacity (SOAC) representing the BRC. The estimated SOAC from ANFIS model and the measured SOAC from experiments are compared, and the results confirm that the proposed approach can provide an accurate estimation of the SOAC under variable discharge currents.

Abstract This study developed a geographical information system-based methodology to maximize the environmental and economic efficiency of large-scale energy plants using different types of biomass. As a precursor to the optimization modelling, multi-criteria spatial analyses and then transport cost optimization are applied taking into account spatial biomass availability and existing road networks, in order to identify optimal biomass energy plant sites for different combinations of biomass types. A geographical information system integrated with a capacitated maximal covering location problem model was employed to assign biomass supply points to biomass energy plants. Capacity limits of the plants and a defined maximum transportation distance were taken into consideration. The resulting information was used to examine major challenges in establishing a large-scale biomass energy plant, biomass supply logistics, environment cost and anticipated traffic congestion. A sensitivity analysis was also carried out to review the influence of plant capacity and maximum transportation distance on economic and environmental sustainability. The proposed methodology was employed utilizing agricultural and forest residues for bioelectricity generation in Queensland, Australia. It was found that 100% bagasse had the highest eco-efficiency for bioelectricity generation from multiple biomass combinations. In contrast, the combination of 70% sawmill residues and 30% forest harvest residues showed the lowest level of traffic congestion (2 trucks per hour). In addition, the impact of traffic congestion of bulky sugarcane residues can be reduced by adding forest residues to the biomass supply. The advantages of the resulting solution are further enhanced when social impacts such as energy security, new income opportunities and job creation are taken into account in addition to the sustainability aspects.

AbstractResting egg production is considered the most common form of dormancy in aquatic invertebrates. Given that many taxa at least partially terminate resting egg state using environmental cues, knowledge on environmental drivers of hatching success is important, particularly within the context of climate change and environmental degradation. Fairy shrimp (anostracans) are temporary wetland specialists that are reliant on resting egg production for population persistence. Temporary wetlands are common in many arid regions projected to experience increases in temperature, and in areas often compromised by human‐mediated activities. In this study, we assessed the combined effects of light and temperature on the hatching success of Streptocephalus cafer (Anostraca) dormant eggs from temporary wetlands in an arid environment. Both temperature and light altered hatching success, with emergent effects evident. Light caused a significant threefold increase in hatching success overall, while temperature effects were non‐linear, with hatching optimised at 27°C, and especially under light conditions. These results are discussed within the context of shifting climates and disturbances to temporary wetland ecosystems.

AbstractClimate change will not only shift environmental means but will also increase the intensity of extreme events, exerting additional stress on ecosystems. While field observations on the ecological consequences of heat waves are emerging, experimental evidence is rare, and lacking at the community level. Using a novel “near‐natural” outdoor mesocosms approach, this study tested whether marine summer heat waves have detrimental consequences for macrofauna of a temperate coastal community, and whether sequential heat waves provoke an increase or decrease of sensitivity to thermal stress. Three treatments were applied, defined and characterized through a statistical analysis of 15 years of temperature records from the experimental site: (1) no heat wave, (2) two heat waves in June and July followed by a summer heat wave in August and (3) the summer heat wave only. Overall, 50% of the species showed positive, negative or positive/negative responses in either abundance and/or biomass. We highlight four possible ways in which single species responded to either three subsequent heat waves or one summer heat wave: (1) absence of a response (tolerance, 50% of species), (2) negative accumulative effects by three subsequent heat waves (tellinid bivalve), (3) buffering by proceeding heat waves due to acclimation and/or shifts in phenology (spionid polychaete) and (4) an accumulative positive effect by subsequent heat waves (amphipod). The differential responses to single or sequential heat waves at the species level entailed shifts at the community level. Community‐level differences between single and triple heat waves were more pronounced than those between regimes with vs. without heat waves. Detritivory was reduced by the single heat wave while suspension feeding was less common in the triple heat wave regime. Critical extreme events occur already today and will occur more frequently in a changing climate, thus, leading to detrimental impacts on coastal marine systems.

This paper presents a comprehensive and validated inventory of road transport emissions worldwide. The bottom-up calculation correlates within 2% and 10% with fuel sales data in Organisation for Economic Co-operation and Development (OECD) and non-OECD regions, respectively; this adds credibility to the results. The inventory covers eight exhaust compounds emitted by five vehicle categories and five fuel types each. For many non-OECD countries, road transport exhaust emissions have been calculated for the first time at this level of detail. Furthermore, this paper provides a conservative estimate of primary particulate matter emissions from diesel and gasoline vehicles. The Group of Seven countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) together with Brazil, China, India, Mexico, and Russia account for more than three-quarters of all considered exhaust emissions, followed by major countries in the Middle East and Southeast Asia. Action in these 15 countries could reduce emissions for the whole region significantly. Exhaust control and maintenance can focus on motorized two-wheelers, buses, and heavy-duty trucks. The inventory is particularly suited for comparisons across countries and regions. Data uncertainties in transport volumes and real-world emissions, notably of hydrocarbon and particulate matter, should be reduced.