The micro-scale fuel consumption model is a tool commonly used to evaluate the effect of traffic flow conditions on vehicle fuel consumptions, which is an essential step in developing traffic management strategies for...
The micro-scale fuel consumption model is a tool commonly used to evaluate the effect of traffic flow conditions on vehicle fuel consumptions, which is an essential step in developing traffic management strategies for saving fuels. In developing any micro-scale fuel consumption model, the Vehicle Specific Power (VSP) binning method has been widely adopted in recent years as a fundamental approach. Existing studies have shown that the high distribution frequency when VSP=0 contributes to high fuel consumptions, so a question quickly emerged about whether VSP=0 should be designed as an independent VSP bin in the VSP binning method. This paper strives to compare different VSP binning methods for Light-Duty Vehicles (LDVs) on urban roads in Beijing in terms of their effects on the estimation of fuel consumptions. After collecting and processing field vehicle activity data and fuel consumption data, three VSP binning methods are proposed for the study. Then, total fuel consumptions and fuel consumption factors are calculated by using the proposed VSP binning methods as well as the second-by-second and average travel speed data. Finally, the estimation accuracy of total fuel consumptions and fuel consumption factors based on the three different VSP binning methods are compared for LDVs on urban roads. The study proves that an independent VSP bin at VSP=0 is indeed necessary, which can improve the estimation accuracy on both total fuel consumptions and fuel consumption factors.
Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is ...
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We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of Hénon maps. It is known that coexisting basins of attraction lead to a hysteretic behaviour in the...
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We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of Hénon maps. It is known that coexisting basins of attraction lead to a hysteretic behaviour in the diagrams of the density of states as a function of a varying parameter. Chimera states, for which coherent and incoherent domains occur simultaneously, emerge as a consequence of the coexistence of basin of attractions for each state. Consequently, the distribution of chimera states can remain invariant by a parameter change, as well as it can suffer subtle changes when one of the basins ceases to exist. A similar phenomenon is observed when perturbations are applied in the initial conditions. By means of the uncertainty exponent, we characterise the basin boundaries between the coherent and chimera states, and between the incoherent and chimera states, respectively. This way, we show that the density of chimera states can be not only moderately sensitive but also highly sensitive to initial conditions. This chimera's dilemma is a consequence of the fractal and riddled nature of the basins boundaries. Coupled dynamical systems have been used to describe the behaviour of real complexsystems, such as power grids, neuronal networks, economics, and chemical reactions. Furthermore, these systems can exhibit various kinds of interesting nonlinear dynamics, e.g. synchronisation, chaotic oscillations, and chimera states. The chimera state is a spatio-temporal pattern characterised by the coexistence of coherent and incoherent dynamics. It has been observed in a great variety of systems, ranging from theoretical and experimental arrays of oscillators, to in phenomena such as the unihemispheric sleep of cetaceans. We study the chimera state in a circulant network of Hénon maps, seeking to determine how the density of states in the network depends on the system parameters and the initial conditions. We have found that, as expected, the density of states might be inva
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based ...
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based on the behavior analysis. Firstly, customers' active behavior is represented by the quantity of active customer households. Based on the analysis of customer behaviors, a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo method. Then, with the inputs as the quantity of active customer households and time of photovoltaic power generation, an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical appliances. By combing the average usage time of electrical appliances, load characteristics are analyzed based on usage state of electrical appliance of distributed power customers. Finally, the simulation results verify the effectiveness of the proposed method.
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